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supplychain-ag-018	supplychain-ag.pdf	18	validates new and existing policies so that the policies adhere to the IAM policy language (JSON) and IAM best practices. IAM Access Analyzer provides more than 100 policy checks and actionable recommendations to help you author secure and functional policies. For more information, see Validate policies with IAM Access Analyzer in the IAM User Guide. • Require multi-factor authentication (MFA) – If you have a scenario that requires IAM users or a root user in your AWS account, turn on MFA for additional security. To require MFA when API operations are called, add MFA conditions to your policies. For more information, see Secure API access with MFA in the IAM User Guide. For more information about best practices in IAM, see Security best practices in IAM in the IAM User Guide. Troubleshooting AWS Supply Chain identity and access Use the following information to help you diagnose and ﬁx common issues that you might encounter when working with AWS Supply Chain and IAM. Topics • I'm not authorized to perform an action in AWS Supply Chain • I'm not authorized to perform iam:PassRole • I want to allow people outside of my AWS account to access my AWS Supply Chain resources Troubleshooting 52 AWS Supply Chain Administrator Guide I'm not authorized to perform an action in AWS Supply Chain If the AWS Management Console that you're not authorized to perform an action, then you must contact your administrator for assistance. Your administrator is the person that provided you with your user name and password. The following example error occurs when the mateojackson IAM user tries to use the console to view details about a ﬁctional my-example-widget resource but doesn't have the ﬁctional scn:GetWidget permissions. User: arn:aws:iam::123456789012:user/mateojackson is not authorized to perform: scn:GetWidget on resource: my-example-widget In this case, Mateo asks his administrator to update his policies to allow him to access the my- example-widget resource using the scn:GetWidget action. I'm not authorized to perform iam:PassRole If you receive an error that you're not authorized to perform the iam:PassRole action, your policies must be updated to allow you to pass a role to AWS Supply Chain. Some AWS services allow you to pass an existing role to that service instead of creating a new service role or service-linked role. To do this, you must have permissions to pass the role to the service. The following example error occurs when an IAM user named marymajor tries to use the console to perform an action in AWS Supply Chain. However, the action requires the service to have permissions that are granted by a service role. Mary does not have permissions to pass the role to the service. User: arn:aws:iam::123456789012:user/marymajor is not authorized to perform: iam:PassRole In this case, Mary's policies must be updated to allow her to perform the iam:PassRole action. If you need help, contact your AWS administrator. Your administrator is the person who provided you with your sign-in credentials. Troubleshooting 53 AWS Supply Chain Administrator Guide I want to allow people outside of my AWS account to access my AWS Supply Chain resources You can create a role that users in other accounts or people outside of your organization can use to access your resources. You can specify who is trusted to assume the role. For services that support resource-based policies or access control lists (ACLs), you can use those policies to grant people access to your resources. To learn more, consult the following: • To learn whether AWS Supply Chain supports these features, see How AWS Supply Chain works with IAM. • To learn how to provide access to your resources across AWS accounts that you own, see Providing access to an IAM user in another AWS account that you own in the IAM User Guide. • To learn how to provide access to your resources to third-party AWS accounts, see Providing access to AWS accounts owned by third parties in the IAM User Guide. • To learn how to provide access through identity federation, see Providing access to externally authenticated users (identity federation) in the IAM User Guide. • To learn the diﬀerence between using roles and resource-based policies for cross-account access, see Cross account resource access in IAM in the IAM User Guide. AWS managed policies for AWS Supply Chain An AWS managed policy is a standalone policy that is created and administered by AWS. AWS managed policies are designed to provide permissions for many common use cases so that you can start assigning permissions to users, groups, and roles. Keep in mind that AWS managed policies might not grant least-privilege permissions for your speciﬁc use cases because they're available for all AWS customers to use. We recommend that you reduce permissions further by deﬁning customer managed policies that are speciﬁc to your use cases. You cannot change the
supplychain-ag-019	supplychain-ag.pdf	19	the IAM User Guide. AWS managed policies for AWS Supply Chain An AWS managed policy is a standalone policy that is created and administered by AWS. AWS managed policies are designed to provide permissions for many common use cases so that you can start assigning permissions to users, groups, and roles. Keep in mind that AWS managed policies might not grant least-privilege permissions for your speciﬁc use cases because they're available for all AWS customers to use. We recommend that you reduce permissions further by deﬁning customer managed policies that are speciﬁc to your use cases. You cannot change the permissions deﬁned in AWS managed policies. If AWS updates the permissions deﬁned in an AWS managed policy, the update aﬀects all principal identities (users, groups, and roles) that the policy is attached to. AWS is most likely to update an AWS managed AWS managed policies 54 AWS Supply Chain Administrator Guide policy when a new AWS service is launched or new API operations become available for existing services. For more information, see AWS managed policies in the IAM User Guide. AWS managed policy: AWSSupplyChainFederationAdminAccess AWSSupplyChainFederationAdminAccess provides AWS Supply Chain federated users access to the AWS Supply Chain application, including the required permissions to perform actions within the AWS Supply Chain application. The policy provides administrative permissions over IAM Identity Center users and groups and is attached to a role created by AWS Supply Chain for you. You shouldn't attach the AWSSupplyChainFederationAdminAccess policy to any other IAM entities. Although this policy provides all access to AWS Supply Chain through the scn:* permissions, the AWS Supply Chain role determines your permissions. The AWS Supply Chain role only includes the required permissions, and don't have permissions to the admin APIs. Permissions details This policy includes the following permissions: • Chime – Provides access to create or delete users under an Amazon Chime AppInstance; Provides access to manage channel, channel members, and moderators; Provides access to send messages to channel. Chime operations are scoped to app instances tagged with "SCNInstanceId". • AWS IAM Identity Center (AWS SSO) – Provides permissions required to associate and disassociate user proﬁles, list proﬁles association, list application assignments, describe application, describe instance, and get application assignment conﬁguration in IAM Identity Center. • AppFlow – Provides access to create, update, and delete connection proﬁles; Provides access to create, update, delete, start, and stop ﬂows; Provides access to tag and untag ﬂows and describe ﬂow records. • Amazon S3 – Provides access to list all buckets. Provides GetBucketLocation, GetBucketPolicy, PutObject, GetObject, and ListBucket access to buckets with resource arn arn:aws:s3:::aws- supply-chain-data-. AWSSupplyChainFederationAdminAccess 55 AWS Supply Chain Administrator Guide • SecretsManager – Provides access to creating secrets and updating secret policy. • KMS – Provides Amazon AppFlow service the access to list keys and key alias. Provides DescribeKey, CreateGrant and ListGrants permissions to KMS keys tagged with key-value aws- suply-chain-access : true; Provides access to create secrets and update secret policy. The permissions (kms:ListKeys, kms:ListAliases, kms:GenerateDataKey, and kms:Decrypt) are not restricted to Amazon AppFlow and these permissions can be granted to any AWS KMS Key in your account. To view the permissions of this policy, see AWSSupplyChainFederationAdminAccess in the AWS Management Console. AWS Supply Chain updates to AWS managed policies The following table lists details about updates to AWS managed policies for AWS Supply Chain since this service began to track these changes. For automatic alerts about changes to this page, subscribe to the RSS feed on the AWS Supply Chain Document history page. Change Description Date AWSSupplyChainFede rationAdminAccess – Updated AWS Supply Chain updated the managed policy to allow December 10, 2024 policy federated users access to ListApplicationAssignments, DescribeApplication, DescribeI nstance, and GetApplic ationAssignmentConﬁguratio n operations in IAM Identity Center. AWSSupplyChainFede rationAdminAccess – Updated policy AWS Supply Chain updated the managed policy to allow federated users access to ListProﬁleAssociations November 01, 2023 Policy updates 56 AWS Supply Chain Change Administrator Guide Description Date operations in IAM Identity Center. AWSSupplyChainFede rationAdminAccess – Updated AWS Supply Chain updated the managed policy to allow September 21, 2023 policy federated users access to the PutObject and GetObject operations on the dedicated S3 bucket with resource arn arn:aws:s3:::aws-supply- chain-data-. AWSSupplyChainFede rationAdminAccess – New AWS Supply Chain added a new policy to allow federated March 01, 2023 policy users to access the AWS Supply Chain application. This includes permissions necessary to perform actions within the AWS Supply Chain application. AWS Supply Chain started tracking changes AWS Supply Chain started tracking changes for its AWS March 01, 2023 managed policies. Compliance validation for AWS Supply Chain Third-party auditors assess the security and compliance of AWS Supply Chain as part of multiple AWS compliance programs. These include SOC, PCI, FedRAMP, HIPAA, and others. For a list of AWS services that fall within the scope of speciﬁc compliance programs, see
supplychain-ag-020	supplychain-ag.pdf	20	added a new policy to allow federated March 01, 2023 policy users to access the AWS Supply Chain application. This includes permissions necessary to perform actions within the AWS Supply Chain application. AWS Supply Chain started tracking changes AWS Supply Chain started tracking changes for its AWS March 01, 2023 managed policies. Compliance validation for AWS Supply Chain Third-party auditors assess the security and compliance of AWS Supply Chain as part of multiple AWS compliance programs. These include SOC, PCI, FedRAMP, HIPAA, and others. For a list of AWS services that fall within the scope of speciﬁc compliance programs, see AWS Services in Scope by Compliance Program. For general information, see AWS Compliance Programs. You can download third-party audit reports with AWS Artifact. For more information, see Downloading Reports in AWS Artifact. Compliance validation 57 AWS Supply Chain Administrator Guide Your compliance responsibility when you use AWS Supply Chain is determined by the sensitivity of your data, your company's compliance objectives, and applicable laws and regulations. AWS provides the following resources to help with compliance: • Security and Compliance Quick Start Guides – These deployment guides discuss architectural considerations and provide steps to take when you deploy security-focused and compliance- focused baseline AWS environments. • Architecting for HIPAA Security and Compliance Whitepaper – This whitepaper describes how companies can use AWS to create HIPAA-compliant applications. • AWS Compliance Resources – This collection of workbooks and guides might apply to your industry and location. • Evaluating Resources with Rules in the AWS Conﬁg Developer Guide – This guide assesses how well your resource conﬁgurations comply with internal practices, industry guidelines, and regulations. • AWS Security Hub – This AWS service provides a comprehensive view of your security state within AWS to help you check your compliance with security industry standards and best practices. Resilience in AWS Supply Chain The AWS global infrastructure is built around AWS Regions and Availability Zones. AWS Regions provide multiple physically separated and isolated Availability Zones. These are connected with low-latency, high-throughput, and highly redundant networking. With Availability Zones, you can design and operate applications and databases that automatically fail over between zones without interruption. Availability Zones are more highly available, fault tolerant, and scalable than traditional single or multiple data center infrastructures. For more information about AWS Regions and Availability Zones, see AWS Global Infrastructure. In addition to the AWS global infrastructure, AWS Supply Chain oﬀers several features to help support your data resiliency and backup needs. Logging and Monitoring AWS Supply Chain Logging and Monitoring is an important part of maintaining the reliability, availability, and performance of AWS Supply Chain and your other AWS solutions. AWS provides the AWS CloudTrail monitoring tool to watch AWS Supply Chain, report when something is wrong, and take automatic actions when appropriate. Resilience 58 AWS Supply Chain Note Administrator Guide APIs called only from the AWS Supply Chain console are captured in AWS CloudTrail. AWS CloudTrail captures API calls and related events made by or on behalf of your AWS account and delivers the log ﬁles to an Amazon S3 bucket that you specify. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred. You can view the AWS Supply Chain events under scn.amazonaws.com. For more information, see the AWS CloudTrail User Guide. Note Note the following with AWS Supply Chain: • When you invite users that don't have access to AWS Supply Chain, these users don't receive information in the notiﬁcations that they receive from the web application. Invited users receive an email notiﬁcation with a link to the web application. They can only log in and view the content in the notiﬁcation if they have the required user permissions. • All users with or without user permissions to a particular Insight can view the Insights chat messages. • As an application admin, when you are add users to the AWS Supply Chain instance, they have access to the AWS KMS key. You can manage the user permissions to add or remove users. For more information on user permissions, see Managing user permission roles. AWS Supply Chain data events in CloudTrail Note The web application APIs listed under AWS Supply Chain web application APIs are listed in the data events in CloudTrail. Data events provide information about the resource operations performed on or in a resource (for example, reading or writing to an Amazon S3 object). These are also known as data plane AWS Supply Chain data events in CloudTrail 59 AWS Supply Chain Administrator Guide operations. Data events are often high-volume activities. By default, CloudTrail doesn’t log data events. The CloudTrail Event history doesn't record data events. Additional charges apply for data events. For more information about CloudTrail pricing, see AWS CloudTrail Pricing.
supplychain-ag-021	supplychain-ag.pdf	21	application APIs listed under AWS Supply Chain web application APIs are listed in the data events in CloudTrail. Data events provide information about the resource operations performed on or in a resource (for example, reading or writing to an Amazon S3 object). These are also known as data plane AWS Supply Chain data events in CloudTrail 59 AWS Supply Chain Administrator Guide operations. Data events are often high-volume activities. By default, CloudTrail doesn’t log data events. The CloudTrail Event history doesn't record data events. Additional charges apply for data events. For more information about CloudTrail pricing, see AWS CloudTrail Pricing. You can log data events for the AWS Supply Chain resource types by using the CloudTrail console, AWS CLI, or CloudTrail API operations. • To log data events using the CloudTrail console, create a trail or event data store to log data events, or update an existing trail or event data store to log data events. 1. Choose Data events to log data events. 2. From the Data event type list, choose the resource type for which you want to log data events. 3. Choose the log selector template you want to use. You can log all data events for the resource type, log all readOnly events, log all writeOnly events, or create a custom log selector template to ﬁlter on the readOnly, eventName, and resources.ARN ﬁelds. • To log data events using the AWS CLI, conﬁgure the --advanced-event-selectors parameter to set the eventCategory ﬁeld equal to Data and the resources.type ﬁeld equal to the resource type value . You can add conditions to ﬁlter on the values of the readOnly, eventName, and resources.ARN ﬁelds. • To conﬁgure a trail to log data events, run the put-event-selectors command. For more information, see Logging data events for trails with the AWS CLI. • To conﬁgure an event data store to log data events, run the create-event-data-store command to create a new event data store to log data events, or run the update-event-data-store command to update an existing event data store. For more information, see Logging data events for event data stores with the AWS CLI. *You can conﬁgure advanced event selectors to ﬁlter on the eventName, readOnly, and resources.ARN ﬁelds to log only those events that are important to you. For more information about these ﬁelds, see AdvancedFieldSelector. AWS Supply Chain data events in CloudTrail 60 AWS Supply Chain Administrator Guide AWS Supply Chain management events in CloudTrail Management events provide information about management operations that are performed on resources in your AWS account. These are also known as control plane operations. By default, CloudTrail logs management events. AWS Supply Chain logs all control plane operations to CloudTrail as management events. AWS Supply Chain web application APIs The APIs listed in this section are called by AWS Supply Chain applications on behalf of federated users. These APIs are not visible in the CloudTrail logs and are not captured in the Service Authorization Reference document, see AWS Supply Chain. Access to these APIs are controlled by AWS Supply Chain applications based on federated user role permissions. You shouldn’t try to control access to these APIs to prevent distrupting the AWS Supply Chain applications. User roles The following APIs are used for managing users, user roles, user notiﬁcations, and chat messages in AWS Supply Chain. scn:AddMembersToResourceBasedChat scn:AssignGalaxyRoleToUser scn:AssociateUser scn:BatchGetUsers scn:BatchMarkNotificationAsDelivered scn:CreateRole scn:DeleteRole scn:DescribeChatForUser scn:GetAccessDetailConfig scn:GetChatPreferencesForUser scn:GetMessagingSessionConnectionDetails scn:GetNotificationsPreference scn:GetOrCreateChimeUser scn:GetOrCreateResourceBasedChat scn:GetOrCreateUserBasedChat scn:GetOrganizationInfo scn:GetResourceBasedChatArn scn:GetUserDetails scn:ListChatMembers AWS Supply Chain management events in CloudTrail 61 AWS Supply Chain Administrator Guide scn:ListChatMessages scn:ListChatModerators scn:ListChats scn:ListRoles scn:ListUserNotifications scn:ListUsersWithRole scn:MarkNotificationAsDelivered scn:MarkNotificationAsRead scn:RemoveMemberFromResourceBasedChat scn:RemoveUser scn:SearchChimeUsers scn:SearchUsers scn:SendChatMessage scn:SetNotificationsPreference scn:UpdateChatPreferencesForUser scn:UpdateChatReadMarker scn:UpdateOrganizationInfo scn:UpdateRole scn:UpdateUser Data lake The following APIs are used for creating and managing data ﬂows and connections in data lake. scn:CreateConnection scn:CreateDataflow scn:CreateDeleteDataByPartitionJob scn:CreateExtractFlows scn:CreatePresignedUrl scn:CreateSampleParsingJob scn:CreateSapODataConnection scn:CreateUpdateDatasetSchemaJob scn:DeleteConnection scn:DeleteDataflow scn:DeleteExtractFlows scn:DeleteSapODataConnection scn:describeDatasetGroup scn:DescribeDataset scn:DescribeJob Web application APIs 62 AWS Supply Chain Administrator Guide scn:GetConnection scn:GetCreateExtractFlowsStatus scn:GetDataflow scn:ListConnections scn:ListCustomerFiles scn:ListDataflows scn:ListDataflowStats scn:ListDatasets scn:UpdateConnection scn:UpdateDataflow scn:UpdateExtractFlow Insights The following APIs are used by the Insights application to manage ﬁlters, watchlists, and view inventory changes. scn:AddModeratorToResourceBasedChat scn:ComputePostRebalancedQuantities scn:ComputePostRebalancedQuantitiesV1 scn:CreateInsightFilter scn:CreateInsightSubscription scn:DeleteInsightFilter scn:DeleteInsightSubscription scn:GetInsightLineItem scn:GetInsightSubscription scn:GetInstanceAttribute scn:GetInstanceRequiredDatasetAvailabilityStatus scn:GetKpiData scn:GetModelEndpointStatus scn:GetPIVForProduct scn:GetPIVForSite scn:GetPIVForSiteAndProduct scn:GetPIVForSitesAndProducts scn:GetProducts scn:GetProductSummaryAggregates scn:GetSites scn:GetSiteSummaryAggregates scn:IsUserAuthorizedForInsightLineItem Web application APIs 63 AWS Supply Chain Administrator Guide scn:ListCustomAttributeValues scn:ListGeographiesAsGalaxyAdmin scn:ListInsightFilters scn:ListInsightLineItems scn:ListInsightSubscriptions scn:ListInventoryQuantityAggregates scn:ListInventoryRisksBySiteAndProduct scn:ListInventorySummariesBySite scn:ListPIVProductsBySite scn:ListProductHierarchiesAsGalaxyAdmin scn:ListProducts scn:ListProductsAsGalaxyAdmin scn:ListSites scn:ListUsers scn:PotentiallyComputeThenListRebalancingOptionsForInsightLineItem scn:RegisterInstanceAttribute scn:UpdateInsightFilter scn:UpdateInsightLineItemStatus scn:UpdateInsightSubscription scn:UpdateRebalancingOptionStatus scn:UpdateRebalancingOptionStatusV1 Demand Planning The following APIs are used in AWS Supply Chain to create and manage forecasts, demand plans, or workbooks. scn:AssociateDatasetWithWorkbook scn:CreateBaselineForecast scn:CreateDemandPlan scn:CreateDemandPlanningCycle scn:CreateDemandPlanningDatasetExportJob scn:CreateDerivedForecast scn:CreateWorkbook scn:DeleteDemandForecastConfig scn:DeleteDemandPlanningCycle scn:DeleteDerivedForecast scn:DeleteWorkbook scn:DescribeBaselineForecast Web application APIs 64 AWS Supply Chain Administrator Guide scn:DescribeDemandPlanningCycleAccuracyJob scn:DescribeDerivedForecast scn:DescribePlanningCycle scn:DescribeWorkbook scn:DisassociatePlanningCycle scn:GetDemandForecastConfig scn:GetDemandPlan scn:GetDemandPlanningCycle scn:GetDemandPlanningCycleAccuracy scn:GetDemandPlanningDatasetJob scn:ListDemandPlans scn:ListDerivedForecasts scn:ListForecastingJobs scn:ListPlanningCycles scn:ListWorkbooks scn:PublishDemandPlan scn:PutDemandForecastConfig scn:StartDemandPlanningCycleAccuracyJob scn:StartForecastingJob scn:UpdateDemandPlan scn:UpdateDemandPlanningCycleMetadata scn:UpdateWorkbook Supply Planning The following APIs are used in AWS Supply Chain
supplychain-ag-022	supplychain-ag.pdf	22	AWS Supply Chain Administrator Guide scn:ListCustomAttributeValues scn:ListGeographiesAsGalaxyAdmin scn:ListInsightFilters scn:ListInsightLineItems scn:ListInsightSubscriptions scn:ListInventoryQuantityAggregates scn:ListInventoryRisksBySiteAndProduct scn:ListInventorySummariesBySite scn:ListPIVProductsBySite scn:ListProductHierarchiesAsGalaxyAdmin scn:ListProducts scn:ListProductsAsGalaxyAdmin scn:ListSites scn:ListUsers scn:PotentiallyComputeThenListRebalancingOptionsForInsightLineItem scn:RegisterInstanceAttribute scn:UpdateInsightFilter scn:UpdateInsightLineItemStatus scn:UpdateInsightSubscription scn:UpdateRebalancingOptionStatus scn:UpdateRebalancingOptionStatusV1 Demand Planning The following APIs are used in AWS Supply Chain to create and manage forecasts, demand plans, or workbooks. scn:AssociateDatasetWithWorkbook scn:CreateBaselineForecast scn:CreateDemandPlan scn:CreateDemandPlanningCycle scn:CreateDemandPlanningDatasetExportJob scn:CreateDerivedForecast scn:CreateWorkbook scn:DeleteDemandForecastConfig scn:DeleteDemandPlanningCycle scn:DeleteDerivedForecast scn:DeleteWorkbook scn:DescribeBaselineForecast Web application APIs 64 AWS Supply Chain Administrator Guide scn:DescribeDemandPlanningCycleAccuracyJob scn:DescribeDerivedForecast scn:DescribePlanningCycle scn:DescribeWorkbook scn:DisassociatePlanningCycle scn:GetDemandForecastConfig scn:GetDemandPlan scn:GetDemandPlanningCycle scn:GetDemandPlanningCycleAccuracy scn:GetDemandPlanningDatasetJob scn:ListDemandPlans scn:ListDerivedForecasts scn:ListForecastingJobs scn:ListPlanningCycles scn:ListWorkbooks scn:PublishDemandPlan scn:PutDemandForecastConfig scn:StartDemandPlanningCycleAccuracyJob scn:StartForecastingJob scn:UpdateDemandPlan scn:UpdateDemandPlanningCycleMetadata scn:UpdateWorkbook Supply Planning The following APIs are used in AWS Supply Chain to create and manage supply plans. scn:CreateReplenishmentPipeline scn:GetReplenishmentPipeline scn:UpdateReplenishmentPipeline scn:ListReplenishmentPipelinesByInstance scn:GetInstanceReplenishmentConfig scn:CreateBacktest scn:CreateReplenishmentReviewInstanceConfig scn:GetReplenishmentReviewInstanceConfig scn:ListReplenishmentVendors scn:GetExceptionsSupplyInsightsStatistics scn:GetPorSupplyInsightsStatistics scn:GetPlanToPOConversionAnalytics Web application APIs 65 AWS Supply Chain Administrator Guide scn:GetPurchasePlanStatistics scn:ListPlanExceptions scn:ListPurchaseOrderRequestLines scn:UpdatePurchaseOrderRequestLines scn:ListBomPurchasePlans scn:ListBomProductionPlans scn:ListBomTransferPlans scn:ListBomInsights scn:ListBomProcesses scn:ExportBomPlans scn:GetBomPlanSummary scn:GetDashboardAnalytics scn:GetPurchaseOrderRequestExplanation scn:ListBomSupplyPlan scn:GetBomPlanRecordDetails scn:GetBomPlanSummaryAnalytics scn:ListBomPurchaseOrders scn:ListBomTransferOrders scn:ListBomProductionOrders scn:ExportAllExplodedBoms scn:ExportBillOfMaterials scn:ExportInventoryPolicy scn:ExportProductionProcess scn:ExportSourcingRule scn:ExportTransportationLane scn:ExportVendorLeadTime scn:ImportBillOfMaterials scn:ImportInventoryPolicy scn:ImportProductionProcess scn:ImportSourcingRule scn:ImportTransportationLane scn:ImportVendorLeadTime Amazon Q in AWS Supply Chain The following APIs are used in Amazon Q in AWS Supply Chain. scn:GetQMessage scn:ListQMessages Web application APIs 66 AWS Supply Chain Administrator Guide scn:PutQMessageFeedback scn:SendQMessage scn:GetQEnablementStatus scn:UpdateQEnablementStatus Managing AWS Supply Chain events using Amazon EventBridge Using EventBridge, you can automate other services to respond to the execution status changes of a Step Functions Standard Workﬂow. Amazon EventBridge is a serverless service that uses events to connect application components together, making it easier for you to build scalable event-driven applications. Event-driven architecture is a style of building loosely-coupled software systems that work together by emitting and responding to events. Events represent a change in a resource or environment. Here's how it works: As with many AWS services, AWS Supply Chain generates and sends events to the EventBridge default event bus. (The default event bus is automatically provisioned in every AWS account.) An event bus is a router that receives events and delivers them to zero or more destinations, or targets. Rules you specify for the event bus evaluate events as they arrive. Each rule checks whether an event matches the rule's event pattern. If the event does match, the event bus sends the event to the speciﬁed target(s). Topics • AWS Supply Chain events • Delivering AWS Supply Chain events using EventBridge rules Managing events using EventBridge 67 AWS Supply Chain Administrator Guide • AWS Supply Chain events detail reference AWS Supply Chain events AWS Supply Chain sends the following events to the default EventBridge event bus automatically. Events that match a rule's event pattern are delivered to the speciﬁed targets on a basis. Events might be delivered out of order. For more information, see EventBridge events in the Amazon EventBridge User Guide. Event detail type Description AWS Supply Chain Data Integration Status Change Displays the status for each ingested ﬁle into AWS Supply Chain. Delivering AWS Supply Chain events using EventBridge rules To have the EventBridge default event bus send AWS Supply Chain events to a target, you must create a rule. Each rule contains an event pattern, which EventBridge matches against each event received on the event bus. If the event data matches the speciﬁed event pattern, EventBridge delivers that event to the rule's target(s). For comprehensive instructions on creating event bus rules, see Creating rules that react to events in the EventBridge User Guide. Creating event pattern that match AWS Supply Chain events Each event pattern is a JSON object that contains: • A source attribute that identiﬁes the service sending the event. For AWS Supply Chain events, the source is aws.supplychain. • (Optional): A detail-type attribute that contains an array of the event types to match. • (Optional): A detail attribute containing any other event data on which to match. For example, the following event pattern matches against all AWS Supply Chain Data Integration Status Change events from AWS Supply Chain: AWS Supply Chain events 68 AWS Supply Chain Administrator Guide { "source": ["aws.supplychain"], "detail-type": ["AWS Supply Chain Data Integration Status Change"] } For more information on writing event patterns, see Event patterns in the EventBridge User Guide. AWS Supply Chain events detail reference All events from AWS services have a common set of ﬁelds containing metadata about the event, such as the AWS service that is the source of the event, the time the event was generated, the account and region in which the event took place, and others. For deﬁnitions of these general ﬁelds, see Event structure reference in the Amazon EventBridge User Guide. In addition, each event has a detail ﬁeld that contains data speciﬁc to that particular event. The reference below deﬁnes the detail ﬁelds for the various AWS Supply Chain events. When using EventBridge to select and manage AWS Supply Chain events, it's useful to keep the following in mind: • The source ﬁeld for all events
supplychain-ag-023	supplychain-ag.pdf	23	the AWS service that is the source of the event, the time the event was generated, the account and region in which the event took place, and others. For deﬁnitions of these general ﬁelds, see Event structure reference in the Amazon EventBridge User Guide. In addition, each event has a detail ﬁeld that contains data speciﬁc to that particular event. The reference below deﬁnes the detail ﬁelds for the various AWS Supply Chain events. When using EventBridge to select and manage AWS Supply Chain events, it's useful to keep the following in mind: • The source ﬁeld for all events from AWS Supply Chain is set to aws.supplychain. • The detail-type ﬁeld speciﬁes the event type. For example, AWS Supply Chain Data Integration Status Change. • The detail ﬁeld contains the data that is speciﬁc to that particular event. For information on constructing event patterns that enable rules to match AWS Supply Chain events, see Event patterns in the Amazon EventBridge User Guide. For more information on events and how EventBridge processes them, see Amazon EventBridge events in the Amazon EventBridge User Guide. AWS Supply Chain Data Integration Status Change Below is an example for the AWS Supply Chain Data Integration Status Change event event. { Events detail reference 69 AWS Supply Chain "version": "0", "id": "instanceID", "detail-type": "AWS Supply Chain Data Integration Status Change", Administrator Guide "source": "aws.supplychain", "account": "acccountID", "time": "2024-03-30T12:26:13Z", "region": "us-east-1", "resources": [], "detail": { "version": "1.0", "instanceId": "instanceID", "flowArn": "arn:aws:scn:region:acccountID:instance/instanceID/data-integration- flows/flowname", "flowExecutionId": "flowExecutionId", "status": "IN_PROGRESS", "startTime": "2024-03-30T12:26:13Z", "endTime": "", "message": "", "sourceType": "S3", "sourceInfo": { "s3Source": { "bucketName": "aws-supply-chain-data-instanceID", "key": "flowname" } } } } endTime is only available when the status is failure or success. Events detail reference 70 AWS Supply Chain Administrator Guide Quotas for AWS Supply Chain Your AWS account has default quotas, formerly referred to as limits, for each AWS service. Unless otherwise noted, each quota is Region-speciﬁc. You can request to increase quotas for resources that are set to your account level. For more information on account level quotas, see the table below. To view the quotas for AWS Supply Chain, open the Service Quotas console. In the navigation pane, choose AWS services and select AWS Supply Chain. To request a quota increase, see Requesting a Quota Increase in the Service Quotas User Guide. If the quota isn't yet available in Service Quotas, use the limit increase form. Your AWS account has the following quotas related to AWS Supply Chain. Resource Default Number of instances 10 Adjustable No Note You can create upto 10 instances within an AWS account. Number of Amazon S3 buckets Active and pending invitatio ns within an AWS account Data requests within an AWS account Insights line items per watchlist 100 30 4,000 1,000 No Yes Yes No 71 AWS Supply Chain Resource Insights watchlists per instance within an AWS account Insights watchlists per user within an AWS account Data integration ﬂows per instance within an AWS account Default 1,000 100 100 Custom dataset namespace s per instance within an AWS 20 account Datasets per custom dataset namespace per instance 250 within an AWS account Datasets in default dataset namespace per instance within an AWS account 1,000 Administrator Guide Adjustable Yes Yes No Yes Yes No 72 AWS Supply Chain Administrator Guide Frequently asked questions (FAQs) The following information can help you troubleshoot common issues in enabling IAM Identity Center. Question Why is IAM Identity Center integration required? Answer IAM Identity Center is the feature within IAM that manages the synchronization of identity sources. IAM Identity Center is the identity source for the AWS Supply Chain instance. You need to conﬁgure IAM Identity Center to setup the AWS Console and the AWS Supply Chain web application. For more information on IAM Identity Center, see Enabling AWS IAM Identity Center in the AWS IAM Identity Center User Guide. Why use an IAM Identity Center organization instance for AWS Supply Chain? By creating an organization instance, you can enable IAM Identity Center access across AWS Why are delegated administrator privileges required for AWS Supply Chain? accounts. For example, if your IAM Identity Center is not enabled in the same AWS account as the AWS Supply Chain instance account. For more information on beneﬁts on creating an organization IAM Identity Center instance, see Organization instances of IAM Identity Center in the AWS IAM Identity Center User Guide. It is not required to have an delegated administrator to use AWS Supply Chain but it's a best practice for an AWS Organization setup to restrict access to the management account for the organization and manage IAM Identity Center. For more information, see Delegated adminsitrotor for AWS Organizations.. 73 AWS Supply Chain Question Administrator Guide Answer While creating an organization instance, make sure the account that will be used to create an
supplychain-ag-024	supplychain-ag.pdf	24	For more information on beneﬁts on creating an organization IAM Identity Center instance, see Organization instances of IAM Identity Center in the AWS IAM Identity Center User Guide. It is not required to have an delegated administrator to use AWS Supply Chain but it's a best practice for an AWS Organization setup to restrict access to the management account for the organization and manage IAM Identity Center. For more information, see Delegated adminsitrotor for AWS Organizations.. 73 AWS Supply Chain Question Administrator Guide Answer While creating an organization instance, make sure the account that will be used to create an AWS Supply Chain instance is part of the same organization as the IAM Identity Center account. Make sure the required permissio ns are enabled to create an instance and you can create an AWS Supply Chain instance in the same region as the IAM Identity Center account. For information on required permissions to create a AWS Supply Chain instance, see Getting started with AWS Supply Chain. 74 AWS Supply Chain Administrator Guide AWS support If you are an administrator and need to contact support for AWS Supply Chain, choose one of the following options: • If you have an Support account, go to Support Center and submit a ticket. • Open the AWS Management Console and choose AWS Supply Chain, Support, Create case. It's helpful to provide the following information: • Your AWS Supply Chain instance ID/ARN. • Your AWS Region. • A detailed description of your issue. 75 AWS Supply Chain Administrator Guide Document history for the AWS Supply Chain Administrator Guide The following table describes the documentation releases for AWS Supply Chain. Change Description Date Updated AWS Supply Chain quotas Updated the quotas for your AWS account related to AWS May 12, 2025 Supply Chain. Updated AWS managed policy AWS Supply Chain updated December 10, 2024 the managed policy to allow federated users access to ListApplicationAssignments, DescribeApplication, DescribeI nstance, and GetApplic ationAssignmentConﬁguratio n operations in IAM Identity Center. Updated the KMS policy to allow AWS Supply Chain to access your AWS KMS key. You can access AWS Supply Chain using an interface endpoint (AWS PrivateLink). Users must be part of an IAM Identity Center group to access AWS Supply Chain. March 18, 2024 February 26, 2024 November 14, 2023 KMS policy update PrivateLink support Adding Groups Updated AWS managed policy AWS Supply Chain updated November 1, 2023 the managed policy to allow federated users access to ListProﬁleAssociations 76 AWS Supply Chain Administrator Guide operations in IAM Identity Center. Updated AWS managed policy AWS Supply Chain updated September 21, 2023 the managed policy to allow federated users access to the PutObject and GetObject operations on the dedicated Amazon S3 bucket with resource arn arn:aws:s3:::aws- supply- chain-data-*. AWS Supply Chain Demand Planning is now also supported in Asia Paciﬁc (Sydney) Region. September 12, 2023 Updated information on regions support Use AWS Console to opt- in and opt-out AWS Supply AWS Supply Chain users can now use the AWS Console September 7, 2023 Chain Updated information on regions support Updated information on how to contact AWS Support and create an instance to opt-in and opt-out AWS Supply Chain to use or store Your Content on AWS Organizations. AWS Supply Chain is now also supported in Asia Paciﬁc (Sydney) Region, and Europe (Ireland) Region. AWS Supply Chain users can now contact AWS Support for help and updated the content on how to create an instance. July 19, 2023 April 3, 2023 77 AWS Supply Chain Administrator Guide Added AWS managed policy AWS Supply Chain added a new policy to allow federated March 1, 2023 users access to the AWS Supply Chain application, including the permissions necessary to perform actions within the AWS Supply Chain application. Initial release of the AWS Supply Chain Administrator Guide. November 29, 2022 Initial release 78
supplychain-ug-001	supplychain-ug.pdf	1	User Guide AWS Supply Chain Copyright © 2025 Amazon Web Services, Inc. and/or its aﬃliates. All rights reserved. AWS Supply Chain User Guide AWS Supply Chain: User Guide Copyright © 2025 Amazon Web Services, Inc. and/or its aﬃliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be aﬃliated with, connected to, or sponsored by Amazon. AWS Supply Chain Table of Contents User Guide What is AWS Supply Chain? ............................................................................................................ 1 Features of AWS Supply Chain .................................................................................................................. 1 Signing into AWS Supply Chain ................................................................................................................ 2 User permissions ........................................................................................................................................... 3 Conﬁguring the AWS Supply Chain dashboard ............................................................................. 5 Key Performance Indicators ....................................................................................................................... 5 On-Time in-full ........................................................................................................................................ 6 Customer order cycle time .................................................................................................................... 6 Supplier ﬁll rate ...................................................................................................................................... 7 Sell-through rate ..................................................................................................................................... 7 Enabling KPIs ........................................................................................................................................... 8 Managing KPIs ......................................................................................................................................... 8 Collaboration ................................................................................................................................................. 9 Notiﬁcations ................................................................................................................................................... 9 AWS Supply Chain Analytics ......................................................................................................... 11 Setting AWS Supply Chain Analytics ..................................................................................................... 11 Conﬁguring AWS Supply Chain Analytics as an administrator ......................................................... 13 Creating new analysis ............................................................................................................................... 13 Prebuilt dashboards ................................................................................................................................... 15 Application datasets used in AWS Supply Chain Analytics ............................................................... 17 Data lake ........................................................................................................................................ 19 Terminology used in data lake ................................................................................................................ 20 Data lake dashboard .................................................................................................................................. 20 Data Ingestion ....................................................................................................................................... 21 Datasets ................................................................................................................................................... 23 Data quality ............................................................................................................................................ 24 Adding a new data source ....................................................................................................................... 27 Prerequisites to ingest data ................................................................................................................ 28 Uploading ﬁles for the ﬁrst time ...................................................................................................... 29 Connecting to an EDI ........................................................................................................................... 33 Connecting to S/4 HANA .................................................................................................................... 35 Connecting to SAP ECC 6.0 ................................................................................................................ 48 Adding a new outbound source for Supply Planning ................................................................... 54 Ingesting data for existing connections ................................................................................................ 54 iii AWS Supply Chain User Guide Uploading data to an Amazon S3 bucket ....................................................................................... 55 Insights ........................................................................................................................................... 57 Insight settings ........................................................................................................................................... 57 Viewing the network map ........................................................................................................................ 59 Viewing inventory visibility ...................................................................................................................... 61 Understanding inventory projections ............................................................................................... 62 Creating insight watchlist ......................................................................................................................... 64 Creating an inventory risk watchlist ................................................................................................. 65 Creating a lead time deviation watchlist ......................................................................................... 66 Viewing inventory insights ....................................................................................................................... 67 Resolving an inventory risk insight ........................................................................................................ 68 Lead time insights ...................................................................................................................................... 70 Lead time deviations and recommendations .................................................................................. 71 Order Planning and Tracking ....................................................................................................... 73 Conﬁguring Order Planning and Tracking for the ﬁrst time ............................................................. 73 Orders settings ........................................................................................................................................... 76 Organization Labels .............................................................................................................................. 79 Orders ........................................................................................................................................................... 81 Viewing order materials ...................................................................................................................... 85 Procurement ................................................................................................................................................ 95 Logistics ...................................................................................................................................................... 100 Troubleshooting ....................................................................................................................................... 106 Demand Planning ........................................................................................................................ 108 Terminology used in Demand Planning .............................................................................................. 108 Create your ﬁrst demand plan .............................................................................................................. 110 Data Validation and Demand Pattern Analysis ................................................................................. 117 Data Validation ................................................................................................................................... 117 Demand Pattern and Recommendation ........................................................................................ 130 Forecast Algorithms ................................................................................................................................ 133 Forecast based on demand drivers ...................................................................................................... 166 Prequisites to use demand drivers .................................................................................................. 166 Demand driver conﬁguration ........................................................................................................... 168 Demand driver recommendations ................................................................................................... 170 Product lineage ........................................................................................................................................ 171 Product lifecycle ....................................................................................................................................... 178 Manage demand plans ........................................................................................................................... 181 iv AWS Supply Chain User Guide Overview ............................................................................................................................................... 181 Demand plan ....................................................................................................................................... 186 Forecast lock ........................................................................................................................................ 193 Forecast model analyzer ........................................................................................................................ 195 Viewing the forecast model analyzer details ............................................................................... 197 Manage Demand Plan settings ............................................................................................................. 198 Role-based access control ...................................................................................................................... 199 Managing user access ........................................................................................................................ 199 Supply Planning .......................................................................................................................... 201 Auto Replenishment ................................................................................................................................ 201 Key inputs ............................................................................................................................................ 201 Planning process ................................................................................................................................. 203 Inventory policies ............................................................................................................................... 206 Conﬁguring Auto Replenishment .................................................................................................... 214 Business workﬂow .............................................................................................................................. 222 Manufacturing Plans ............................................................................................................................... 224 Key inputs ............................................................................................................................................ 224 Planning process ................................................................................................................................. 225 Conﬁguring Manufacturing Plans ................................................................................................... 226 Business workﬂow .............................................................................................................................. 235 Planning conﬁguration data .................................................................................................................. 237 Product .................................................................................................................................................. 238 Site ......................................................................................................................................................... 238 Trading partner ................................................................................................................................... 238 Vendor product ................................................................................................................................... 238 Vendor lead time ................................................................................................................................ 238 Sourcing rule ....................................................................................................................................... 239 Inventory policy .................................................................................................................................. 241 Sourcing schedule .............................................................................................................................. 242 Bill of Material (BOM) ........................................................................................................................ 245 Production process ............................................................................................................................. 245 Supply planning parameters ............................................................................................................ 245 Transactional data .............................................................................................................................. 245 N-Tier Visibility ............................................................................................................................ 249 Using N-Tier Visibility for the ﬁrst time ............................................................................................. 249 N-Tier Visibility dashboard .................................................................................................................... 251 v AWS Supply Chain User Guide Partner Network ................................................................................................................................. 252 Purchase Orders .................................................................................................................................. 254 Forecast Commits ............................................................................................................................... 255 Responding to requests as a Partner .................................................................................................. 257 Reviewing and accepting partner invites ...................................................................................... 257 Reviewing and accepting purchase orders .................................................................................... 258 Reviewing and accepting forecast commits .................................................................................. 259 N-Tier Visibility settings ......................................................................................................................... 260 Sustainability ............................................................................................................................... 261 Using Sustainability for the ﬁrst time ................................................................................................. 261 Sustainability dashboard ........................................................................................................................ 262 Partner Network ................................................................................................................................. 263 Data requests ...................................................................................................................................... 266 Responding to requests as a Partner .................................................................................................. 277 Reviewing or responding to data requests ................................................................................... 277 Reviewing and accepting partner invites ...................................................................................... 278 Reviewing or responding to emission data forms ....................................................................... 279 Reviewing or responding to transportation (GLEC) emission data forms
supplychain-ug-002	supplychain-ug.pdf	2	............................................................................................................................... 255 Responding to requests as a Partner .................................................................................................. 257 Reviewing and accepting partner invites ...................................................................................... 257 Reviewing and accepting purchase orders .................................................................................... 258 Reviewing and accepting forecast commits .................................................................................. 259 N-Tier Visibility settings ......................................................................................................................... 260 Sustainability ............................................................................................................................... 261 Using Sustainability for the ﬁrst time ................................................................................................. 261 Sustainability dashboard ........................................................................................................................ 262 Partner Network ................................................................................................................................. 263 Data requests ...................................................................................................................................... 266 Responding to requests as a Partner .................................................................................................. 277 Reviewing or responding to data requests ................................................................................... 277 Reviewing and accepting partner invites ...................................................................................... 278 Reviewing or responding to emission data forms ....................................................................... 279 Reviewing or responding to transportation (GLEC) emission data forms ............................... 280 Sustainability settings ............................................................................................................................. 281 Amazon Q in AWS Supply Chain ................................................................................................ 282 Enabling Amazon Q in AWS Supply Chain ......................................................................................... 282 Prerequisites for existing AWS Supply Chain users ..................................................................... 283 Creating and assigning custom user roles to access Amazon Q in AWS Supply Chain ............... 285 Updating existing custom user roles to access Amazon Q in AWS Supply Chain .................. 286 Using Amazon Q in AWS Supply Chain .............................................................................................. 286 Sample questions you can ask Amazon Q in AWS Supply Chain ................................................... 288 Cross-Region calls with Amazon Q in AWS Supply Chain ............................................................... 292 Data entities used in AWS Supply Chain ................................................................................... 293 Sustainability ............................................................................................................................................. 293 N-Tier Visibility ......................................................................................................................................... 295 Supply Planning ....................................................................................................................................... 298 Insights ....................................................................................................................................................... 324 Order Planning and Tracking ................................................................................................................ 427 Demand Planning .................................................................................................................................... 448 Prequisites before uploading your dataset ................................................................................... 449 Data mapping example for fulﬁllment .......................................................................................... 450 vi AWS Supply Chain User Guide Data entities supported in AWS Supply Chain .......................................................................... 472 Organization .............................................................................................................................................. 478 company ............................................................................................................................................... 478 geography ............................................................................................................................................ 480 trading_partner ................................................................................................................................... 483 trading_partner_poc ........................................................................................................................... 486 Product ....................................................................................................................................................... 238 product .................................................................................................................................................. 487 product_hierarchy ............................................................................................................................... 497 product_uom ....................................................................................................................................... 499 product_alternate ............................................................................................................................... 503 un_details ............................................................................................................................................. 507 Network ...................................................................................................................................................... 508 site ......................................................................................................................................................... 508 transportation_lane ............................................................................................................................ 511 Vendor management .............................................................................................................................. 517 vendor_product ................................................................................................................................... 517 vendor_lead_time ............................................................................................................................... 522 vendor_holiday .................................................................................................................................... 527 Planning ..................................................................................................................................................... 528 product_bom ....................................................................................................................................... 528 inv_policy .............................................................................................................................................. 532 segmentation ....................................................................................................................................... 540 sourcing_rules ...................................................................................................................................... 543 sourcing_schedule ............................................................................................................................... 548 sourcing_schedule_details ................................................................................................................. 550 reservation ........................................................................................................................................... 553 supply_planning_parameters ........................................................................................................... 557 Operation ................................................................................................................................................... 559 process_header .................................................................................................................................... 560 process_operation ............................................................................................................................... 564 process_product .................................................................................................................................. 566 production_process ............................................................................................................................ 570 work_order_plan ................................................................................................................................. 573 Inventory management .......................................................................................................................... 576 inv_level ................................................................................................................................................ 576 vii AWS Supply Chain User Guide Inbound ...................................................................................................................................................... 580 inbound_order ..................................................................................................................................... 580 inbound_order_line ............................................................................................................................ 585 inbound_order_line_schedule .......................................................................................................... 593 shipment ............................................................................................................................................... 598 shipment_stop ..................................................................................................................................... 608 shipment_stop_order ......................................................................................................................... 611 shipment_lot ........................................................................................................................................ 613 Outbound fulﬁllment .............................................................................................................................. 616 outbound_order_line .......................................................................................................................... 617 outbound_shipment ........................................................................................................................... 624 Cost management .................................................................................................................................... 628 customer_cost ...................................................................................................................................... 628 Plan ............................................................................................................................................................. 632 supply_plan .......................................................................................................................................... 633 Forecast ...................................................................................................................................................... 246 supplementary_time_series .............................................................................................................. 639 forecast ................................................................................................................................................. 644 Reference ................................................................................................................................................... 652 reference_ﬁeld ..................................................................................................................................... 652 calendar ................................................................................................................................................ 653 uom_conversion .................................................................................................................................. 655 AWS support ................................................................................................................................ 658 Document history ........................................................................................................................ 659 viii AWS Supply Chain User Guide What is AWS Supply Chain? AWS Supply Chain is a cloud-based supply chain management application that works with your existing enterprise resource planning (ERP) and supply chain management systems. Using AWS Supply Chain, you can connect and extract your inventory, supply, and demand related data from existing ERP or supply chain systems into one uniﬁed AWS Supply Chain data model. Topics • Features of AWS Supply Chain • Signing into AWS Supply Chain • User permissions Features of AWS Supply Chain AWS Supply Chain supports the following features: • Data Lake – The AWS Supply Chain data lake simpliﬁes the process of aggregating data from your supply chain systems in one place, using an extensible data model built for supply chain management. The data lake consumes data from any structured data source, including your existing ERP and supply chain management systems. To connect to any of the other Warehouse management systems, you can use the Amazon S3 connector. Once the data source is connected, you can review and conﬁrm the data mapping between your data source to AWS Supply Chain's Features of AWS Supply Chain 1 AWS Supply Chain User Guide data model. Once the data ﬁelds are mapped, you can start importing your data from your data source. For more information, see Data lake. • Insights – AWS Supply Chain insights uses the supply chain data in the data lake to automatically generate insights of potential supply chain risks (for example, stockouts, excess stocks, lead time deviations). After the data is imported, AWS Supply Chain automatically computes the projected inventory based on the inventory snapshots, open orders,in-transit shipments, and demand from outbound orders and forecast. AWS Supply Chain proactively alerts inventory managers of potential inventory risks that include both below and above the stock levels stored in inventory policy and provides rebalance recommendations to resolve stockouts. Inventory managers are also alerted when there are consistent lead time deviations by a vendor and recommends updating contractual lead times to avoid such deviations in the future. For more information, see Insights. • Order Planning and Tracking – You
supplychain-ug-003	supplychain-ug.pdf	3	deviations). After the data is imported, AWS Supply Chain automatically computes the projected inventory based on the inventory snapshots, open orders,in-transit shipments, and demand from outbound orders and forecast. AWS Supply Chain proactively alerts inventory managers of potential inventory risks that include both below and above the stock levels stored in inventory policy and provides rebalance recommendations to resolve stockouts. Inventory managers are also alerted when there are consistent lead time deviations by a vendor and recommends updating contractual lead times to avoid such deviations in the future. For more information, see Insights. • Order Planning and Tracking – You can use Order Planning and Tracking to view work order status, expected time of arrival (ETA) predictions, delivery risk and recommendations for each work order. For more information, see Order Planning and Tracking. • Demand planning – You can use AWS Supply Chain Demand Planning to create demand forecasts, adjust the forecasts according to market conditions, and allow demand planners to collaborate across teams. For more information, see Demand Planning. • Supply planning – You can use Supply planning to plan and forecast purchases of raw materials, components, and ﬁnished goods. Supply planning supports two types of supply plans, Auto replenishment and Manufacturing plans. For more information, see Supply Planning. • N-Tier Visibility – N-Tier Visibility extends visibility and insights beyond your organization to your external trading partners. For more information, see N-Tier Visibility. • Sustainability – You can invite partners by using the AWS Supply Chain data lake connectors and by mapping the partner information to Partners or Partner's point-of-contact from Amazon S3 or other ERP systems. For more information, see Sustainability. Signing into AWS Supply Chain AWS Supply Chain has a web-based client so you can access your AWS Supply Chain account from a web browser. To get started with the AWS Supply Chain, you need a broadband internet connection and one of the web browsers listed in the following table. Signing into AWS Supply Chain 2 AWS Supply Chain Browser Google Chrome User Guide Supported Versions Latest three versions. Mozilla Firefox Extended Support Release (ESR) All versions are supported until the version's end-of-life date. For more information, see the Firefox ESR release calendar. Mozilla Firefox Latest three versions. Microsoft Edge and Edge Chromium Version 84 and later. Safari Safari 10 or later on macOS. Your AWS Supply Chain system administrator provides you with a unique AWS Supply Chain web client URL. To recover a lost or forgotten password, contact your administrator. Note The AWS Supply Chain dashboard is customized according to your permission role. For more information, see User permissions. 1. 2. In your web browser, enter the web client URL provided by your AWS Supply Chain administrator. For example, https://alias.awsapps.com. For Username and Password, enter your AWS IAM Identity Center SSO credentials (formerly known as AWS SSO). 3. Choose Sign In. User permissions AWS Supply Chain supports the following default user permission roles. Additionally, you can create custom user permission roles that include multiple permission roles. You can also add speciﬁc locations and products. • Administrator – Access to create, view, and manage all data and user permissions. • Data Analyst – Access to create, view, and manage all data connections. User permissions 3 AWS Supply Chain User Guide • Inventory Manager – Access to create, view, and manage Insights. • Planner – Access to create, view, and manage forecasts and overrides, and also publish demand plans. • Partner Data Manager – Access to manage and view partners, manage and view data requests, and view sustainability data. • Supply Planner – Access to manage and view supply plans. User permissions 4 AWS Supply Chain User Guide AWS Supply Chain dashboard You can view your data connections and inventory visibility, add users or groups, and monitor your watchlists and key performance indicators (KPIs) directly from the dashboard. Your default dashboard view depends on the permission the AWS Supply Chain administrator assigns you. To customize your dashboard, complete the following procedure: 1. On the AWS Supply Chain dashboard, choose Manage dashboard. The Build your dashboard page appears. 2. Depending on your user permission role, you will see cards that you can use for customizing your dashboard. For each card that you want to add to your dashboard, select its check box. 3. Choose Save. Key Performance Indicators Key performance indicators (KPIs) are metrics that can help measure the performance of a supply chain. AWS Supply Chain administrator supports the following KPIs: Key Performance Indicators 5 AWS Supply Chain On-Time in-full User Guide On-time In-Full (OTIF) measures the eﬀectiveness of customer fulﬁllment operations, such as, picking, packing and shipping orders on-time and in full. This metric is measured by adding the total number of orders shipped in-full, on or before the expected ship date divided by the total number
supplychain-ug-004	supplychain-ug.pdf	4	card that you want to add to your dashboard, select its check box. 3. Choose Save. Key Performance Indicators Key performance indicators (KPIs) are metrics that can help measure the performance of a supply chain. AWS Supply Chain administrator supports the following KPIs: Key Performance Indicators 5 AWS Supply Chain On-Time in-full User Guide On-time In-Full (OTIF) measures the eﬀectiveness of customer fulﬁllment operations, such as, picking, packing and shipping orders on-time and in full. This metric is measured by adding the total number of orders shipped in-full, on or before the expected ship date divided by the total number of shipments with an expected ship date for the month. OTIF requires the following entities to be populated and mapped in AWS Supply Chain Data lake: Dataset Outbound_Shipment Entity Shipped_Qty Outbound_Order_Line Quantity_Promised Outbound_Shipment_Records Actual_Ship_Date Outbound_Shipment Expected_Ship_Date To calculate OTIF, AWS Supply Chain uses the following formula: SUM (outbound_shipment.shipped_qty = outbound_order_line.Quantity promised AND outbound_shipment_records.actual_ship_date ≤ outbound_shipment.expected_ship_date) ÷ by total number of orders with outbound_shipment.expected_ship_date for a given month. Customer order cycle time Customer order cycle time measures the eﬃciency of the supply chain fulﬁllment process. This metric is calculated by the average number of days between the order date and when the order is shipped. Customer order cycle time requires the following entities to be populated and mapped in AWS Supply Chain data lake. Dataset Outbound_Order_Line Entity Order_Date Outbound_Shipment_Records Actual_Ship_Date On-Time in-full 6 AWS Supply Chain User Guide AWS Supply Chain uses the following formula to calculate customer order cycle time: Average number of days between Outbound_order_Line.order_date and Outbound_Shipment.actual_ship_date for all outbound order lines during a given month. Supplier ﬁll rate The supplier ﬁll rate measures your supplier’s commitment to your organization. This metric is calculated by adding all the inbound orders where the quantity received matches the quantity requested by the expected delivery date. The supplier ﬁll rate requires the following entities to be populated and mapped in AWS Supply Chain data lake. Dataset Entity Inbound_Order_Line Quantity_Submitted Inbound_Order_Line Quantity_Received Inbound_Order_Line Received_Date Inbound_Order_Line Expected_Delivery_Date To calculate supplier ﬁll rate, AWS Supply Chain uses the following formula : Sum (inbound_order_line.Quantity Submitted = inbound_order_line.quantity_recieved and inbound_order_line.order.recieve.date ≤ inbound_order_line.expected_delivery_date) ÷ by the total number of lines with inbound_order_line.expected_delivery_date within a given month. Sell-through rate A sell-through rate measures the percentage of available inventory sold in a given month. This metric is calculated by adding all outbound shipment quantities for a given month divided by the sum of current inventory at the beginning of the month and the inventory received during the month. The sell-through rate requires the following entities to be populated and mapped in AWS Supply Chain data lake. Supplier ﬁll rate 7 User Guide AWS Supply Chain Dataset Outbound_Shipment Entity Shipped_Qty Outbound_Shipment_Records Actual_Ship_Date Inventory_Level_Records On_Hand_Inventory Inbound_Order_Line Expected_Delivery_Date Inbound_Order_Line Quantity_Received Inbound_Order_Line Received_Date To calculate sell-through rate, AWS Supply Chain uses the following formula: SUM outbound_shipment_records.quantity_shipped for a given month ÷ by SUM( InventoryLevel_records.on_hand_inventory at start of month+ inbound_order_line.quantity_recieved during the month). Enabling KPIs To enable KPIs in AWS Supply Chain, complete the following procedure: 1. On the AWS Supply Chain dashboard, under Monitor KPIs, choose Enable. The AWS Supply Chain dashboard updates to display the KPIs for the current dataset. 2. To view the actual value or percentage, hover over the KPI. Managing KPIs To view or remove KPIs from the AWS Supply Chain dashboard, complete the following procedure: 1. On the AWS Supply Chain dashboard, choose Manage dashboard. 2. Choose the KPIs that you want to see or remove from the AWS Supply Chain dashboard. 3. Choose Save. Enabling KPIs 8 AWS Supply Chain User Guide Collaborating with other AWS Supply Chain users You can collaborate with other AWS Supply Chain users to discuss supply chain related issues. On the AWS Supply Chain dashboard, choose Go to collaboration. You can do the following: • Under Team Conversations, you can see all the individual users with whom you have had conversations. • Under Insight Conversations, all the conversations within the team for an Insight are listed. • Once you select a particular Insight conversation, you can view the Insight risk on the right with recommendations to resolve the risk. You can also choose View Insight Details to view the Insight risk page. • Choose Start Conversation. The New Conversation dialog box appears. From the Add User(s) drop-down, select the user to start the conversation and choose Start Conversation. • Slide the Get notiﬁcations for this thread button to activate the web application notiﬁcations for the conversation. Notiﬁcations You can receive a notiﬁcation in the AWS Supply Chain web application or through email. To enable notiﬁcations, perform the following procedure: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. The Settings page appears. 2. Choose Notiﬁcations. The Notiﬁcation Preferences page appears. 3. Under Insights, slide the In-app
supplychain-ug-005	supplychain-ug.pdf	5	Choose Start Conversation. The New Conversation dialog box appears. From the Add User(s) drop-down, select the user to start the conversation and choose Start Conversation. • Slide the Get notiﬁcations for this thread button to activate the web application notiﬁcations for the conversation. Notiﬁcations You can receive a notiﬁcation in the AWS Supply Chain web application or through email. To enable notiﬁcations, perform the following procedure: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. The Settings page appears. 2. Choose Notiﬁcations. The Notiﬁcation Preferences page appears. 3. Under Insights, slide the In-app and Email button to receive notiﬁcations when a lead time deviation is identiﬁed, inventory risks are identiﬁed, lead time export fails, or when lead time export succeeds. Collaboration 9 AWS Supply Chain Note User Guide You can choose to receive an email, in-app notiﬁcation, or both. 4. Under Forecast Collaboration, slide the In-app button to receive a notiﬁcation in AWS Supply Chain when there is an update to the forecast or if the forecast request is decline by the Partner. You can also use the Email button to receive a summarized email once a day on all the forecast updates. 5. Under Purchase Orders, slide the In-app button to receive a notiﬁcation in AWS Supply Chain when there is a purchase order update by the Partner. You can also use the Email button to receive a summarized email once a day on all the purchase order updates. 6. Under Disclosure Data Requests, slide the In-app button to receive a notiﬁcation in AWS Supply Chain when a data request is submitted or declined or to track the status of the data request. For example, in progress, rework requested, canceled, and so on. 7. Choose Save. 8. On the AWS Supply Chain dashboard, choose the Bell icon on the top-right to view the in-app notiﬁcations. Notiﬁcations 10 AWS Supply Chain User Guide AWS Supply Chain Analytics AWS Supply Chain uses QuickSight's authoring capability that enables you to build custom dashboards using the data you ingested into AWS Supply Chain data lake and data generated by AWS Supply Chain. For example, demand forecast, project inventory, supply plans, and so on. Using a single dashboard, a supply chain manager can visualize supply chain data, perform custom analysis, derive metrics, and gain insights from multiple sources. For information on QuickSight, see Amazon QuickSight. AWS Supply Chain Analytics supports Administrator, Author, and Reader permission roles. The default role is an AWS Supply Chain Analytics Author. Note When you are enabling AWS Supply Chain Analytics for the ﬁrst time, you can either setup under Settings or choose Analytics in the left navigation pane on the AWS Supply Chain dashboard. Topics • Setting AWS Supply Chain Analytics • Conﬁguring AWS Supply Chain Analytics as an administrator • Creating new analysis • Prebuilt dashboards • Application datasets used in AWS Supply Chain Analytics Setting AWS Supply Chain Analytics You must enable AWS Supply Chain Analytics before you can start using QuickSight dashboards. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Organization, choose Analytics. The Analytics setting page appears. Setting AWS Supply Chain Analytics 11 AWS Supply Chain User Guide 3. Slide the Enable data access for Analytics button to enable AWS Supply Chain Analytics. 4. Under User and Permissions, choose Permission Roles. You can edit the permission roles for a current user or add a new permission role to enable Analytics access. 5. On the Manage Permission Role page, under Analytics, slide the Manage or View button to grant read or write access. Setting AWS Supply Chain Analytics 12 AWS Supply Chain User Guide • Manage – Select this permission role if you want the Analytics user to create and view dashboards. • View – Select this permission role if you want the Analytics user to only view the dashboards. Conﬁguring AWS Supply Chain Analytics as an administrator You must conﬁgure AWS Supply Chain Analytics to use Analytics dashboard. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Analytics or choose Go to Analytics from the AWS Supply Chain dashboard. The Set up AWS Supply Chain Analytics page appears. Note If you have not ingested data into Data Lake, you need to ingest data before using AWS Supply Chain Analytics. To ingest data, see Data lake. 2. Choose Set up Analytics. The QuickSight dashboard page appears. 3. Choose Analyses. You can view all the existing analysis. Creating new analysis To create a new analysis, follow the below procedure. Note Granular access based on Location and Product is not supported in AWS Supply Chain Analytics. 1. On the QuickSight dashboard page, choose New analysis. 2. Choose New dataset Conﬁguring AWS Supply Chain Analytics as an administrator
supplychain-ug-006	supplychain-ug.pdf	6	Chain Analytics page appears. Note If you have not ingested data into Data Lake, you need to ingest data before using AWS Supply Chain Analytics. To ingest data, see Data lake. 2. Choose Set up Analytics. The QuickSight dashboard page appears. 3. Choose Analyses. You can view all the existing analysis. Creating new analysis To create a new analysis, follow the below procedure. Note Granular access based on Location and Product is not supported in AWS Supply Chain Analytics. 1. On the QuickSight dashboard page, choose New analysis. 2. Choose New dataset Conﬁguring AWS Supply Chain Analytics as an administrator 13 AWS Supply Chain User Guide The Create a Dataset page appears. You will see the AWS Supply Chain data lake as an existing dataset for you to pick. For example, ask-datalake-your instance id. 3. Choose the data source. Note Select the blue QuickSight logo to navigate to the QuickSight menu to view the datasets or analyses. 4. Choose Create dataset. 5. Under Schema:contain set of tables drop-down, select one of the following data source names: • asc_data_<your instance id>: Contains datasets processed and transformed by AWS Supply Chain for use within the application. These can be used for creating dashboards and custom analyses. Examples include asc_insights_order_insights and asc_adp_forecast. For more information on available datasets and their uses, see Application datasets used in AWS Supply Chain Analytics. Creating new analysis 14 AWS Supply Chain User Guide • asc_custom_data_<your instance id>: Contains original, non-transformed data as provided. You can query these datasets to access and analyze your raw data directly and build dashboards out of them. 6. Under Tables: contain the data you can visualize, choose the dataset from the list of AWS Supply Chain datasets. 7. Choose Select. 8. Under Finish dataset creation, choose Visualize. 9. Under Data, choose the ﬁelds you want to visualize and choose Publish. The Publish a dashboard page appears. 10. Under Publish new dashboard as, enter a name for your dashboard. 11. Choose Publish dashboard. You will see the new dashboard created under Dashboards and a new analysis created under Analyses. For more information on using Dashboards or Analyses, see Amazon QuickSight. Prebuilt dashboards AWS Supply Chain Analytics supports the following prebuilt dashboards. • Plan-over-plan variance analysis – Use this dashboard to compare two demand plans and view the diﬀerence in both units and values across key dimensions such as product, site, and time periods. Prebuilt dashboards 15 AWS Supply Chain User Guide • Seasonality analysis – Displays the year-over-year view of demand, displaying the trends in average demand quantities, and highlighting seasonality patterns through peaks at both monthly and weekly intervals. You can identify the demand patterns and assign the appropriate forecasting levels. To add a prebuilt dashboard to your dashboard page, follow the below procedure. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Analytics. The AWS Supply Chain Analytics page appears. 2. Choose the Prebuilt Dashboards tab. 3. Under Add Dashboards, select the dashboard you want to add and choose Add. 4. Choose the QuickSight tab. 5. Choose Dashboards. You should see the prebuilt dashboard you added from Prebuilt Dashboards. 6. Choose the dashboard you want to view. Prebuilt dashboards 16 AWS Supply Chain User Guide 7. Choose the share icon to share the dashboard with other AWS Supply Chain Analytics users. For more information on permission roles, see Setting AWS Supply Chain Analytics. Application datasets used in AWS Supply Chain Analytics The following are the list of application datasets displayed in AWS Supply Chain Analytics. AWS Supply Chain module name Data entity Dataset name Description Demand Planning Forecast asc_adp_forecast PlanningCycleAccur acy asc_adp_planning_c ycle_accuracy Forecast generated by AWS Supply Chain's Demand Planning application. Forecast accuracy data generated by Demand Planning. Supply Planning SupplyPlan asc_supply_plannin g_supply_plan Replenishment plan generated by AWS Application datasets used in AWS Supply Chain Analytics 17 AWS Supply Chain AWS Supply Chain module name Data entity Dataset name Description User Guide Supply Chain's Supply Planning application. InboundOrderLine asc_supply_plannin g_inbound_order_line Data generated by AWS Supply Chain's Insights ProjectedInventory asc_insights_proje cted_inventory Order Planning and Tracking OrderLineInsights asc_insights_order _line_insights Supply Planning application for Inbound_order_line. Projected inventory data generated by AWS Supply Chain's Insights application. Order line data generated by AWS Supply Chain's Order Planning and Tracking application. OrderInsights asc_insights_order _insights Order data generated by AWS Supply Chain's Order Planning and Tracking application. Application datasets used in AWS Supply Chain Analytics 18 AWS Supply Chain Data lake User Guide You can use AWS Supply Chain to ingest your data stored in the following data sources and extract your supply chain information. AWS Supply Chain can store the extracted information in your Amazon S3 buckets and use the data for Demand planning, Insights, Supply Planning, N-Tier Visibility, Work Order Insights, and Sustainability. • Amazon S3 source data – You can
supplychain-ug-007	supplychain-ug.pdf	7	by AWS Supply Chain's Order Planning and Tracking application. OrderInsights asc_insights_order _insights Order data generated by AWS Supply Chain's Order Planning and Tracking application. Application datasets used in AWS Supply Chain Analytics 18 AWS Supply Chain Data lake User Guide You can use AWS Supply Chain to ingest your data stored in the following data sources and extract your supply chain information. AWS Supply Chain can store the extracted information in your Amazon S3 buckets and use the data for Demand planning, Insights, Supply Planning, N-Tier Visibility, Work Order Insights, and Sustainability. • Amazon S3 source data – You can use the Amazon S3 data source ﬂow option if you don't have an ERP system, or if you use another extraction tool. You can extract raw data from your data source, map the data ﬁelds with AWS Supply Chain data model, and upload them to Amazon S3 with an integration tool of your choice. You can only upload CSV ﬁles to Amazon S3 when you're using Auto-association. • Electronic data interchange (EDI) – AWS Supply Chain supports X12 ANSI version 4010 for EDI messages 850, 860, and 856. Supported data formats are .edi or .txt. You can add your raw EDI messages to Amazon S3 using an integration tool of your choice. AWS Supply Chain can extract and associate your raw EDI messages using default templates by Natural Language Processing (NLP) for EDI 856. NLP templates are not supported for EDI 850 and 860 and come with pre- deﬁned, but customizable recipes in AWS Supply Chain. • SAP S/4HANA – To extract your supply chain data from an SAP S/4HANA data source, AWS Supply Chain can use the Amazon AppFlow connector to connect to this source. AWS Supply Chain can associate your supply chain data stored in SAP S/4HANA system to the AWS Supply Chain data model using AWS Glue DataBrew. • SAP ECC 6.0 – You can use an integration tool (for example, ETL or iPaaS) to extract your supply chain data stored in the SAP ECC 6.0 system and put it into the Amazon S3 bucket using an API. AWS Supply Chain can associate your supply chain data stored in the SAP ECC 6.0 system to the AWS Supply Chain data model using DataBrew. Topics • Terminology used in data lake • Data lake dashboard • Adding a new data source • Ingesting data for existing connections 19 AWS Supply Chain User Guide Terminology used in data lake The following terms are used in data lake: • Entity – Information about a data object for each category. For example, company, geography, and trading_partner are entities for an organization. For more information, see Data entities and columns used in AWS Supply Chain. • Dataset – Information related to the entity. You can have only one dataset per entity. • Connector – A way to import data into AWS Supply Chain. • Recipe – A set of steps that describes how to map source data into one dataset. • Source Flows1 – Displays the datasets and ﬁelds that you uploaded. • Destination Flows1 – Associates the data from your dataset to the AWS Supply Chain data entities in data lake. • Source system1 – Your existing enterprise resource planning (ERP) system, Warehouse Management System (WMS), or any supply chain data management system. 1 – These terms are only displayed when you ingest data through Amazon S3 (or the Upload any CSV option in the web application). Data lake dashboard You can use AWS Supply Chain data lake to ingest your data from various data sources. For information about supported data sources, see Data lake. Terminology used in data lake 20 AWS Supply Chain User Guide Data Ingestion You can view the current connections, source, and destination ﬂows. To view the status of the ingested data, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake and then choose the Data Ingestion tab. The Data Ingestion page appears. Data Ingestion 21 AWS Supply Chain User Guide 2. Choose the Source Flows tab. • Source Flows – Displays the ﬁle or folder structure of the dataset that was uploaded. • S3 Preﬁx – Displays the Amazon S3 path where the source ﬁles are uploaded. • Status – Displays the source ﬁles' upload status. • Last Sync – Displays when the ﬁles were last synced or updated. • Actions – You can view the following: • Manage Flow – You can update the data mapping. • Upload Files – You can add additional source ﬁles to your existing source ﬂows. • Delete Flow – You can delete the source ﬂow completely. 3. Choose the Destination Flows tab. 4. Under Actions, choose Manage Flow to view and update the data mappings. The Manage Destination Flows
supplychain-ug-008	supplychain-ug.pdf	8	Displays the Amazon S3 path where the source ﬁles are uploaded. • Status – Displays the source ﬁles' upload status. • Last Sync – Displays when the ﬁles were last synced or updated. • Actions – You can view the following: • Manage Flow – You can update the data mapping. • Upload Files – You can add additional source ﬁles to your existing source ﬂows. • Delete Flow – You can delete the source ﬂow completely. 3. Choose the Destination Flows tab. 4. Under Actions, choose Manage Flow to view and update the data mappings. The Manage Destination Flows page appears. Data Ingestion 22 AWS Supply Chain User Guide 5. Move any unassociated source columns under Source Columns to Destination Columns. 6. Choose Exit and Review Destination Flows to go back to the Destination Flows page to review the destination ﬂows. 7. Choose the Connections tab. You can view all the existing connections. Datasets You can view the status of the datasets ingested. To view all the datasets uploaded to existing connections, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake and then choose the Datasets tab. Datasets 23 AWS Supply Chain User Guide The Datasets page appears. 2. To view a dataset, choose View. 3. Under the Dataset Fields tab, you can view all the existing dataset ﬁelds in the dataset. 4. Under the Source Connections tab, you can view the connections that are feeding that dataset. Data quality Any identiﬁed data quality errors are displayed on the web application under Module errors. You can view the dataset that has errors and the impacted AWS Supply Chain module. Additionally, you can download the data quality report from your Amazon S3 bucket. The report provides detailed information on the dataset errors in the ingested data. Viewing data quality reports To view the AWS Supply Chain module errors, complete the following steps: Note For information on required and optional data entities for each AWS Supply Chain module, see the Demand Planning, Insights, and Work Order Insights sections under Data entities and columns used in AWS Supply Chain. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake and then choose the Data Quality tab. 2. Choose the Module Errors tab. You can view the data ingestion errors for the AWS Supply Chain modules. Note You can also view the dataset errors and the aﬀected modules after the ﬁrst ingestion is complete and the destination ﬂows are successful. If the destination ﬂows are unsuccessful, you can view the data quality errors under the Detail column of the Destination Flows tab. Data quality 24 AWS Supply Chain User Guide You can ﬁlter the errors using the following ﬁlters in the Module dropdown box: • All • Multiple Applications • Demand Planning • Insights • Order Insights 3. View the data quality errors under the Impacted Module and Status Message columns. The Impacted Module column displays the AWS Supply Chain application and the related feature that was impacted. The Status Message column displays the product entity and the number of errors under each product entity. For example, the "The ﬁeld "channel_id" has null or empty value..." error means that the "channel_id" column in the ingested outbound_order_line ﬁle is missing data. Data quality 25 AWS Supply Chain User Guide Downloading data quality reports To download the data quality report, complete the following steps: 1. Open the Amazon S3 console at https://console.aws.amazon.com/s3/ and sign in. 2. Navigate to the aws-supply-chain-data instance ID folder, then data-quality-report. 3. Select the folder for the data entity you want to view. Individual folders for each data ingestion will appear. Data quality 26 AWS Supply Chain User Guide 4. Select the folder for the data ingestion you want to view. The data quality report will appear. 5. Select the ﬁle and choose Download to download the data quality report in json format. Adding a new data source You can use AWS Supply Chain to ingest your data stored in your data source and extract your supply chain information. AWS Supply Chain can store the extracted information in your Amazon S3 buckets and use the data for Demand planning, Insights, Supply Planning, N-Tier Visibility, Work Order Insights, and Sustainability. Topics • Prerequisites to ingest data Adding a new data source 27 AWS Supply Chain • Uploading ﬁles for the ﬁrst time • Connecting to an EDI • Connecting to S/4 HANA • Connecting to SAP ECC 6.0 • Adding a new outbound source for Supply Planning User Guide Prerequisites to ingest data Note the following before uploading your datasets for ingestion: • The ﬁle that you upload should be less than 5 GB. • The content in the dataset should follow the UTF-8 encoding format. •
supplychain-ug-009	supplychain-ug.pdf	9	for Demand planning, Insights, Supply Planning, N-Tier Visibility, Work Order Insights, and Sustainability. Topics • Prerequisites to ingest data Adding a new data source 27 AWS Supply Chain • Uploading ﬁles for the ﬁrst time • Connecting to an EDI • Connecting to S/4 HANA • Connecting to SAP ECC 6.0 • Adding a new outbound source for Supply Planning User Guide Prerequisites to ingest data Note the following before uploading your datasets for ingestion: • The ﬁle that you upload should be less than 5 GB. • The content in the dataset should follow the UTF-8 encoding format. • The ﬁle type must be supported by the connector. The connectors for SAP systems supports CSV, EDI connector supports .txt and .edi formats, and Amazon S3 supports CSV. • Data rows must contain non-null values for the required ﬁelds. • The date and time format should follow the ISO8601 standards. For example, 2020-07-10 15:00:00.000, represents the 10th of July 2020 at 3 pm. • The column names in the dataset shouldn't contain spaces or special characters. Column names should be separated by an underscore (_) between two words. • When using the Amazon S3 source path, AWS Supply Chain will create a parent folder named after the source system that you selected. Sub-folders are named after the source table that you selected. Make sure that the ﬁle names are unique. The ﬁle structure that you build will be used to create the Amazon S3 path. • AWS Supply Chain follows a multi-step upload process with pre-assigned URLs. Due to browser security restrictions, to upload your dataset, your S3 bucket cross-origin resource sharing (CORS) permissions must allow PUT requests and return an ETag header. To update the CORS policy on your Amazon S3 bucket, under Connections, scroll-down to CORS and paste the following policy: [ { "AllowedHeaders": [ "*" ], "AllowedMethods": [ Prerequisites to ingest data 28 AWS Supply Chain "PUT" ], "AllowedOrigins": [ "https://instance-id.scn.global.on.aws" ], "ExposeHeaders": [ "Etag" ] } ] User Guide Uploading ﬁles for the ﬁrst time You can use the AWS Supply Chain Auto-association feature to upload your raw data and automatically associate your raw data with AWS Supply Chain data model. You can also view the required columns and tables for each AWS Supply Chain module within the AWS Supply Chain web application. Note You can only upload CSV ﬁles to Amazon S3 when you are using Auto-association. After the source columns from your dataset are associated with the destination columns, AWS Supply Chain will automatically generate the SQL recipe. Note AWS Supply Chain uses Amazon Bedrock for Auto-association, which it's not supported in all the &AWS Regions that AWS Supply Chain is available in. Hence, AWS Supply Chain will call Amazon Bedrock endpoint from the closest available region, Europe (Ireland) Region – Europe (Frankfurt) and Asia Paciﬁc (Sydney) Region – US West (Oregon). Uploading ﬁles for the ﬁrst time 29 AWS Supply Chain Note User Guide Auto-association using the Large Language Models (LLM) is only supported when data is ingested through Amazon S3. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake and then choose the Data Ingestion tab. The Data Ingestion page appears. 2. Choose Add New Source. The Select your data source page appears. 3. On the Select your data source page, choose Upload ﬁles. 4. Choose Continue. Uploading ﬁles for the ﬁrst time 30 AWS Supply Chain User Guide 5. On the Which capabilities do you want to run page, choose the AWS Supply Chain modules that you want to use. You can choose more than one module. 6. Under Upload your source ﬁles section, add a suﬃx to the Source system name. For example, oracle_test. 7. To upload your source dataset, choose ﬁles or drag and drop ﬁles. The source tables with the name and status are displayed. 8. Choose Upload to S3. The upload status will change to display the status. 9. Under Review data requirements, review all the required data entities and columns for the selected AWS Supply Chain feature. All of the required primary and foreign keys are displayed. 10. Choose Continue. 11. Under Manage your source tables, the following source tables and the columns listed will be auto associated and imported into data lake. Choose Delete table to delete any of the source tables before importing into data lake. 12. Choose Accept all and Continue. A message on auto-associating your tables to AWS Supply Chain data lake is displayed. Uploading ﬁles for the ﬁrst time 31 AWS Supply Chain User Guide 13. Under Manage Destination Flows, you can review each auto-associated table. By default, Auto-Association is enabled and the source columns are auto-associated with the destination columns. To update the auto-associated columns, you can update the SQL recipe to create your
supplychain-ug-010	supplychain-ug.pdf	10	and the columns listed will be auto associated and imported into data lake. Choose Delete table to delete any of the source tables before importing into data lake. 12. Choose Accept all and Continue. A message on auto-associating your tables to AWS Supply Chain data lake is displayed. Uploading ﬁles for the ﬁrst time 31 AWS Supply Chain User Guide 13. Under Manage Destination Flows, you can review each auto-associated table. By default, Auto-Association is enabled and the source columns are auto-associated with the destination columns. To update the auto-associated columns, you can update the SQL recipe to create your custom recipe. 14. Under Source Columns, all of the unassociated source columns are listed. Drag and drop the unassociated columns to the Destination Columns on the right. 15. Follow the preceding step for each auto-associated table. 16. Choose Submit. 17. Choose Exit and Review Destination Flows. Uploading subsequent ﬁles to an existing source There are two ways to upload subsequent datasets to an existing source. You can either upload the dataset on the Amazon S3 path displayed under the Source Flows tab, or choose Upload ﬁles under the Actions tab. If you're using an automated connector, executing scripts, or using a middle ware solution to ingest the dataset into AWS Supply Chain, you must update the Amazon S3 path with the Amazon S3 path displayed under the Source Flows tab. Uploading ﬁles for the ﬁrst time 32 AWS Supply Chain Note User Guide If an existing ﬁle with the same ﬁle name is re uploaded to Amazon S3, AWS Supply Chain will overwrite the ﬁle on Amazon S3. Connecting to an EDI To ingest data from an EDI data source, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake. 2. On the Data lake page, choose Add New Source. The Select your supply chain data source page appears. 3. Choose EDI. 4. In the EDI Connection Details page, under Name your connection, enter a name for your connection. 5. (Optional) Under Connection description, enter a description for your connection. 6. Under Amazon S3 Bucket Billing, review the Amazon S3 billing information, and then select Acknowledge. 7. Choose Next. Connecting to an EDI 33 AWS Supply Chain User Guide 8. Under Data Mapping, choose Get started. 9. Note EDI 850, EDI 860, and EDI 856 are supported in AWS Supply Chain. Note The required ﬁelds are already mapped. Perform this step only if you want to make speciﬁc changes to the default transformation recipe. On the Mapping Recipe page, you can view the default transformation recipe under Field mappings. Choose Add mapping, to map any additional destination ﬁeld. The Required Destination Fields are mandatory. Choose Destination ﬁeld to add an additional custom destination ﬁeld. Note Review all the entities (for example, Inbound Order, Inbound Order Line, and Inbound Order Line Schedule for EDI 850 Entity Group) under each Entity Group. 10. To view the source ﬁeld values and data mappings from the transformation recipe, you can upload sample data. On the Mapping Recipe page, under Upload sample data, choose browse ﬁles, or drag and drop ﬁles. The sample data ﬁle must contain the required parameters and include the source ﬁeld names. 11. Choose Accept all and continue. 12. Under Review and conﬁrm, you can view the data connection summary. To edit your data ﬁeld mapping, choose Go back to Data Mapping. 13. Choose Conﬁrm and conﬁgure data ingestion to review the Amazon S3 paths where your source data must be uploaded to start the ingestion process. 14. Choose Conﬁrm and conﬁgure data ingestion later if you want to ingest data later. You can ingest data anytime after creating the connection from the AWS Supply Chain dashboard. 15. On the AWS Supply Chain dashboard, choose Open Connections. Select the connection dataﬂow that you want to ingest data, choose the vertical ellipsis, and select Ingestion setup. Connecting to an EDI 34 AWS Supply Chain User Guide Connecting to S/4 HANA Before you can connect to your S/4 HANA data source, you must complete the following prerequisites. After that, AWS Supply Chain automatically creates the Amazon S3 paths and ingests data from the SAP source tables. Prerequisites to connect to S/4 HANA To connect to S/4 HANA data source, the following prerequisites must be completed before ingesting data. 1. Conﬁgure your SAP S/4 HANA system to turn on ODP-based data extraction through the SAP OData connector for Amazon AppFlow. For more information, see SAP OData connector for Amazon AppFlow. 2. Conﬁgure your SAP data sources or extractors, and generate ODP based OData services for AWS Supply Chain to connect and extract information. For more information, see SAP data sources. 3. Conﬁgure your SAP system with one of the following types of authentication: • Basic
supplychain-ug-011	supplychain-ug.pdf	11	source tables. Prerequisites to connect to S/4 HANA To connect to S/4 HANA data source, the following prerequisites must be completed before ingesting data. 1. Conﬁgure your SAP S/4 HANA system to turn on ODP-based data extraction through the SAP OData connector for Amazon AppFlow. For more information, see SAP OData connector for Amazon AppFlow. 2. Conﬁgure your SAP data sources or extractors, and generate ODP based OData services for AWS Supply Chain to connect and extract information. For more information, see SAP data sources. 3. Conﬁgure your SAP system with one of the following types of authentication: • Basic • OAuth 4. Conﬁgure security roles in the SAP system to turn on data extraction. 5. Set up network connectivity to SAP S/4 HANA. If your SAP instance is in a secure VPN and you can't open a port for AWS Supply Chain to connect, we recommend that you use AWS PrivateLink. To manually setup AWS PrivateLink, see AWS for SAP and to automatically setup using AWS CloudFormation, see AWS CloudFormation. Conﬁguring S/4 HANA connection To ingest data from an SAP S/4HANA data source, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake. 2. On the Data lake page, choose Add New Source. The Select your supply chain data source page appears. 3. Choose SAP S/4HANA. 4. Choose Next. Connecting to S/4 HANA 35 AWS Supply Chain User Guide 5. Under SAP S/4HANA Connection Details, enter the following: • Connection name – Enter a name for this connection. • (Optional) Connection description – Enter a name for this connection. • Use Existing AppFlow Connector – Choose Yes to use an existing AppFlow connector. • Application Host URL – Enter the SAP account's URL. • Application Service Path – Enter the SAP application service path. • Port Number – Enter the SAP port number. • Client Number – Enter the SAP client number. • Logon Language – Enter the SAP language code. For example, EN for English. • PrivateLink – Choose Enabled to enable a private connection between the SAP server and your AWS account hosting AWS Supply Chain. • Username – Enter the username of the SAP account. • Password – Enter the password of the SAP account. Note Amazon AppFlow uses the SAP Username and Password provided by you to connect to SAP. 6. Choose Connect to SAP. If the SAP username and password are entered correctly, a Connection Successful message appears. 7. (Optional) Under Optional AppFlow Conﬁguration, Step 1 - Download the JSON template ﬁle, choose Download the existing JSON template ﬁle to modify the appﬂow ingestion settings. Note You can use your own editor to edit the .json ﬁle. You cannot edit the .json ﬁle in AWS Supply Chain. After you update the .json ﬁle, under Step 2 - Upload the modiﬁed JSON template ﬁle, choose browse ﬁles to upload. Connecting to S/4 HANA 36 AWS Supply Chain Note User Guide If this upload is unsuccessful, the Upload summary will display the errors or conﬂicts in the .json ﬁle. You can update the .json ﬁle to ﬁx the issues and re-upload the ﬁle. Here is a sample .json ﬁle with the required schedule, data ﬂows, and source tables. { "schedule" : { "scheduleExpression" : "rate(1days)", // scheduleExpression key should be available and the value cannot be null/empty. Format starts with rate and having time values in minutes, hours, or days. For example, rate(1days) "scheduleStartTime" : null // Supported format - "yyyy-MM- dd'T'hh:mm:ss[+\|-]hh:mm". For example, 2022-04-26T13:00:00-07:00. ScheduleStartTime should atleast be 5 minutes after current time. A null value will automatically set the start time as 5 minutes after the connection creation time }, "dataFlows" : [ // DataFlows cannot be null or empty. Make sure to choose from the list below "Company-Company", "Geography-Geography", "Inventory-Inventory Level", "Inventory-Inventory Policy", "Outbound-Outbound Order Line", "Outbound-Outbound Shipment", "Product-Product", "Product-Product Hierarchy", "Production Order-Inbound Order", "Production Order-Inbound Order Line", "Purchase Order-Inbound Order", "Purchase Order-Inbound Order Line", "Purchase Order-Inbound Order Line Schedule", "Reference-Reference Fields", "Shipment-Shipment", "Site-Site", "Site-Transportation Lane", "Trading Partner-Trading Partner", "Transfer Order-Inbound Order Line", "Vendor Management-Vendor Lead Time", Connecting to S/4 HANA 37 AWS Supply Chain User Guide "Vendor Management-Vendor Product", "Product-Product UOM" ], "sourceTables" : [ // sourceTables cannot be empty { "tableName" : "SomeString", // Should be an existing table name from the SAP instance "extractType" : "DELTA", // Should either be DELTA or FULL "tableCols" : [ // TableCols cannot be empty. Enter valid column names for the table "col1", "col2", "col3" ], "filters" : [// Optional field "colName" : "col1", // colName value should be part of tableCols "dataType" : "String", // Should contain values `STRING` or `DATETIME` "value" : "String", "operator" : "String" // Choose a string value from the pre-defined value of "PROJECTION", "LESS_THAN", "CONTAINS","GREATER_THAN","LESS_THAN_OR_EQUAL_TO","GREATER_THAN_OR_EQUAL_TO","EQUAL_TO","NOT_EQUAL_TO","ADDITION","MULTIPLICATION","DIVISION","SUBTRACTION","MASK_ALL","MASK_FIRST_N","MASK_LAST_N","VALIDATE_NON_NULL","VALIDATE_NON_ZERO","VALIDATE_NON_NEGATIVE",or "VALIDATE_NUMERIC","NO_OP"; ] }, {
supplychain-ug-012	supplychain-ug.pdf	12	: [ // sourceTables cannot be empty { "tableName" : "SomeString", // Should be an existing table name from the SAP instance "extractType" : "DELTA", // Should either be DELTA or FULL "tableCols" : [ // TableCols cannot be empty. Enter valid column names for the table "col1", "col2", "col3" ], "filters" : [// Optional field "colName" : "col1", // colName value should be part of tableCols "dataType" : "String", // Should contain values `STRING` or `DATETIME` "value" : "String", "operator" : "String" // Choose a string value from the pre-defined value of "PROJECTION", "LESS_THAN", "CONTAINS","GREATER_THAN","LESS_THAN_OR_EQUAL_TO","GREATER_THAN_OR_EQUAL_TO","EQUAL_TO","NOT_EQUAL_TO","ADDITION","MULTIPLICATION","DIVISION","SUBTRACTION","MASK_ALL","MASK_FIRST_N","MASK_LAST_N","VALIDATE_NON_NULL","VALIDATE_NON_ZERO","VALIDATE_NON_NEGATIVE",or "VALIDATE_NUMERIC","NO_OP"; ] }, { // sourceTables with same keys - tableName, extractType, tableCols, filters(not mandatory) } ] } 8. Under Amazon S3 Bucket Billing, review the Amazon S3 billing information, and then select Acknowledge. 9. Choose Next. 10. Under Data Mapping, choose Get started. Connecting to S/4 HANA 38 AWS Supply Chain 11. Note User Guide The required ﬁelds are already mapped. Perform this step only if you want to make speciﬁc changes to the default transformation recipe. On the Mapping Recipe page, you can view the default transformation recipe under Field mappings. Choose Add mapping, to map any additional destination ﬁeld. The Required Destination Fields are mandatory. Choose Destination ﬁeld to add an additional custom destination ﬁeld. 12. To view the source ﬁeld values and data mappings from the transformation recipe, you can upload sample data. On the Mapping Recipe page, under Upload sample data, choose browse ﬁles, or drag and drop ﬁles. The sample data ﬁle must contain the required parameters and include the source ﬁeld names. 13. Choose Accept all and continue. 14. Under Review and conﬁrm, you can view the data connection summary. To edit your data ﬁeld mapping, choose Go back to Data Mapping. 15. (Optional) Under Recipe Actions, you can do the following: • Download recipe ﬁle - Select Download to edit your recipe ﬁles in SQL as a text ﬁle. Note For information about built-in SQL functions, see Spark SQL. • Upload recipe ﬁle - Choose browse ﬁles or drag and drop your edited recipe text ﬁles. Select Conﬁrm upload to upload the edited recipe ﬁle and modify your data ﬁeld mappings. 16. To review the Amazon S3 location paths where you must upload your SAP source data for ingestion, choose Conﬁrm and conﬁgure data ingestion. Alternatively, you can choose Conﬁrm and conﬁgure data ingestion later. You can view the data ingestion information anytime. From the AWS Supply Chain dashboard, select Connections. Select the connection dataﬂow that you want to ingest data, choose the vertical ellipsis, and select Ingestion setup. Connecting to S/4 HANA 39 AWS Supply Chain SAP data sources User Guide Conﬁgure the following SAP table sources for AWS Supply Chain to connect and extract information. Note When you search for an SAP data source, preﬁx the data source name with EntityOf. For example, for the data source 0BP_DEF_ADDRESS_ATTR, the entity name should be EntityOf0BP_DEF_ADDRESS_ATTR. When Amazon AppFlow extracts each SAP data source, the entity name format is used to extract information. For example, to extract data from 0BP_DEF_ADDRESS_ATTR, the data is extracted from the entity path /sap/opu/odata/sap/Z0BP_DEF_ADDRESS_ATTR_SRV/ EntityOf0BP_DEF_ADDRESS_ATT. SAP data source SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll 0BP_DEF_ ADDRESS_A TTR 0BPARTNER_ ATTR 0BPARTNER_ TEXT NA NA NA on BP standard address extracti on BP: BW Extractio n Central Data BP: DataSourc e for Business Z0BP_DEF_ ADDRESS_ ATTR_SRV Data source Master data Delta Z0BPARTNER_ ATTR_SRV Data source Master data Delta Z0BPARTNER_ TEXT_SRV Data source Master data Delta Connecting to S/4 HANA 40 AWS Supply Chain SAP data source SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide on Partner Texts Material Valuation : Prices Company Code Text NA NA Customer NA NA Material or Vendor Material NA 0CO_PC_ACT _05 0COMP_CODE _TEXT 0CUSTOMER_ ATTR 0MAT_VEND_ ATTR 0MATERIAL_ ATTR 0MATERIAL_ TEXT Material text 0PURCH_ORG_ TEXT Purchasin g org text NA NA Z0CO_PC_ ACT_05_SRV Data source Master data Z0COMP_CODE _TEXT_SRV Data source Master data Z0CUSTOMER_ ATTR_SRV Data source Z0MAT_VEND_ ATTR_SRV Data source Z0MATERIAL_ ATTR_SRV Z0MATERIAL_ TEXT_SRV Z0PURCH_O RG_TEXT_SRV Data source Data source Data source Master data Master data Master data Master data Master data Full Full Delta Delta Delta Delta Full 0VENDOR_ ATTR Vendor NA Z0VENDOR_ ATTR_SRV Data source Master data Delta Connecting to S/4 HANA 41 AWS Supply Chain SAP data source 2LIS_02_HDR SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide on Purchasin g Data (Header Level) NA Z2LIS_02_ HDR_SRV Data source Transact ional Delta 2LIS_02_ITM Purchasin g Data NA Z2LIS_02_ ITM_SRV Data source Transact ional Delta 2LIS_02_SCL 2LIS_02_SCN 2LIS_03_BF (Item Level) Purchasin g Data (Schedule Line Level) Conﬁrmat ion of Schedule Lines NA NA
supplychain-ug-013	supplychain-ug.pdf	13	data Master data Master data Master data Full Full Delta Delta Delta Delta Full 0VENDOR_ ATTR Vendor NA Z0VENDOR_ ATTR_SRV Data source Master data Delta Connecting to S/4 HANA 41 AWS Supply Chain SAP data source 2LIS_02_HDR SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide on Purchasin g Data (Header Level) NA Z2LIS_02_ HDR_SRV Data source Transact ional Delta 2LIS_02_ITM Purchasin g Data NA Z2LIS_02_ ITM_SRV Data source Transact ional Delta 2LIS_02_SCL 2LIS_02_SCN 2LIS_03_BF (Item Level) Purchasin g Data (Schedule Line Level) Conﬁrmat ion of Schedule Lines NA NA NA Goods Movements from Inventory Managemen t Z2LIS_02_ SCL_SRV Data source Transact ional Delta Z2LIS_02_ SCN_SRV Data source Transact ional Delta Z2LIS_03_ BF_SRV Data source Transact ional Delta 2LIS_04_P _MATNR Material View from PP/ PP-PI NA Z2LIS_04_P_ MATNR_SRV Data source Transact ional Delta Connecting to S/4 HANA 42 AWS Supply Chain SAP data source SAP data source SAP source descripti table on OData service name BW data source SAP data Delta/Fu ll User Guide 2LIS_08TRFKP Shipment Costs NA Z2LIS_08TRFKP _SRV Data source Transact ional Delta at Item Level 2LIS_08TRTLP Shipment: Delivery NA Z2LIS_08TRTLP _SRV Data source Transact ional Delta Item Data by Section Shipment: Header NA Data Sales Document NA Header 2LIS_08TRTK 2LIS_11_ VAHDR 2LIS_11_VAITM Sales NA Document Item 2LIS_12_VCITM Delivery NA Item Data Z2LIS_08TRTK _SRV Data source Transact ional Delta Z2LIS_11 _VAHDR_SRV Data source Transact ional Delta Z2LIS_11_ VAITM_SRV Data source Transact ional Delta Z2LIS_12 _VCITM_SRV Data source Transact ional Delta ZADRC Addresses ADRC ZADRC_SRV Table ZBUT021_FS Partner Address BUT021_FS ZBUT021_FS Table _SRV Master data Master data Full Full Connecting to S/4 HANA 43 AWS Supply Chain SAP data source ZCDHDR ZEINA ZEINE ZEKKO ZEKPO ZEQUI SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide on Change document header Purchasin g Info Record: General Data Purchasin g Info Record: Purchasin g Organiza tion Data Purchasin g Document Header Purchasin g Document Item Equipment master data CDHDR ZCDHDR_SRV Table EINA ZEINA_SRV Table Master data Delta Master data Full ZV_EINE ZEINE_SRV Table Master data Full ZV_EKKO ZEKKO_SRV Table Transact ional Delta ZV_EKPO ZEKPO_SRV Table Transact ional Delta EQUI ZEQUI_SRV Table Master data Full Connecting to S/4 HANA 44 AWS Supply Chain SAP data source ZGEOLOC ZLIKP ZLIPS ZMDRP_NO DTT ZMARC ZMARD ZMCHB on Geo Location Delivery Header Data Delivery: Item Data Node Type for DRP Network Plant Data for Material Storage Location Data for Material Batch Stocks SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide GEOLOC ZGEOLOC_SRV Table LIKP ZLIKP_SRV Table ZV_LIPS ZLIPS_SRV Table Master data Full Transact ional Delta Transact ional Delta MDRP_NODT T ZMDRP_NOD TT_SRV Table Master data Full ZQ_MARC ZMARC_SRV Table ZQ_MARD ZMARD_SRV Table ZQ_MCHB ZMCHB_SRV Table Master data Master data Master data Master data Master data Full Full Full Full Full ZT001W Plant T001W ZT001W_SRV Table ZT005T Country Names T005T ZT005T_SRV Table Connecting to S/4 HANA 45 AWS Supply Chain SAP data source SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide ZT141T ZT173T ZT179 ZT179T ZT370U ZT618T ZTVRAB on Descripti ons of Material Status Shipping Type of Transport Texts Materials : Product Hierarchi es Materials : Product Hierarchi es Text Equipment Category Text Mode of Transport Descripti ons Route Stages T141T ZT141T_SRV Table Master data Full T173T ZT173T_SRV Table Master data Full T179 ZT179_SRV Table Master data Full T179T ZT179T_SRV Table Master data Full T370U ZT370U_SRV Table T618T ZT618T_SRV Table Master data Master data Full Full TVRAB ZTVRAB_SRV Table Master data Full Connecting to S/4 HANA 46 AWS Supply Chain SAP data source SAP data source SAP source descripti table on OData service name BW data source ZTVRO Routes TVRO ZTVRO_SRV Table VALW ZVALW_SRV Table VBBE ZVBBE_SRVs Table ZVALW ZVBBE Route Schedule Sales Requireme nts: Individua l Records User Guide SAP data Delta/Fu ll Full Full Full Master data Master data Master data ZINB_SHI PMENT Shipment Header ZV_INB_ S ZINB_SHIP MENT_SRV Table Transact ional Full and Item HIPMENT (Inbound) based with join conditio n: VTTK.MAND T = VTTP.MAND T and VTTK.TKN UM = VTTP.TKNU M ZAUFK Order Master Data AUFK ZAUFK_SRV Table Master data Full Connecting to S/4 HANA 47 AWS Supply Chain SAP data source ZMARM ZEBAN SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide on Unit of Measure for Material Purchase requisiti ons MARM ZMARM_SRV Table Master data Full EBAN ZEBAN_SRV Table Transacti onal data Delta Connecting to SAP ECC 6.0 To extract your data from SAP ECC 6.0, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake. 2. On the Data
supplychain-ug-014	supplychain-ug.pdf	14	ZAUFK Order Master Data AUFK ZAUFK_SRV Table Master data Full Connecting to S/4 HANA 47 AWS Supply Chain SAP data source ZMARM ZEBAN SAP data source SAP source descripti table OData service name BW data source SAP data Delta/Fu ll User Guide on Unit of Measure for Material Purchase requisiti ons MARM ZMARM_SRV Table Master data Full EBAN ZEBAN_SRV Table Transacti onal data Delta Connecting to SAP ECC 6.0 To extract your data from SAP ECC 6.0, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake. 2. On the Data lake page, choose Add New Source. The Select your supply chain data source page appears. 3. Choose SAP ECC. 4. Under SAP ECC Connection Details, enter the following: • Connection name – Enter a name for your connection. Connection names can only contain letters, numbers, and dashes. • Connection description – Enter a description for your connection. 5. Under Amazon S3 Bucket Billing, review the Amazon S3 billing information, and then select Acknowledge. 6. Choose Next. 7. Under Data Mapping, choose Get started. Connecting to SAP ECC 6.0 48 AWS Supply Chain 8. Note User Guide The required ﬁelds are already mapped. Perform this step only if you want to make speciﬁc changes to the default transformation recipe. On the Mapping Recipe page, you can view the default transformation recipe under Field mappings. Choose Add mapping to map any additional destination ﬁeld. The Required Destination Fields are mandatory. Choose Destination ﬁeld to add an additional custom destination ﬁeld. 9. Note You can only use AWS Glue DataBrew to edit the recipes for transactional entities. Use AWS Supply Chain to download your recipes, and edit them in DataBrew. Then upload the recipes back into AWS Supply Chain. You can't use the AWS Supply Chain web application to edit the transactional data ﬁelds in a recipe. (Optional) Under Recipe Actions, you can do the following: • Download recipe ﬁle - Select Download to edit your recipe ﬁles oﬄine with DataBrew. • Upload recipe ﬁle - Choose browse ﬁles, or move (drag and drop) your edited recipe ﬁles. Select Conﬁrm upload to upload the edited recipe ﬁle and modify your data ﬁeld mappings. • Reset to default recipe - Select Yes, reset my recipe to remove all your custom mappings and revert to the default recipe recommended by AWS Supply Chain. 10. To edit your source ﬁeld mappings and validate your transformation recipe, you can upload sample data. On the Mapping Recipe page, under Upload sample data, choose browse ﬁles, or move (drag and drop) ﬁles. The sample data ﬁle must contain the required parameters and include the source ﬁeld names. 11. Choose Accept all and continue. 12. Under Review and conﬁrm, you can view the data connection summary. To edit your data ﬁeld mapping, choose Go back to Data Mapping. 13. To review the Amazon S3 paths where you must upload your SAP source data for ingestion, choose Conﬁrm and conﬁgure data ingestion. Alternatively, you can choose Conﬁrm and conﬁgure data ingestion later. You can view the data ingestion information anytime. From Connecting to SAP ECC 6.0 49 AWS Supply Chain User Guide the AWS Supply Chain dashboard, select Connections. Select the connection dataﬂow that you want to ingest data, choose the vertical ellipsis, and select Ingestion setup. 14. If you're not using the Amazon S3 API to ingest data, create the Amazon S3 path manually on the Amazon S3 console. For more information about how to create paths, see Uploading data to an Amazon S3 bucket. 15. Review the following table to map the AWS Supply Chain data entity with SAP source. Important On the Amazon S3 path page, you must upload the parent entity before the child entity. You can ﬁrst upload all the parent entities and then upload all the child entities together. Data entity SAP source Hierarchy Data entity action Company – company 0COMP_CODE_TEXT Parent Geography – geography ADRC Parent Inventory – inv_level MARD MCHB VBBE Inventory – inv_policy MARC Parent Parent Child Parent Outbound – outbound_order_line 0MATERIAL_ATTR Child 2LIS_11_VAITM Parent 0BP_DEF_A DDRESS_ATTR Child 0MATERIAL_ATTR Child 2LIS_11_VAHDR Child Replace Replace Update Update Update Replace Update Update Update Update Update Connecting to SAP ECC 6.0 50 AWS Supply Chain User Guide Data entity SAP source Hierarchy Data entity action Outbound – outbound_shipment 2LIS_08TRTLP Parent 2LIS_08TRFKP 2LIS_08TRTK 2LIS_12_VCITM Child Child Child Product – product 0MATERIAL_ATTR Parent 0MATERIAL_TEXT Child Product – product_h ierarchy T179 Parent Purchase order – inbound_order 2LIS_02_HDR Parent CDHDR EKKO Child Child Purchase order – inbound_order_line 2LIS_02_ITM Parent 0MATERIAL_ATTR Child 2LIS_03_BF EKPO LIPS LIKP INB-SHIPMENT Child Child Child Child Child Purchase order – inbound_order_line _schedule 2LIS_02_SCL Parent 2LIS_02_SCN Child Update Update Update Update Replace Update Replace Update Update Update Update Update Update Update Update Update Update Update Update
supplychain-ug-015	supplychain-ug.pdf	15	Update Connecting to SAP ECC 6.0 50 AWS Supply Chain User Guide Data entity SAP source Hierarchy Data entity action Outbound – outbound_shipment 2LIS_08TRTLP Parent 2LIS_08TRFKP 2LIS_08TRTK 2LIS_12_VCITM Child Child Child Product – product 0MATERIAL_ATTR Parent 0MATERIAL_TEXT Child Product – product_h ierarchy T179 Parent Purchase order – inbound_order 2LIS_02_HDR Parent CDHDR EKKO Child Child Purchase order – inbound_order_line 2LIS_02_ITM Parent 0MATERIAL_ATTR Child 2LIS_03_BF EKPO LIPS LIKP INB-SHIPMENT Child Child Child Child Child Purchase order – inbound_order_line _schedule 2LIS_02_SCL Parent 2LIS_02_SCN Child Update Update Update Update Replace Update Replace Update Update Update Update Update Update Update Update Update Update Update Update Connecting to SAP ECC 6.0 51 AWS Supply Chain User Guide Data entity SAP source Hierarchy Data entity action 2LIS_04_P_MATNR Parent Update Production order – inbound_order Production order – inbound_order_line Reference – reference _ﬁeld 2LIS_04_P_MATNR Parent 0CO_PC_ACT_05 Child 0MATERIAL_ATTR Child 0PURCH_ORG_TEXT Parent MDRP_NODTT T005T T141T T173T T179T T370U T618T Parent Parent Parent Parent Parent Parent Parent Shipment – shipment INB-SHIPMENT Parent EQUI LIKP LIPS Parent Parent Parent 0MATERIAL_TEXT Parent 0MAT_VEND_ATTR Parent 0MATERIAL_ATTR Parent EKPO Parent Update Update Update Update Update Update Update Update Update Update Update Replace Replace Replace Replace Replace Replace Replace Replace Connecting to SAP ECC 6.0 52 AWS Supply Chain User Guide Data entity SAP source Hierarchy Data entity action Site – site Trading partner – trading_partner T001W ADRC Parent Parent 0VENDOR_ATTR Parent BUT021_FS T001W ADRC GEOLOC Parent Parent Child Child 0BPARTNER_ATTR Parent 0BPARTNER_TEXT Child 0VENDOR_ATTR Child 0CUSTOMER_ATTR Child 0BP_DEF_A DDRESS_ATTR Child Transfer order – inbound_order_line 2LIS_03_BF Parent 0MATERIAL_ATTR Child Transportation – transportation_lane Vendor management – vendor_lead_time TVRO TVRAB VALW EINA EINE Parent Child Child Parent Child 0MATERIAL_ATTR Child Replace Replace Replace Replace Replace Update Update Update Update Update Update Update Update Update Replace Update Update Replace Update Update Connecting to SAP ECC 6.0 53 AWS Supply Chain User Guide Data entity SAP source Hierarchy Data entity action Vendor management – vendor_product EINA Parent 0MATERIAL_ATTR Child Replace Update Adding a new outbound source for Supply Planning You can use the new outbound source to upload the updated Supply Planning purchase order requests or plan enhancements. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake and then choose the Data Ingestion tab. The Data Ingestion page appears. 2. Choose Add Outbound Source. The Amazon S3 Connection details page appears. 3. Under Connection name, enter a name for your Amazon S3 connection. 4. Under Outbound Data, select the outbound dataﬂow that you want to export. Purchase order request and Supply forecast data ﬂows are supported. 5. Choose Conﬁrm. The new outbound source is created and the Connections page appears. Ingesting data for existing connections The following are the ingestion options if you're using Amazon S3: • Append – To append the ingestion data or for incremental ingestion, all ﬁles from the source path are combined into a single dataset before being ingested into data lake. This method ensures completeness of data for ﬁles spanning multiple days. When you remove ﬁles from the source path in your S3 bucket, ﬁles that are only available in the source path are ingested into data lake. The Append option make sure that your ﬁles in Amazon S3 are replicated and synchronized in data lake. Adding a new outbound source for Supply Planning 54 AWS Supply Chain User Guide • Overwrite – During replace, data ﬁles are ingested into data lake as they're updated in the source path. Each new ﬁle replaces the dataset entirely. Note You can delete source ﬂows and corresponding data in both the Append and Overwrite options. The following are the ingestion operation options for EDI, SAP S/4 HANA, and SAP ECC: • Update – Updates existing rows of data using the same ﬁelds that are used in the recipe. • Replace – Deletes existing, uploaded data and replaces it with the new, incoming data. • Delete – Deletes one or more rows of data by using the primary IDs. To start data ingestion, follow the procedure below. 1. On the AWS Supply Chain dashboard, on the left navigation pane, choose Data Lake. 2. On the Data Ingestion tab, choose Connections. 3. Select the connection to ingest data and choose Data Ingestion. The Data Ingestion Conﬁguration page appears. 4. Choose Get started. 5. On the Data Ingestion Details page, select if you would like to Update, Replace, or Delete the data. Copy the Amazon S3 path by choosing Copy. Uploading data to an Amazon S3 bucket Note Follow this procedure for the SAP ERP Component Central (ECC) connector, and the EDI connector to manually ingest data in the S3 bucket associated with the AWS Supply Chain instance. If you're using the Amazon S3 API to upload data, see Connecting to SAP ECC 6.0, or Connecting to an EDI. Uploading data to an Amazon S3
supplychain-ug-016	supplychain-ug.pdf	16	Ingestion Conﬁguration page appears. 4. Choose Get started. 5. On the Data Ingestion Details page, select if you would like to Update, Replace, or Delete the data. Copy the Amazon S3 path by choosing Copy. Uploading data to an Amazon S3 bucket Note Follow this procedure for the SAP ERP Component Central (ECC) connector, and the EDI connector to manually ingest data in the S3 bucket associated with the AWS Supply Chain instance. If you're using the Amazon S3 API to upload data, see Connecting to SAP ECC 6.0, or Connecting to an EDI. Uploading data to an Amazon S3 bucket 55 AWS Supply Chain User Guide To upload data to an Amazon S3 bucket associated with the AWS Supply Chain instance follow the following procedure. 1. On the AWS Supply Chain dashboard, on the left navigation bar, choose Open Connections. 2. Select the required connection. 3. On the Connection Details page, note down the Amazon S3 path or choose Copy to copy the Amazon S3 path. 4. Open the Amazon S3 console at https://console.aws.amazon.com/s3/ and sign in. 5. Under Buckets, select the name of the bucket (the ﬁrst name in the Amazon S3 path) that you want to upload your folders or ﬁles to. 6. Navigate to the Amazon S3 path that you copied from the AWS Supply Chain dashboard. 7. Choose Upload. Uploading data to an Amazon S3 bucket 56 AWS Supply Chain Insights User Guide You can use AWS Supply Chain Insights to generate inventory shortage and excess and lead time deviation insights based on the watchlist conﬁgured. Insights also provides recommendations on how to resolve the deviations. Insights scans for inventory and lead time risks every 24 hours or when new data is ingested into data lake. Note You can only view the current and projected inventory for products and locations that you are authorized to access. Topics • Insight settings • Viewing the network map • Viewing inventory visibility • Creating insight watchlist • Viewing inventory insights • Resolving an inventory risk insight • Lead time insights Insight settings After creating an instance, follow the procedure below: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. Choose Organization and then choose Insights. The Insight Settings page appears. Insight settings 57 AWS Supply Chain User Guide 2. Under Projection Period, enter the inventory projection time horizon and the time buckets. You can see inventory projections upto a total of six months. Note You can group and analyze the inventory projections in daily, weekly, or monthly intervals. Choosing a daily interval will provide a daily projection and weekly and monthly intervals will provide a long-term projection in a single bucket. Insights supports up to 60 days, 8 weeks, and 3 months per projection bucket. The following example displays the projected inventory level for a portable air conditioner at the New York warehouse for 7 days, next 4 weeks, and 1 month beyond the weeks. 3. Under Rebalancing Recommendations Options, you can setup the radius surrounding the stocked out site to search for available stock for rebalance. You can setup the distance in miles or kilometers. Insight settings 58 AWS Supply Chain User Guide You can conﬁgure the rebalance model to optimize inventory levels for both supplying and receiving sites. Insights supports up to a maximum of six weeks beyond the current date, and you can customize the time horizon by factoring your lead times to see the impact of the rebalance before and after transfers. 4. Under Rebalancing Recommendations Score Weights, use the Up/down arrow to enter the core weight values to determine how ranking is calculated for rebalance recommendations. Depending on the inventory risk resolved, distance, time horizon, available transportation modes from the ingested data (transportation_lane.trans_mode), and shipping costs (transportation_lane.unit_costs), Insights recommends one or more ways to resolve an inventory risk insight. Insights also provides a Score per recommendation which is derived based on the weights conﬁgured. The higher the score, the recommendation is ranked higher and is displayed at the top. • Distance – Distance between your current location and the location where you want to transfer inventory from. • Emissions (CO2) – CO2 emissions computed for the rebalance option. • Risk Resolved – Net improvement in inventory risk percentage when excess inventory is reduced at one location to help restock the current stocked out location. • Shipping Cost – Shipping cost to rebalance and transfer inventory from one location to another. Viewing the network map After ingesting the required datasets for Insights, the network map displays the current and projected inventory for products and locations in a map view for quick understanding of your inventory health and projected health. Locations appear in clusters, and the total number of locations appear under each cluster. You can zoom in
supplychain-ug-017	supplychain-ug.pdf	17	rebalance option. • Risk Resolved – Net improvement in inventory risk percentage when excess inventory is reduced at one location to help restock the current stocked out location. • Shipping Cost – Shipping cost to rebalance and transfer inventory from one location to another. Viewing the network map After ingesting the required datasets for Insights, the network map displays the current and projected inventory for products and locations in a map view for quick understanding of your inventory health and projected health. Locations appear in clusters, and the total number of locations appear under each cluster. You can zoom in on each cluster to see individual locations. Each icon represents a location type. The colored ring shows the inventory health for each location or cluster for the selected time interval on the scroll bar at the bottom left. Inventory health status depends on the inventory policy, that is, min_safety_stock and max_safety_stock in your ingested data. The ring colors are deﬁned as follows: Viewing the network map 59 AWS Supply Chain Note The color code deﬁnitions remain the same throughout Insights. User Guide • Red – Products in this location are stocked out or are at risk of a stock out for future dates. • Green – Products in this location are well within your safety stock levels. • Purple – Products in this location have excess stock or are at risk of a holding more stock than your safety stock levels for this product and site. To view the network map, perform the following procedure. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Network Map. The Network Map page appears. 2. Select a ring and zoom in on a location that you need. You can view the details of the current and projected inventory for one or more particular items. 3. Use the timeslider on the bottom left of the page to view the projected inventory for the current map view. The slider defaults to current date representing current inventory health. 4. Click the +/- symbol to zoom in and out of a particular location in the network map. Viewing the network map 60 AWS Supply Chain User Guide 5. Click the Filter icon to ﬁlter by Locations and Products. Your permissions determine your level of access. When you click on a cluster of sites, you will see a pop-up on the right side of the page, which displays the current inventory levels, safety stock levels for this product, and projected inventory graph. Viewing inventory visibility You can use inventory visibility to view the inventory projections for all the ingested products and site combinations. You can change the projections view by product or location. To view the inventory visibility, perform the following procedure. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Inventory Visibility. 2. To know when the inventory visibility page was last updated, see Date updated on the top right corner of the page. The page is refreshed when you ingest data into data lake. By default, Insights are generated every 24 hours or when data is ingested into data lake. 3. Choose Filters to ﬁlter inventory projections based on Products, Locations, or Inventory Risks. Under All Products, you can select a group of products based on their product hierarchy, that are stored under the product-hierarchy data entity upto one level. Under All Locations, you can select a group of sites based on their regions, that are stored under the geography data entity upto one level. Under Inventory Risks - Current Day Locations, select Excess, Balanced, or Stock Out to view projections with speciﬁc inventory risk for the current date. Viewing inventory visibility 61 AWS Supply Chain User Guide 4. Select the Pivot by dropdown to ﬁlter the inventory by Location or Product. Pivot by Location – When you pivot by location, the inventory projections are grouped by location. At a high-level, for a given location, you can view the site type (for example, RDC, DC, and so on), number of products at the location, number of products that are balanced(that is, well within their safety stock range), number of products that are stocked out, and the number of products that are excess in stock. Pivot by Product – When you pivot by product, the projections are grouped by product. At a high-level, for a given product, you can view the category (that is, one level up), the total number of available products, the total number of products on order, and the total number of products currently in transit across locations. Understanding inventory projections This section explains how to read the inventory projections. Understanding inventory projections 62 AWS Supply Chain User Guide • What is On Hand and Safety stock? – Displays the on-hand inventory value from the latest
supplychain-ug-018	supplychain-ug.pdf	18	products that are excess in stock. Pivot by Product – When you pivot by product, the projections are grouped by product. At a high-level, for a given product, you can view the category (that is, one level up), the total number of available products, the total number of products on order, and the total number of products currently in transit across locations. Understanding inventory projections This section explains how to read the inventory projections. Understanding inventory projections 62 AWS Supply Chain User Guide • What is On Hand and Safety stock? – Displays the on-hand inventory value from the latest snapshot for both past dates and current date. This information is extracted from the inv_level data entity. When there are multiple records with diﬀerent on-hand values for the same snapshot date, Insights will select the latest snapshot record for processing. The safety stock is the range speciﬁed in the inventory policy. • How is demand calculated? – Insights gathers data from the forecast, outbound sales orders, and the transfers orders (that is, products moving out of site for a given time frame) to calculate the total demand. When demand is available at a higher granularity, such as, weekly, monthly, and so on, Insights will spread the forecasted value across the given time frame. • Prior – When you slide the Prior button, you can view the inventory values for the last seven days, including any day in the past. • How is Projected inventory diﬀerent from On Hand? – On hand inventory is the current stock in your ERP system and projected inventory is the future inventory level prediction based on factors such as previous day’s ending on hand/projected level, inbound supply (inbound order line, inbound shipment, inbound order line schedules), outbound sales (outbound order line, outbound shipment, and the demand forecast. Using projected inventory, you can plan the future inventory required to avoid stockouts or overpricing. • How is On Hand diﬀerent from Projected On Hand? – Insights calculates projected on hand when there are no records available for the current date using the same logic used to calculate the projected inventory for future dates. • How is quantity unit of measure (UOM) calculated and are there any defaults used? – The unit for inventory quantity measures, such as on hand, on order, in transit, and projected inventory are displayed to distinguish between eaches, pallets, and cases. To prevent UOM mismatches and streamline calculations, Insights defaults to using the product’s base UOM speciﬁed in the product data entity for conversions. The unit conversions are derived from product_uom and uom_conversion. For more information on the data entities, see Insights. Understanding inventory projections 63 AWS Supply Chain User Guide You can also set the default UOM by adjusting the default conﬁguration. For more information on how to change the default conﬁguration, see Get support for AWS Supply Chain. • Are inventory projections and risks generated for products that are not in stock? – Adjust the inventory policy safety stock range to zero for products that are not in stock. This adjustment will prompt Insights to categorize such product-site combinations as products not in stock. Similarly, you will be alerted to excess stock risks when stock is held at a location. Insights also oﬀers recommendations to move excess stock out and receive stock when there is a stock out. Note This feature is only available in US East (N. Virginia). • How does Insights handle unallocated demand? – When outbound_shipment information is unavailable, Insights will allocate demand from outbound_order_line to either the promised delivery date or the requested delivery date. When outbound_shipment information is available, Insights will distribute the total demand quantity across ship dates. Any unallocated demand in a day and up to six months are carry forwarded. When there is a cancellation, Insights will stop carrying forward the demand. Note This feature is only available in US East (N. Virginia). Creating insight watchlist You can create an insight watchlist to track and notify you on supply chain risks and deviations. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Insights. The Insights page appears. 2. If you are a ﬁrst-time user, select an insight type to create an insight watchlist. See Creating an inventory risk watchlist and Creating a lead time deviation watchlist. To view existing watchlists, see Viewing inventory insights. Creating insight watchlist 64 AWS Supply Chain User Guide Creating an inventory risk watchlist You can create an inventory risk insight watchlist to view projected stock out and excess stock risks generated by Insights from the tracking parameters you selected. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Insights. The Insights page appears. 2. Choose New Insight Watchlist. The Create an Insight Watchlist page appears. 3. Under Select an insight
supplychain-ug-019	supplychain-ug.pdf	19	create an insight watchlist. See Creating an inventory risk watchlist and Creating a lead time deviation watchlist. To view existing watchlists, see Viewing inventory insights. Creating insight watchlist 64 AWS Supply Chain User Guide Creating an inventory risk watchlist You can create an inventory risk insight watchlist to view projected stock out and excess stock risks generated by Insights from the tracking parameters you selected. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Insights. The Insights page appears. 2. Choose New Insight Watchlist. The Create an Insight Watchlist page appears. 3. Under Select an insight type, choose Inventory Risk. 4. Under Name the watchlist, enter a name to track your insight watchlist. 5. Under Select location(s), select the locations from the drop-down that you want to add to your watchlist. 6. Under Select product(s), select the products from the dropdown that you want to add to your watchlist. 7. Under Tracking Parameters, choose what you want to track. The options are Stock Out Risk, Excess Stock Risk, or Both. 8. Under Time Horizon, enter the time frame to generate inventory risk notiﬁcations. Creating an inventory risk watchlist 65 AWS Supply Chain User Guide 9. Under Watchers, you can add other users who you think might beneﬁt from this insight. The users within this insight can track and collaborate to resolve risks. All the settings you chose are displayed on the right. 10. Choose Save to save and create an inventory risk watchlist. Creating a lead time deviation watchlist You can view and receive notiﬁcations for lead time deviations that AWS Supply Chain discovers. You can select any insight, and AWS Supply Chain will recommend how to address it. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Insights. The Insights page appears. 2. Choose New Insight Watchlist. The Create an Insight Watchlist page appears. Creating a lead time deviation watchlist 66 AWS Supply Chain User Guide 3. Under Select an insight type, choose Lead Time Deviation. 4. Under Name the watchlist, enter a name to track your insight watchlist. 5. Under Select location(s), select the locations from the drop-down to add to your watchlist. 6. Under Select product(s), select the products from the drop-down to add to your watchlist. 7. Under Tracking Parameters, Standard deviation, select the lead time deviation percentage from the drop-down. When the percentage is met, AWS Supply Chain will generate an insight and notify you about the lead time deviation. 8. Under Tracking Parameters, Historical time period to track miss frequency, select the historical time period of your ingested data from the drop-down to analyze lead time deviations. 9. Under Watchers, you can add other users to collaborate and share the risks and notiﬁcations. All the settings you chose are displayed on the right. 10. Choose Save to save and create an inventory risk watchlist. Note AWS Supply Chain only supports 1000 insights per watchlist and 100 watchlists per instance. To increase the limit, contact AWS Support. Viewing inventory insights When you create a watchlist for a speciﬁc product, site, risk type, and planning horizon, depending on the notiﬁcations settings, you will get notiﬁed when Insights detects an inventory risk. You will receive notiﬁcations through the web application or email. You can view the inventory risks in Card or Table view. By using the Card view, you can view the risks in a list format separated by when the risks will happen. For example, 0 to 7 days, 7 to 14 days, or 14+ days. Using the Table view, you can view the risks by name of the product, the impacted site name, type of risk, risk in days, the percentage deviation from the relevant threshold, start of the on-hand value, the safety stock values you ingested under the inv_policy data entity for this product/site combination, and the inventory projections. Choose the chat icon to collaborate with your peers on the inventory risk. Viewing inventory insights 67 AWS Supply Chain User Guide You can use the Search ﬁeld to search the inventory insights page by product and site name. Choose Edit on the top-right of the page to edit the inventory insights. For information on how to edit the insight watchlist page, see Creating insight watchlist. Note AWS Supply Chain supports rebalance planning horizon for up to six weeks. • New Insights – This section displays all new insights that AWS Supply Chain discovers after you created your Insight Watchlist. AWS Supply Chain scans for Inventory Risk Insights every 6 hours, and Lead Time Insights every 24 hours. • In Review – This section displays all insights that are currently under review. • Resolved – This section displays resolved insights. Resolving an inventory risk insight Insights recommends one or more ways to resolve an inventory risk depending
supplychain-ug-020	supplychain-ug.pdf	20	edit the insight watchlist page, see Creating insight watchlist. Note AWS Supply Chain supports rebalance planning horizon for up to six weeks. • New Insights – This section displays all new insights that AWS Supply Chain discovers after you created your Insight Watchlist. AWS Supply Chain scans for Inventory Risk Insights every 6 hours, and Lead Time Insights every 24 hours. • In Review – This section displays all insights that are currently under review. • Resolved – This section displays resolved insights. Resolving an inventory risk insight Insights recommends one or more ways to resolve an inventory risk depending on the distance, time horizon, available transportation modes in the ingested data (transportation_lane.trans_mode), shipping costs (transportation_lane.unit_costs), and emissions that you've conﬁgured under Insights settings. The recommendation might include an inventory transfer from other locations within a certain distance and this would resolve an inventory risk in the location under review. Under Settings > Insights, Rebalancing Recommendations Score Weights, you can adjust the core weight values to determine how ranking is calculated for rebalance recommendations. You can setup the radius surrounding the stocked out site to search for available stock for rebalance. You can set the distance in miles and kilometers. You can conﬁgure the rebalance model to optimize inventory levels for both supplying and receiving sites. Insights supports up to a maximum of six weeks beyond the current date, and you can customize the time horizon by factoring your lead times to see the impact of the rebalance before and after transfers. Inventory risk recommendations are helpful for immediately resolving stockout issues rather than overstocks. You may see rebalancing recommendations linked with overstock or excess stock issues but those will have a stockout risk at the receiving site. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Insights. Resolving an inventory risk insight 68 AWS Supply Chain The Insights page appears. 2. Under New Insights, select an insight to resolve the inventory risk. 3. Choose View details. User Guide An overview of the inventory risk with the current and projected inventory, and the rebalance options are displayed. 4. Under the details page, you can view the following: • Identiﬁed – Displays the date on when the inventory risk was identiﬁed. • Product – Displays the product in the inventory that is at risk. • Destination – Displays the destination where the product should be shipped. • Risk Timeframe – Displays the upcoming risk in days with the current inventory. • Summary – Displays the details of the risk in detail. • Current inventory – Displays the inventory that is currently on hand, the safety stock limit, and the allocated amount of inventory against the current orders. • Projected Inventory – Displays how your current inventory is projected starting daily to upto six weeks. Choose the graph icon to view the inventory in a graph. 5. Under Rebalance Options, review the rebalance options and choose Select against the rebalance option recommended by Insights. Once you select the rebalance option, you can view the current and projected inventories before and after the rebalance. 6. On the Conﬁrm Resolution page, the rebalance option that you chose is shown under Resolution Option. 7. Under Message the team, select the After clicking... check box to notify the team on the selected rebalance option. 8. Choose Conﬁrm. 9. Choose Send to Amazon S3 to export the resolution recommendation to your Amazon S3 bucket. Note Insights only recommends options to rebalance inventory. You must use your own planning system to update the inventory transfers or orders. Resolving an inventory risk insight 69 AWS Supply Chain User Guide 10. Choose the chat icon to collaborate with other users or add users as watchers to the current insight. Lead time insights AWS Supply Chain provides insights on the lead time deviation for a vendor, product, and destination site level. The vendor lead time deviation insights also includes transportation mode, source locations, and identify lead time deviations at a more granular level. You can incorporate the recommended lead times in your planning cycle for enhanced planning accuracy and to avoid stock out risks. For example, for supplier S, product P, destination site D, source site S, and transportation mode like Truck, Ship, and so on, the Miss Frequency displays the frequency of time the lead time was missed, compared to the planned lead time (that is, contractual lead times) shared in the vendor_lead_time entity. Therefore, Insights recommends to update the planned lead time for the same vendor, product, and site to avoid future lead time issues. Choose Export All Recommendations to export the vendor lead time recommendations for the ingested product, site, or vendor combinations in a .csv ﬁle into your Amazon S3 bucket. Once the export is completed, you will receive an email and notiﬁcation
supplychain-ug-021	supplychain-ug.pdf	21	and transportation mode like Truck, Ship, and so on, the Miss Frequency displays the frequency of time the lead time was missed, compared to the planned lead time (that is, contractual lead times) shared in the vendor_lead_time entity. Therefore, Insights recommends to update the planned lead time for the same vendor, product, and site to avoid future lead time issues. Choose Export All Recommendations to export the vendor lead time recommendations for the ingested product, site, or vendor combinations in a .csv ﬁle into your Amazon S3 bucket. Once the export is completed, you will receive an email and notiﬁcation on the AWS Supply Chain web application with a link to the Amazon S3 bucket where the recommendations are exported. Lead time insights 70 AWS Supply Chain User Guide When values for optional columns source_site_id and trans_mode in the vendor_lead_time data entity are not available, Insights will use the master records for lead times. However, when transactional data for product, source site, destination site, vendor, and transportation mode is at a more granular level, that is, inbound_order_line and inbound_shipment, it inﬂuences the recommendations and the planned lead time. When there are multiple planned lead time records in the master data ﬁle, Insights will use the highest planned lead time for calculation. Lead time deviations and recommendations For every generated lead time insight, you can select a row to view the historical trend on the vendor's performance on delivering products from a given ship location to the destination location. For all orders that are in progress, you can view the status of the order and anticipate the delivery date. Insights uses a machine learning model trained on historical data spanning 1 to 5 years, a time frame chosen during the watchlist creation process, to provide predicted delivery dates with varying levels of conﬁdence. The Historical Orders graph displays the historical average lead times by month calculated from historical order data based on submitted and delivery dates. The bar graphs represent the current planned lead time value and the recommended lead time for vendors at speciﬁc sites for the given products. The actual lead time for future orders will be equal or lower than the recommended lead time 50% of the time. The Upcoming Orders graph displays the future purchase order lead times by day, calculated by viewing the order’s submitted date and delivery dates. The bar graphs represent the current planned lead time value and the recommended lead time for vendors at speciﬁc sites for the given products. The actual lead time for future orders will be equal or lower than the recommended lead time 50% of the time. The Orders in Progress table displays detailed information of the current or upcoming purchase orders that are at risk based on the model predictions from the historical data for the given vendor, product, and site. The table displays the granular view of all open orders with details such as order quantity, the expected or planned delivery date available from the order line data, and Insights predicted delivery dates with multiple options categorized as Estimated - Low and Estimated - High. The deviation determines the disparity between the estimated high dates and the actual delivery dates available at the order line level. Lead time deviations and recommendations 71 AWS Supply Chain Note User Guide The x-axis in the Historical Orders chart shows months according to the UTC timezone regardless of your location. This means that the beginning of the month coincides with 00h:00m:00s UTC of the ﬁrst day of the month and the end of the month coincides with 23h:59m:59s UTC of the last day of the month. Lead time deviations and recommendations 72 AWS Supply Chain User Guide Order Planning and Tracking You can use Order Planning and Tracking to view order status, expected time of arrival (ETA) predictions, delivery risk and recommendations for each order. AWS Supply Chain uses real-time data from your ERP system and provides in-depth visibility into each order for better planning. Topics • Conﬁguring Order Planning and Tracking for the ﬁrst time • Orders settings • Orders • Procurement • Logistics • Troubleshooting Conﬁguring Order Planning and Tracking for the ﬁrst time As an administrator, you can create multiple processes and milestones to track your orders. Note To generate a order insight, in addition to conﬁguring the processes and milestones for your orders, you must ingest the required data entities and columns. For more information on the required data entities, see Order Planning and Tracking. 1. Open the AWS Supply Chain web application. 2. In the left navigation pane on the AWS Supply Chain dashboard, choose Order Planning and Tracking. The Manage your orders page appears. 3. Choose Setup. 4. On the Orders Setup page, under Getting Started with Orders, choose Create Process. Conﬁguring Order Planning and
supplychain-ug-022	supplychain-ug.pdf	22	create multiple processes and milestones to track your orders. Note To generate a order insight, in addition to conﬁguring the processes and milestones for your orders, you must ingest the required data entities and columns. For more information on the required data entities, see Order Planning and Tracking. 1. Open the AWS Supply Chain web application. 2. In the left navigation pane on the AWS Supply Chain dashboard, choose Order Planning and Tracking. The Manage your orders page appears. 3. Choose Setup. 4. On the Orders Setup page, under Getting Started with Orders, choose Create Process. Conﬁguring Order Planning and Tracking for the ﬁrst time 73 AWS Supply Chain User Guide The Edit Process page appears. Conﬁguring Order Planning and Tracking for the ﬁrst time 74 AWS Supply Chain User Guide 5. Under Please enter the Process ID you expect this conﬁguration to match – Enter the Process ID. If the work_order_plan data entity is uploaded, the Process ID is derived from the work_order_plan data entity or AWS Supply Chain will generate an UUID that you can modify to match the process ID you know will be ingested. 6. Under Enter Process Name – Enter a name for the process. If you have multiple sites that uses the same process name, choose Add Site to add a site with your process. The site value can be determined from any of the entities (process_header, process_operation, process_product, product, site, vendor_product) that have a one-to-one relationship with the order line (process_product). Conﬁguring Order Planning and Tracking for the ﬁrst time 75 AWS Supply Chain User Guide 7. (Optional) Under Lead Time Rule > What method would you like to use to write the rules for this milestone?, choose one of the following: • UI Builder – Select the dataset and the corresponding columns that should be included in the lead time process. Make sure the dataset you select is ingested into data lake. • Manual JSON Upload – Paste the process and rule deﬁnitions in .json format. 8. Under Forecast Date Options, you can specify how you want the forecast completion date to be calculated. • If the target date is missed – Select Add Lead Time to current day if you want the forecast completion date to be the next day. Select Add 1 day to current day to add one day to the forecast completion target. • Forecasted completion rule – Select Work forward from previous process if you want the forecast calculation to work forward from the previous process completion date plus the duration of the current process. This means that the process is trying to complete as soon as possible. Select Work backwards from required on site date for the forecast calculation to subtract the duration from the process target date. This mean the process is trying to complete by the process target date. 9. Create the milestones for this process – Select the milestone name and type from the dropdown. 10. Choose Add Milestone to add a new milestone. 11. Choose Continue. The Milestone Rules page appears. Review the milestone rules you created. 12. Choose Save and Exit. Orders settings You can setup orders and track the material status from vendor to delivery using the following procedure. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Organization, choose Orders . The Order setting page appears. Orders settings 76 AWS Supply Chain User Guide 3. Under the Process List tab, you can view all the conﬁgured processes or processes that need to be conﬁgured. You can delete or create new processes. 4. Choose Import/Export. Orders settings 77 AWS Supply Chain User Guide 5. Under Import / Export Order Conﬁguration, choose Save to copy the Milestone Deﬁnitions, Process Deﬁnitions, and Default Order Plans in JSON format. You can use this feature to setup the conﬁguration in one instance (for example, pre-production instance) and then copy the same conﬁguration to another instance (for example, production instance). 6. (Optional) Under the Default Order Plans tab, you can setup fallback lead times for processes that don't match the order plan data. By default, order planning and tracking uses the lead time information from the work_order_plan dataset. If order tracking can't ﬁnd the material to process combination in the wwork_order_plan dataset, order planning and tracking will use the default order plan conﬁguration for matching lead times. Order plans are segmented by the reservation_type in the reservation dataset. To use the default order conﬁguration, the reservation dataset must be ingested. The reservation types are displayed under the order conﬁguration and you can setup the order plan for each reservation type by adding processes and deﬁning lead times for each process. 7. (Optional) Under the Procurement and Logistics tab, expand Procurement and Logistics. 8. Under Procurement and
supplychain-ug-023	supplychain-ug.pdf	23	work_order_plan dataset. If order tracking can't ﬁnd the material to process combination in the wwork_order_plan dataset, order planning and tracking will use the default order plan conﬁguration for matching lead times. Order plans are segmented by the reservation_type in the reservation dataset. To use the default order conﬁguration, the reservation dataset must be ingested. The reservation types are displayed under the order conﬁguration and you can setup the order plan for each reservation type by adding processes and deﬁning lead times for each process. 7. (Optional) Under the Procurement and Logistics tab, expand Procurement and Logistics. 8. Under Procurement and Logistics, choose Add Process to add the processes that should be listed on the Procurement and Logistics page. Orders settings 78 AWS Supply Chain Note User Guide When there are no processes added under Procurement or Logistics, the Procurement and Logistics tab will display the details of all the processes. 9. On the Select an existing process page, select an existing process from the drop-down. 10. Choose Add. 11. Choose Save. Organization Labels As an administrator, you can customize the order labels. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Organization, choose Organization Labels . The Organization Labels page appears. Organization Labels 79 AWS Supply Chain User Guide 3. Under Change to Label, enter the preferred name for each Default Label. Note Changing the default label will update your entire organization with the new label for Orders. For example, you will see the Orders table updated when you update the Order, Order Description, Main Work Center, and Planner Group labels under Organization Labels (see screenshot above). 4. Choose Save. Organization Labels 80 AWS Supply Chain User Guide 5. To change the customized labels to the default labels, choose Reset all to Defaults. Orders You can view all the orders that are at-risk, delivered, early, late, on time, or watch. You can expand the order to view the materials under each order. In the left navigation pane on the AWS Supply Chain dashboard, choose Order Planning and Tracking. The Order Planning and Tracking page appears. Choose Filters to ﬁlter the orders based on Country/Location, Campaign, Revision , Main Work Center, Process Name, and Planner Group. Once you set your ﬁlters, choose Apply. You can also choose Save ﬁlter group to save your ﬁlters. You can also ﬁlter the orders by All, On Time/Early, Watch, At Risk, Late, Delivered, and Site Delivery Forecast status. For example, if you choose Late, you will see all the orders that are currently late or delayed. You can use the Search ﬁeld to search by order or material number and use the Sort option to sort the orders. You can sort them by any of the headers but by default, the orders are sorted ﬁrst by Site Delivery Forecast and second by Order Priority. The Orders page, displays the following from your ERP or source system: Orders 81 AWS Supply Chain User Guide Orders column Description Data entity Column Order Campaign/Revision Main Work Center Planner Group Order Description Order End Date Order Priority Display the order number. You can select the order to view your ERP or source system. You can expand each order to view the materials in the order. Displays the campaign and/or the revision of the order. Displays the main work center deﬁned in the source system. Displays the planning group for each order. Displays a brief reasoning of the order. Displays the date by which the order should me completed . Displays the priority of the order. AWS Supply Chain will only accept a numerical value for this ﬁeld. For process_header process_id process_header program_group process_header revision process_header execution_group process_header planning_group process_header description process_header planned_completion _date process_header priority Orders 82 AWS Supply Chain User Guide Orders column Description Data entity Column example, 1,2,3, and so on. If your ERP system doesn't contain a numerical value for this ﬁeld, you will not be able to sort the order by priority. The date when all the materials are required on-site before starting the work. Custom ﬁelds that can be renamed and populated with any data. Planned Start Date Flex 1 to 5 process_header planned_start_date process_header ﬂex_1, ﬂex_2, ﬂex_3, ﬂex_4, ﬂex_5 Recommendation Displays all actionabl e items and is linked Calculated by Order Planning and Calculated by Order Planning and to a milestone. For Tracking Tracking example, if the order is blocked with a PO blocked milestone, the recommendation text will display to look for alternate products. Orders 83 AWS Supply Chain User Guide Orders column Description Data entity Column Site Delivery Forecast Displays one of the following: • At risk – Displayed when the material with the latest arrival date has a process that is either delayed or is in a blocked milestone. This item
supplychain-ug-024	supplychain-ug.pdf	24	ﬂex_1, ﬂex_2, ﬂex_3, ﬂex_4, ﬂex_5 Recommendation Displays all actionabl e items and is linked Calculated by Order Planning and Calculated by Order Planning and to a milestone. For Tracking Tracking example, if the order is blocked with a PO blocked milestone, the recommendation text will display to look for alternate products. Orders 83 AWS Supply Chain User Guide Orders column Description Data entity Column Site Delivery Forecast Displays one of the following: • At risk – Displayed when the material with the latest arrival date has a process that is either delayed or is in a blocked milestone. This item can still make the required date and is displayed in Yellow. • Delivered – Displayed after the last milestone of the last process is initiated indicating the completion of the process. • Early – Displayed in green when all the order lines are early and includes the count of days of the earliest line. • Late – Displayed when the order is running late due to the underlying order material with the latest delivery Orders 84 AWS Supply Chain User Guide Orders column Description Data entity Column date estimated to arrive late. This item is displayed in Red. • On-time – Displayed when the materials under the order is reaching the site within the required on-site date. This item is displayed in Green. • Watch – Displayed when the material with the latest date is either blocked or late in a current supply chain process. Viewing order materials You can view all the materials related to a order. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Order Planning and Tracking. The Order Planning and Tracking page appears. 2. Expand the order you would like to view. The Materials in Order page appears. Viewing order materials 85 AWS Supply Chain User Guide Order Lines Description Data entity Column Material Material Description Quantity/UoM Material Source Required on Site Brand name Product status Product type Reservation type Displays the material number. Provides a descripti on of the material. Lists the quantity of the material. If UoM is available, UoM value is displayed . For example, 2 eaches. Displays if the material is in inventory or direct purchase. Displays the date on which the material is required on-site. Provides a name of the brand. Provides the status of the product. Provides the type of the product. Provides the type of the reservation. process_product product_id product description reservation quantity quantity_uom site description inbound_order tpartner_id trading_partner description process_header planned_start_date process_product requested_availabi lity_date product brand_name process_product status process_product type reservation reservation_type Viewing order materials 86 AWS Supply Chain User Guide Order Lines Description Data entity Column Process product allocation type Process product allocation status Displays the allocation type for the product. . Displays the allocation status for the product. . process_product overallocation process_product allocation_status Product ﬂexible ﬁeld 1 to 5 Custom ﬁelds that can be renamed and process_product ﬂex_1, ﬂex_2, ﬂex_3, ﬂex_4, ﬂex_5 populated with any data. Reservation ﬂexible ﬁeld 1 to 5 Displays the reservation type of reservation ﬂex_1, ﬂex_2, ﬂex_3, ﬂex_4, ﬂex_5 Revision Order type the product. Displays the material revision. Displays the order type. process_header revision process_header type Current Process Displays the current supply chain process Calculated by order planning and Calculated by order planning and for the order tracking. tracking. Recommendation Site Delivery Forecast material. Displays all actionable items and is linked to a milestone. Displays the site delivery forecast and status. Viewing order materials 87 AWS Supply Chain User Guide 3. Choose the Material you would like to view in-detail. The Material Summary page appears and displays the summary of the material. Viewing order materials 88 AWS Supply Chain User Guide You can view the current milestone for the material and the recommendation AWS Supply Chain provides for each milestone. Material Description Data entity Column Material name Material Quantity/UoM Required on Site Displays the name of the material. Provides a descripti on of the material. Lists the quantity of the material. If UoM is available, UoM value is displayed . For example, 2 eaches. Displays the date on which the material is required on-site. product description process_product product_id reservation quantity reservation quantity_uom process_header planned_start_date process_product requested_availabi lity_date Viewing order materials 89 AWS Supply Chain Material Vendor PO Delivery Date Description Data entity Column User Guide Display the vendor from which the material is being procured. Displays the purchase order delivery date. inbound_order tpartner_id trading_partner description inbound_order_line expected_delivery_ date Site Delivery Forecast Displays the site delivery forecast Calculated by order planning and and status. tracking. Updated PO Delivery Date Displays the updated PO delivery Update Quantity date. Displays the updated product quantity. Supplier Delivery Date Conﬁrmation Displays the delivery date conﬁrmation Process product allocation type Process product allocation status from the supplier. Displays the allocation type for the
supplychain-ug-025	supplychain-ug.pdf	25	Viewing order materials 89 AWS Supply Chain Material Vendor PO Delivery Date Description Data entity Column User Guide Display the vendor from which the material is being procured. Displays the purchase order delivery date. inbound_order tpartner_id trading_partner description inbound_order_line expected_delivery_ date Site Delivery Forecast Displays the site delivery forecast Calculated by order planning and and status. tracking. Updated PO Delivery Date Displays the updated PO delivery Update Quantity date. Displays the updated product quantity. Supplier Delivery Date Conﬁrmation Displays the delivery date conﬁrmation Process product allocation type Process product allocation status from the supplier. Displays the allocation type for the product. . Displays the allocation status for the product. . process_product allocation_type process_product allocation_status Inventory Location Displays the inventory location. site description Viewing order materials 90 AWS Supply Chain User Guide Material Description Data entity Column Inco Terms Reservation Type Brand Name Product Status Product Type Campaign Order PR/Line Number Displays the incoterm code. Displays the type of reservation. Displays the brand name of the product. Displays the product status. Displays the product type. Displays the campaign of the order. Display the order number. You can select the order to view your ERP or source system. You can select the procurement or line number to view in your ERP or source system. inbound_order_line incoterm reservation reservation_type product brand_name process_product status process_product type process_header program_group process_product process_id process_header process_url reservation requisition_id reservation requisition_line_id inbound_order_line inbound_order_line _url Viewing order materials 91 AWS Supply Chain User Guide Material Description Data entity Column PO/Line Number You can select the purchase order (PO) or line number to view in your ERP or source system. reservation order_id reservation order_line_id inbound_order_line STO/Line Number You can select the STO or line number to view in your ERP or source system. reservation reservation reservation reservation inbound_order_line inbound_order_line _url stock_transfer_1_o rder_id stock_transfer_1_o rder_line_id stock_transfer_2_o rder_id stock_transfer_2_o rder_line_id inbound_order_line _url reservation rfq_id reservation rfq_line_id inbound_order_line inbound_order_line _url product product_type process_product currency_uom RFQ/Line Number Product Type Currency UOM You can select the RFQ or line number to view in your ERP or source system. Displays the type of the product. Displays the currency unit of measure for the price and other economic variables of this product. . Viewing order materials 92 AWS Supply Chain Material Danger Hazmat Class UN Class UN Description Image Description Data entity Column User Guide product un_id un_details un_class un_details hazmat_class un_details un_description un_details image_url Displays the products that are hazardous. Displays the products that contain hazardous materials. Displays the products that are under the hazardous category. Displays the description of the products that are under the hazardous category. Displays an image of the products that are under the hazardous category. 4. Choose Copy shareable link to clipboard to share the material summary dashboard. 5. Choose the Edit icon to edit the material summary view. Slide the data entity button to view the data ﬁeld on the material summary page. Viewing order materials 93 AWS Supply Chain User Guide You can drag and drop the data entities to rearrange the date entity view on the material summary page. 6. Choose Save Changes. 7. Slide the Show Completed Milestones button to view all the completed milestones for a material. Viewing order materials 94 AWS Supply Chain Procurement User Guide You can view the procurement details for all the items ordered as part of a order. By default, you can view the supply chain processes for procurement and you can use the ﬁlters to view a subset of procurement processes. You can select the Material Name to view the corresponding procurement summary. In the left navigation pane on the AWS Supply Chain dashboard, choose Order Planning and Tracking. The Order Planning and Tracking page appears. Choose the Procurement tab. You can choose Filters to ﬁlter the orders based on Country/Location, Campaign, Revision , Main Work Center, Process Name, and Planner Group. Once you set your ﬁlters, choose Apply. You can also choose Save ﬁlter group to save your ﬁlters. You can also ﬁlter the orders by All, On Time, Delivered, Watch, At Risk, and Late status. For example, if you choose Late, you will see all the orders that are currently late or delayed. You can use the Search ﬁeld to search for the required orders. You can sort them by any of the headers but by default, the orders are sorted ﬁrst by Site Delivery Forecast and second by Work Priority. The Procurement page, displays the following from your ERP or source system: Procurement 95 AWS Supply Chain User Guide Procurement column Description Data entity Column Order Revision Order type PR/Line RFQ/Line PO/Line Order Priority process_product process_id process_header process_url process_header revision process_header type reservation requisition_id reservation requisition_line_id inbound_order_line inbound_order_line _url reservation rfq_id reservation rfq_line_id inbound_order_line inbound_order_line _url reservation order_id reservation order_line_id inbound_order_line inbound_order_line _url process_header priority Display the order
supplychain-ug-026	supplychain-ug.pdf	26	to search for the required orders. You can sort them by any of the headers but by default, the orders are sorted ﬁrst by Site Delivery Forecast and second by Work Priority. The Procurement page, displays the following from your ERP or source system: Procurement 95 AWS Supply Chain User Guide Procurement column Description Data entity Column Order Revision Order type PR/Line RFQ/Line PO/Line Order Priority process_product process_id process_header process_url process_header revision process_header type reservation requisition_id reservation requisition_line_id inbound_order_line inbound_order_line _url reservation rfq_id reservation rfq_line_id inbound_order_line inbound_order_line _url reservation order_id reservation order_line_id inbound_order_line inbound_order_line _url process_header priority Display the order number. You can select the order to view your ERP or source system. Displays the material revision. Displays the order type. You can select the procurement or line number to view in your ERP or source system. You can select the RFQ or line number to view in your ERP or source system. You can select the purchase order (PO) or line number to view in your ERP or source system. Displays the priority of the order. AWS Supply Chain will only accept a numerical value Procurement 96 AWS Supply Chain User Guide Procurement column Description Data entity Column for this ﬁeld. For example, 1,2,3, and so on. If your ERP system doesn't contain a numerical value for this ﬁeld, you will not be able to sort the order by priority. Displays the name of material that is being procured. If a material is marked Hazmat in your ERP system, AWS Supply Chain will display the Hazmat sign next to the material. You can select the material name to view the current order milestone . Slide the Show Completed Milestone s button to view all the completed milestones for a material. Displays the allocatio n type for the product. . Material Name Process product allocation type process_product product_id process_product allocation_type Procurement 97 AWS Supply Chain User Guide Procurement column Description Data entity Column QTY/UoM Source Required on Site Displays the quantity of the material that is being procured. Display the source from which the material is being procured. Displays the date the product is required at the order site. reservation quantity reservation quantity_uom trading_partner description inbound_order tpartner_id process_header planned_start_date process_product request_availabili ty_date Current Process Displays the current process of the order. Calculated by order planning and Calculated by order planning and tracking. tracking. Procurement 98 AWS Supply Chain User Guide Procurement column Description Data entity Column Site Delivery Forecast Displays the current process of the order. • Late – Displayed when the order is running late due to the underlying order material with the latest delivery date estimated to arrive late. This item is displayed in Red. • On-time – Displayed when the materials under the order is reaching the site within the required on-site date. This item is displayed in Green. • At risk – Displayed when the material with the latest arrival date has a process that is either delayed or is in a blocked milestone. This item can still make the required date and is displayed in Yellow. Procurement 99 AWS Supply Chain User Guide Procurement column Description Data entity Column • Watch – Displayed when the material with the latest date is either blocked or late in a current supply chain process. • Delivered – Displayed after the last milestone of the last process is initiated indicating the completion of the process. Recommended Action Due Date Displays the current process of the order. Recommendation Displays all actionabl e items and is linked to a milestone. Logistics You can view the logistics details for all the items ordered as part of a order. You can select the Material Name to view the corresponding material summary for any supply chain process. In the left navigation pane on the AWS Supply Chain dashboard, choose Order Planning and Tracking. The Order Planning and Tracking page appears. Choose the Logistics tab. Logistics 100 AWS Supply Chain User Guide You can choose Filters to ﬁlter the orders based on Country/Location, Campaign, Revision , Main Work Center, Process Name, and Planner Group. Once you set your ﬁlters, choose Apply. You can also choose Save ﬁlter group to save your ﬁlters. You can also ﬁlter the orders by All, On Time, Delivered, Watch, At Risk, and Late status. For example. if you choose Late, you will see all the orders that are currently late or delayed. You can use the Search ﬁeld to search for the required orders. You can sort them by any of the headers but by default, the orders are sorted ﬁrst by Site Delivery Forecast and second by Work Priority. The Logistics page, displays the following from your ERP or source system: Logistics column Description Data entity Column Order Display the order number. You can select the order to view
supplychain-ug-027	supplychain-ug.pdf	27	ﬁlter the orders by All, On Time, Delivered, Watch, At Risk, and Late status. For example. if you choose Late, you will see all the orders that are currently late or delayed. You can use the Search ﬁeld to search for the required orders. You can sort them by any of the headers but by default, the orders are sorted ﬁrst by Site Delivery Forecast and second by Work Priority. The Logistics page, displays the following from your ERP or source system: Logistics column Description Data entity Column Order Display the order number. You can select the order to view your ERP or source system. process_product process_id process_header process_url Logistics 101 AWS Supply Chain User Guide Logistics column Description Data entity Column Revision Order type PR/Line PO/Line STO/Line Displays the material revision. process_header revision Displays the order type. You can select the procurement or line number to view in your ERP or source system. You can select the purchase order (PO) or line number to view in your ERP or source system. You can select the standard transfer order (STO) or line number to view in your ERP or source system. process_header type reservation requisition_id reservation requisition_line_id inbound_order_line inbound_order_line _url reservation order_id reservation order_line_id inbound_order_line reservation reservation reservation reservation inbound_order_line _url stock_transfer_1_o rder_id stock_transfer_1_o rder_line_id stock_transfer_2_o rder_id stock_transfer_2_o rder_line_id Logistics 102 AWS Supply Chain User Guide Logistics column Description Data entity Column process_header priority process_product product_id Order Priority Material Name Displays the priority of the order. AWS Supply Chain will only accept a numerical value for this ﬁeld. For example, 1,2,3, and so on. If your ERP system doesn't contain a numerical value for this ﬁeld, you will not be able to sort the order by priority. Displays the name of material that is being procured. If a material is marked Hazmat in your ERP system, AWS Supply Chain will display the Hazmat sign next to the material. You can select the material name to view the current order milestone . Slide the Show Completed Milestone s button to view all the completed milestones for a material. Logistics 103 AWS Supply Chain User Guide Logistics column Description Data entity Column QTY/UoM Source Required on Site Displays the quantity of the material that is being procured. Display the source from which the material is being procured. Displays the date on which the material is required on-site. reservation quantity reservation quantity_uom trading_partner description inbound_order tpartner_id process_header planned_start_date process_product request_availabili ty_date Logistics 104 AWS Supply Chain User Guide Logistics column Description Data entity Column Site Delivery Forecast Displays the current process of the order. Calculated by order planning and Calculated by order planning and tracking. tracking. • Late – Displayed when the order is running late due to the underlying order material with the latest delivery date estimated to arrive late. This item is displayed in Red. • On-time – Displayed when the materials under the order is reaching the site within the required on-site date. This item is displayed in Green. • At risk – Displayed when the material with the latest arrival date has a process that is either delayed or is in a blocked milestone. This item can still make the required date and is displayed in Yellow. Logistics 105 AWS Supply Chain User Guide Logistics column Description Data entity Column • Watch – Displayed when the material with the latest date is either blocked or late in a current supply chain process. • Delivered – Displayed after the last milestone of the last process is initiated indicating the completion of the process. Displays the current milestone. Current Process Recommended Action Due Date Displays the current process of the order. Recommendation Displays all actionabl e items and is linked to a milestone. Troubleshooting This section contains information about how to troubleshoot order planning and tracking issues that may occur. Issue Resolution Order planning and tracking page is blank • Make sure data ingestion is complete. • Check the data quality tab under Data Lake for missing required entities or any speciﬁc Troubleshooting 106 AWS Supply Chain Issue User Guide Resolution errors. For information on required entities for order planning and tracking, see Order Planning and Tracking. • Make sure the order planning and tracking conﬁguration is complete. For more information, see Orders settings. A speciﬁc column is not displayed under orders or order lines Hover over on any column name and select the three vertical dots. Choose Manage columns and make sure the required column is selected. Column or ﬁeld values are not displayed under orders or orders insights • Make sure the column name has a value in the dataset. • Check the data mapping between the source and destination ﬁelds in the data lake page. For more information, see Uploading ﬁles for the ﬁrst time. A column or
supplychain-ug-028	supplychain-ug.pdf	28	order planning and tracking conﬁguration is complete. For more information, see Orders settings. A speciﬁc column is not displayed under orders or order lines Hover over on any column name and select the three vertical dots. Choose Manage columns and make sure the required column is selected. Column or ﬁeld values are not displayed under orders or orders insights • Make sure the column name has a value in the dataset. • Check the data mapping between the source and destination ﬁelds in the data lake page. For more information, see Uploading ﬁles for the ﬁrst time. A column or ﬁeld is not displayed under Material Summary • Make sure the column name has a value in the dataset. • Check the data mapping between the source and destination ﬁelds in the data lake page. For more information, see Uploading ﬁles for the ﬁrst time. • Choose Edit on the material summary page to see if the data entity is enabled to view on the material summary page. Troubleshooting 107 AWS Supply Chain User Guide Demand Planning Demand Planning is a web-based application that allows business users to create, collaborate, and publish demand plans. Demand Planning generates forecasts using proprietary machine learning algorithms based on historical forecasting experience. Topics • Terminology used in Demand Planning • Create your ﬁrst demand plan • Data Validation and Demand Pattern Analysis • Forecast Algorithms • Forecast based on demand drivers • Product lineage • Product lifecycle • Manage demand plans • Forecast model analyzer • Manage Demand Plan settings • Role-based access control Terminology used in Demand Planning The following is the common terminology that you may frequently use in Demand Planning. • Enterprise demand plan – A single planning workbook that consolidates forecast input from multiple stakeholders to create a uniﬁed forecast. It can consist of multiple planning cycles, enabling iterative reﬁnement of forecast based on evolving forecast input dataset. The enterprise demand plan displays two status points: • Active – The planning cycle is open and you can edit your forecast. • Published – The planning cycle is closed, and you cannot edit your forecast. However, you can view the demand plan. • Demand planning cycle – The time taken to create and ﬁnalize demand plans, which include forecast generation, and collaborating with stakeholders to adjust and publish demand plans. Terminology used in Demand Planning 108 AWS Supply Chain User Guide • Dataset – A collection of data used for generating forecasts, such as historical sales orders or product information. • Forecast granularity – Deﬁnes how you want to create and manage the forecast. You can use a combination of product, location, customer, and channel dimensions. You can also choose the time interval for the forecast data to be aggregated by day, week, month, or year for each product in the dataset. For example, if your forecast granularity is set as Daily, you will see the forecast daily for each product in the dataset. Note Demand Planning uses the Gregorian calendar for planning. The default start day of the week is Monday. • Forecast conﬁguration – The set of conﬁgurations for forecast generation. This includes the planning cycle conﬁguration, time horizon granularity, and that hierarchy conﬁguration that inﬂuences how Demand Planning will generate the forecast. • System generated forecast – This is also known as the baseline forecast. It refers to the use of the historical data by the system to generate a forecast. It provides initial demand prediction before you apply any overrides. • Override – A modiﬁcation that you make to the system generated forecast. • Published demand plan – The ﬁnal output of the planning workbook. You can choose to publish the ﬁnalized demand plan to downstream inventory and supply planning systems for implementation. • Product lineage – You can establish links between products and their previous versions or alternate products and set rules for the amount of historical data to be used in forecasting. For more information, see Product lineage. • Product lifecycle – The product lifecycle refers to the various stages of a product from introduction to End of Life (EoL). For more information on product lifecycle, see Product lifecycle. • Demand driver – Factors that directly inﬂuence the level of demand for a particular product. For example, advertising and marketing eﬀorts, pricing strategies, and so on. For more information on demand drivers, see Forecast based on demand drivers. • Forecast lag – The time between when the forecast was created and the actual demand. For example, forecast from January considered for February is considered a one month lag. Similarly, forecast from January that is considered for March is considered a two month lag. Terminology used in Demand Planning 109 AWS Supply Chain User Guide • Forecast Model Analyzer – You can use this tool to
supplychain-ug-029	supplychain-ug.pdf	29	directly inﬂuence the level of demand for a particular product. For example, advertising and marketing eﬀorts, pricing strategies, and so on. For more information on demand drivers, see Forecast based on demand drivers. • Forecast lag – The time between when the forecast was created and the actual demand. For example, forecast from January considered for February is considered a one month lag. Similarly, forecast from January that is considered for March is considered a two month lag. Terminology used in Demand Planning 109 AWS Supply Chain User Guide • Forecast Model Analyzer – You can use this tool to execute trial or experimental forecast by varying test conditions and reviewing the results of the diﬀerent forecast methods. You can use the results to compare and evaluate model performance, ensuring the best selection based on business priorities. • Forecast Lock – You can use the forecast lock feature to lock speciﬁc periods in your forecast to prevent any further edits or adjustments. • Intra-cycle Forecast Refresh – You can refresh the forecast mid-cycle and incorporate the latest forecast input data without ﬁnalizing the demand plan. • # of Forecasts – Number of unique time-series forecasts, where each time-series represents a distinct combination of product, site, customer, and channel as per demand plan conﬁguration. • Critical Rules – Data validation rules that, if violated, can block forecast creation. For more information, see Prequisites before uploading your dataset. • Data Validation – The process of checking data for completeness, correctness, and consistency before using it for forecasting. • Demand Pattern Analysis – Exploratory Data Analysis of forecast input data including classifying historical demand data into diﬀerent patterns. Create your ﬁrst demand plan When you log into Demand Planning for the ﬁrst time, you will be able to view the onboarding pages that highlight key product features and help you get familiar with the Demand Planning capabilities. Overview of the process: To create your ﬁrst forecast, from the left navigation bar, choose Demand Planning, Manage Demand Plan, and Create forecast. The system guides you through the following steps. For more information, see the section called “Role-based access control”. 1. Data ingestion – Before proceeding with conﬁguration, the system veriﬁes that required datasets are ingested into Data Lake. You need the following, at minimum. For more information about which table and columns are used by Demand Planning, including prerequisites, see the section called “Demand Planning”. • Required: Outbound Order Line and Product data • Recommended: Product Alternate and Supplementary Time Series data Create your ﬁrst demand plan 110 AWS Supply Chain User Guide 2. Plan conﬁguration – After data ingestion is complete, you'll conﬁgure various aspects of your demand plan, including forecast dimensions, time frames, settings, and scheduling options. After Demand Planning is conﬁgured, you can view or modify the demand plan conﬁguration settings by choosing Settings, Organization, and Demand Planning. 3. Plan creation – After conﬁguration, choosing Generate Forecast initiates three sub-processes: • Data Validation: System validates data quality and completeness • Demand Pattern Analysis & Recommendations: System analyzes historical patterns and provides insights • Forecast Creation: System generates the forecast In an ideal scenario, where no data validation errors are found, the system smoothly proceeds through all three steps, creating both the demand pattern analysis report and forecast. However, if any data validation errors are detected, the system halts both the forecast creation and demand pattern analysis until the errors are resolved. Work with your data administrator to correct the underlying data issues, and choose Retry to try forecast creation again. 1. On the Conﬁgure Demand Planning page, there are ﬁve steps to conﬁgure Demand Planning. • Scope – Deﬁnes the dimensions and the time frame for Demand Planning to generate forecasts. • Conﬁgure your dataset – Deﬁnes the outbound_order_line dataset. This option is mandatory for Demand Planning to generate an accurate forecast. You also deﬁne how you want Demand Planning to handle negative quantity values in the outbound_order_line dataset. For more information about mandatory and optional Demand Planning ﬁelds, see Data entities and columns used in AWS Supply Chain. • Forecast Settings – Set global parameters to determine the forecast period, minimum forecast value, and initialization values for new products with no alternate data. • Scheduler – You can deﬁne how and when forecasts should be refreshed and published. • Organization Settings – Deﬁnes where your Demand Plans will be published. It also shows other conﬁguration options within the application. 2. Under Scope, Planning Horizon, select the following: • Time Interval – Select the time interval from the choice of daily, weekly, monthly, or yearly options. The time interval is used to aggregate and analyze data. Choose a time interval based on the nature of your business, availability, and granularity of historical data. Create your ﬁrst demand plan 111 AWS Supply
supplychain-ug-030	supplychain-ug.pdf	30	no alternate data. • Scheduler – You can deﬁne how and when forecasts should be refreshed and published. • Organization Settings – Deﬁnes where your Demand Plans will be published. It also shows other conﬁguration options within the application. 2. Under Scope, Planning Horizon, select the following: • Time Interval – Select the time interval from the choice of daily, weekly, monthly, or yearly options. The time interval is used to aggregate and analyze data. Choose a time interval based on the nature of your business, availability, and granularity of historical data. Create your ﬁrst demand plan 111 AWS Supply Chain User Guide • Time Horizon – Time horizon is the speciﬁc period for when a forecast is generated. The value should be a whole number with a minimum value of 1 and maximum of 500. The amount of historical data available also will dictate the Time Horizon. Make sure that at least one product in the outbound_order_line dataset has sales history at least four times the time horizon set. For example, if you set Time Horizon to 26 and Time Interval as weekly, the minimum order data requirement is 26*4 = 104 weeks. Under Forecast Granularity, Required Hierarchy, select the parameters to deﬁne your forecast hierarchy. Product ID attribute is mandatory and is automatically selected as the last level in the hierarchy. You can choose Add level to add additional hierarchy levels between product_group_id, product_type, brand_name, color, display_desc, and parent_product_id. Make sure that the required hierarchy attributes have information in the product dataset, because you can use these attributes to ﬁlter the demand plan. Under Optional Hierarchy, choose Add level to add up to ﬁve attributes from Site, Channel, and Customer to better manage your forecast. The supported columns from the outbound_order_line dataset are: • Site hierarchy = ship_from_site_id, ship_to_site_id, ship_to_site_address_city, ship_to_address_state, ship_to_address_country • Channel hierarchy = channel_id • Customer hierarchy = customer_tpartner_id Make sure that the required hierarchy attributes have information in the product dataset since these attributes are used to ﬁlter demand plans. 3. Choose Continue. 4. On the Conﬁgure your dataset page, under Conﬁgure Forecast Input, you should conﬁgure the required and recommended datasets. Note AWS Supply Chain recommends uploading two to three years of outbound order line history as an input to generate an accurate forecast. This duration allows the forecasting models to capture your business cycles and ensure a more robust and Create your ﬁrst demand plan 112 AWS Supply Chain User Guide reliable prediction. For improved forecast accuracy, it is also recommended to include product attributes such as brand, product_group_id, and price in the product dataset. • Required Datasets – The outbound_order_line and product data entities are required to generate a forecast. • Recommended Datasets – The product_alternate and supplementary_time_series data entities are optional. You can generate a forecast without these data entities but when provided, the forecast quality will be improved. 5. Under Required Datasets, expand Historical Demand and choose Conﬁgure to set the negative value for missing data. outbound_order_line dataset is the primary source of historical demand. • Ignore – Select if you want AWS Supply Chain to ignore the products with missing order_date before creating the forecast. • Replace with zero – Select if you want AWS Supply Chain to replace the missing order_date ﬁelds with zero by default to the ﬁnal requested quantity. 6. No additional conﬁguration is required for product data entity. Product attributes are used for ﬁlters, conﬁgure hierarchy, and for training the learning model. 7. Under Recommended Datasets, no additional conﬁguration is required for product_lineage. You can use the product_alternate data entity to provide information on alternate or previous version of the product. For more information on product lineage, see Product lineage. 8. Select Demand Drivers if you have demand drivers information such as promotions, price changes, and so on, you can use supplementary_time_series data entity to ingest data. You can select up to 13 demand drivers and conﬁgure aggregation and missing data ﬁlling strategy. For more information on demand drivers, see Forecast based on demand drivers. 9. Choose Continue. 10. On the Forecast Settings page, you need to conﬁgure the following: • Choose the forecast model/ensembler for the plan. AWS Supply Chain Demand Planning has a default forecast model assigned for the demand plan. Customers have the ability to change the default if they choose to. Create your ﬁrst demand plan 113 AWS Supply Chain Note User Guide The AWS Supply Chain assigned default model will be used if the user does not change the selection. • Under Forecast Start Date, enter the forecast start date to start the planning cycle. • Max History Date – Select this option if you want to start forecasting from the next time period after the last complete historical data point. • Plan Execution Date – Demand Planning uses
supplychain-ug-031	supplychain-ug.pdf	31	a default forecast model assigned for the demand plan. Customers have the ability to change the default if they choose to. Create your ﬁrst demand plan 113 AWS Supply Chain Note User Guide The AWS Supply Chain assigned default model will be used if the user does not change the selection. • Under Forecast Start Date, enter the forecast start date to start the planning cycle. • Max History Date – Select this option if you want to start forecasting from the next time period after the last complete historical data point. • Plan Execution Date – Demand Planning uses this date when the forecast is triggered as the start of the planning cycle. • Custom Date – Select this option when the selected forecast start date is later than the outbound_order_line dataset end date then the default planning cycle start date is considered. If the selected forecast start date is before the outbound_order_line start date or if the length of the demand history is insuﬃcient, the forecast will fail and display an error. For more information, see Prequisites before uploading your dataset. It is recommended to select the ﬁrst of the month for monthly intervals or Monday for weekly intervals. If you choose a diﬀerent date, Demand Planning will automatically adjust to the nearest default date. For example, if you selected Wednesday as the forecast start date, Demand Planning will select the next Monday as the forecast start date for weekly intervals. Similarly, selecting May 10th 2024 will result in June 1st 2024 as the planning cycle start date for monthly intervals. • Under Handling Partial History and Filling Strategy, select one of the following: • Trim Partial History – Select this option to trim the partial history. For example, the illustration below explains how trim partial history works for the following settings: • Weekly granularity start period – Monday (default Demand Planning setting) • Monthly granularity start period – 1st of the Gregorian Calendar Month (default Demand Planning setting) • Demand plan granularity – Weekly • Forecast start date– Plan run date • Trim partial history – Set to Yes • Plan run date – Set to Monday • Forecast horizon – Four weeks Create your ﬁrst demand plan 114 AWS Supply Chain User Guide • Include Partial History – Select this option to include the partial history and use a ﬁlling strategy to ﬁll the gaps. For example, if you are forecasting at a monthly level and your last month in history has only 10 days of data, you can choose to trim or exclude the 10 days of data. If you choose not to trim or exclude the 10 days of data, you can select a ﬁlling strategy to ﬁll data for the rest of the month. • Zero – Use this ﬁlling method when no sales activity is expected for certain periods. Impact: May lead to lower forecast, best for seasonal data with expected zero demand • NaN – Use this ﬁlling method when marking data is missing. • Mean – Use this ﬁlling method when smoothing out ﬂuctuations. • Median – Use this ﬁlling method when minimizing the inﬂuence of outliers or data skewness. • Min – Use this ﬁlling method when representing the lowest possible value for conservative forecasting. • Max – Use this ﬁlling method when assuming the highest possible value for optimistic forecasting Impact. • Under Conﬁgure Forecast Periods in..., select the start and end dates for New Product Introduction (NPI) and End-of-life EOL) products. For more information, see Product lifecycle. • Under New Product Initial Forecast, enter an initial forecast value for products with no demand history or product lineage to make the products searchable in the demand plan web application and to create a forecast. Specify the value and the periods to apply. Create your ﬁrst demand plan 115 AWS Supply Chain Note User Guide The time period displayed will depend on the time period you chose under Time intervals in the Planning Horizon page. For example, if you chose Monthly under Time intervals, you will be able to specify the number of months before or after to start and stop the forecast, and for products with no demand history. • The planning cycle start date is based on the last order date in the outbound order line dataset. If the time interval conﬁguration is: • Daily – Planning cycle start date will be the day after the last order date. For example, if the last order date is October 30, 2023, the planning cycle start date will be October 31, 2023. • Weekly or Monthly – When the last order date is the same as the time boundary, the planning cycle start date will be after a week or month. For example, when the last order date is
supplychain-ug-032	supplychain-ug.pdf	32	history. • The planning cycle start date is based on the last order date in the outbound order line dataset. If the time interval conﬁguration is: • Daily – Planning cycle start date will be the day after the last order date. For example, if the last order date is October 30, 2023, the planning cycle start date will be October 31, 2023. • Weekly or Monthly – When the last order date is the same as the time boundary, the planning cycle start date will be after a week or month. For example, when the last order date is October 29, 2023 (which is a Sunday and Demand Planning's week time boundary), the planning cycle start date will be October 30, 2023. When the last order date falls within the time boundary, Demand Planning will trim the order history for the last time window and create forecast from the new period. For example, when the last order date is November 01, 2023 (which is a Wednesday and not in the Demand Planning's week time boundary), the planning cycle start date will be October 30, 2023. Demand Planning will ignore the order history from October 30, 2023 to November 01, 2023. • Under Accuracy Metrics Preferences, setup three diﬀerent lags for your organization. 11. Choose Continue. 12. On the Demand Plan Publish Scheduler page, under How do you like to manage ongoing forecast refresh and demand plan release?, choose Auto to view your next forecast plan published on the Demand Planning page. Under Set the release frequency for the ﬁnal demand plan, choose the frequency at which you want to publish the demand plans to the downstream processes and close the planning cycle. (Optional) Under Set the intra-cycle forecast refresh frequency, select the frequency of the forecast update within the same planning cycle without releasing the interim updates to the Create your ﬁrst demand plan 116 AWS Supply Chain User Guide downstream processes or closing the planning cycle. You can also select None to opt-out of intra-cycle forecast refresh frequency. 13. Choose Continue. 14. Under Organization Settings, note the Amazon Simple Storage Service (Amazon S3) path where the demand plans are published. Note You can also ﬁnd the Amazon S3 path for the published demand plans on the Settings page. For more information, see Manage Demand Plan settings. Forecast is generated only when you ingest data into AWS Supply Chain. Make sure that all the required and optional attributes that you chose have information in the dataset. Data Validation and Demand Pattern Analysis Data Validation and Demand Pattern Analysis tools help you evaluate the quality of your data and identify key patterns inﬂuencing your demand forecasts. These insights help you understand which patterns are likely to impact demand. Topics • Data Validation • Demand Pattern and Recommendation Data Validation Data Validation is a crucial step early in the forecast creation process that ensures the input data meets the necessary quality standards for forecasting. This feature runs a series of checks on your data, surfacing data errors that need to be ﬁxed before proceeding to forecast creation, helping you identify and resolve issues early in the process. The data validation step is preceded by a set of preprocessing activities to prepare the data, based on the plan settings or deﬁnition, which includes the following: • Aggregation to align with forecast granularity. For example: Data Validation and Demand Pattern Analysis 117 AWS Supply Chain User Guide • If your forecast granularity is set to weekly, daily demand history data will be aggregated to weekly totals. • If your demand history contains product, site, customer, and channel dimensions, but your forecast granularity is set to product-site level, the system will aggregate sales across all customers and channels for each product-site combination. • Data transformations from Demand Plan settings. These transformations are based on your Demand Planning conﬁguration settings. For example, if you have conﬁgured the system to ignore negative values, these will be handled accordingly. • Product lineage consideration. The system takes into account product relationships, such as predecessor-successor pairs or product alternatives, as deﬁned in your conﬁguration. • Supplementary time series transformation. The system transforms supplementary time series data into demand drivers that can inﬂuence the forecast generation. These transformed demand drivers provide additional context to the items above. Topics • Data Validation Process • Data Validation Report Access • Data Validation Error Export • Data Validation Rules Data Validation Process After the preprocessing process described above completes, the data validation process begins. Data validation consists of three steps: 1. Data Structure Validationthe section called “Demand Planning” - This step includes checks to ensure all required tables and columns exist and have data before any transformation begins. This stage conﬁrms your data tables are properly set up. 2. Data Quality Validation -
supplychain-ug-033	supplychain-ug.pdf	33	that can inﬂuence the forecast generation. These transformed demand drivers provide additional context to the items above. Topics • Data Validation Process • Data Validation Report Access • Data Validation Error Export • Data Validation Rules Data Validation Process After the preprocessing process described above completes, the data validation process begins. Data validation consists of three steps: 1. Data Structure Validationthe section called “Demand Planning” - This step includes checks to ensure all required tables and columns exist and have data before any transformation begins. This stage conﬁrms your data tables are properly set up. 2. Data Quality Validation - This step ensures that data content is complete and error-free. It checks for: • Missing values in essential ﬁelds • Validation checks on data formats and validity of dates • Data completeness required for building forecast input Data Validation 118 AWS Supply Chain User Guide This ensures all necessary data is present and valid before proceeding with transformations. 3. Forecasting Eligibility Validation: This step ensures that suﬃcient data is provided to create a forecast, including: • Minimum historical data requirements • Time series length limitations • Other algorithm-speciﬁc constraints This stage ensures that your data is suitable for generating forecasts. Even a single validation failure will stop the forecast creation process. You must work with your data administrator to correct the underlying data issues, then choose Retry to try forecast creation again. Data Validation Report Access When creating a forecast for the ﬁrst time, navigate to the Demand Planning module in AWS Supply Chain and choose Create a Plan. The system guides you through three steps: Data Ingestion, Plan Conﬁguration, and ﬁnally, Forecast Generation. After completing data ingestion and plan conﬁguration, choose Generate Forecast to initiate data validation. Each new forecast generation creates a fresh validation report based on the current state of your data. Data Structure validation failures (such as missing tables or columns) appear as banner messages at the top of your screen. These fundamental issues must be resolved before proceeding. After data structure validation passes, the system proceeds with Data Quality and Forecasting Eligibility validations. Any failures in these stages are detailed in the validation report, accessible by choosing Data Validations. Subsequent Forecast Creation For subsequent forecasts, choose Generate Forecast. You will see a banner displaying three steps, with data validation as the ﬁrst step. The same validation behavior applies. Structural issues appear as banners, while other validation failures are available in the detailed report. Data Validation 119 AWS Supply Chain Report Content User Guide The Data Validation Issues report provides a comprehensive view of Data Quality and Forecasting Eligibility validation failures that need to be addressed. The report displays the following: • Dataset: Identiﬁes the speciﬁc dataset where the issue occurs • Rule: Describes the type of validation that failed • Error Date/Time: Shows when the error was detected • Status Message: Provides detailed information about the records aﬀected and recommended actions To help navigate and resolve these issues, you can do the following: • Use the search box to ﬁnd speciﬁc types of errors • Filter by dataset using the drop-down menu • Download a detailed report containing all validation failures • View Records aﬀected for each validation to understand the scope of the issue Data Validation Error Export Error records can be exported by choosing Download on the Data Validation report page when the validation is checking individual data points that failed. Note The export option is not available when the validation is checking structural, systemic, or aggregate-level requirements. Export is available for the following: • Validation checks for content or quality of existing data • Validations that involve checking for missing or invalid values in existing ﬁelds • Data Quality Validations (such as null checks, and date range validations) Data Validation 120 AWS Supply Chain Note User Guide The system limits error record downloads to a maximum of 10,000 rows. If the total error count exceeds this limit, a notiﬁcation will appear on the screen. Work with your data administrator to review and resolve all errors in the source table. Export is not available for the following: • Validation checks for structural elements (such as table existence or column presence) • Validations that involve system-level constraints (such as size limits, counts, and thresholds) • Forecasting eligibility checks (such as time series limits or active product counts) Data Validation Rules The validations performed prior to forecast creation are below. For more information, see the section called “Demand Planning”. Rule Type Rule Datasets Description Export error records? Data Structure Validation Mandatory columns existence validation Product, Outbound order Veriﬁes presence of critical No line, Supplemen columns in tary time series datasets in required datasets: Outbound order line: product_i d, order_dat e, ﬁnal_qua ntity_requested Product: id, description Data Validation 121 AWS Supply Chain Rule Type Rule Datasets
supplychain-ug-034	supplychain-ug.pdf	34	involve system-level constraints (such as size limits, counts, and thresholds) • Forecasting eligibility checks (such as time series limits or active product counts) Data Validation Rules The validations performed prior to forecast creation are below. For more information, see the section called “Demand Planning”. Rule Type Rule Datasets Description Export error records? Data Structure Validation Mandatory columns existence validation Product, Outbound order Veriﬁes presence of critical No line, Supplemen columns in tary time series datasets in required datasets: Outbound order line: product_i d, order_dat e, ﬁnal_qua ntity_requested Product: id, description Data Validation 121 AWS Supply Chain Rule Type Rule Datasets Description User Guide Export error records? Veriﬁes presence of critical columns in recommend ed datasets, if provided: Supplementary Time Series: id, order_dat e, time_seri es_name, time_seri es_value Data Validation 122 AWS Supply Chain Rule Type Rule Datasets Description User Guide Export error records? Data Structure Validation Granulari ty columns existence validation Product, Outbound order Veriﬁes presence of columns No line set as forecast granularity, if set in the demand plan settings. Outbound order line: product_i d, ship_from _site_id, ship_to_s ite_id, ship_to_s ite_address_city, ship_to_a ddress_state, ship_to_a ddress_country, channel_id, customer_ tpartner_id Product: id, product_g roup_id, product_type, brand_name, color, display_d esc, parent_pr oduct_id Data Validation 123 AWS Supply Chain Rule Type Rule Datasets Description User Guide Export error records? Data Structure Validation Active product's history validatio Product, Outbound order Veriﬁes that there is atleast No n line,Product one active Alternate product that has history on its own or through product lineage Data Quality Validation Missing values in mandatory Product, Outbound order Veriﬁes for null/ empty values Yes columns validation line, Supplemen tary time series in mandatory columns speciﬁed in Mandatory columns existence check Data Quality Validation Missing values in granulari Product, Outbound order Veriﬁes for null/ empty values Yes ty columns validation line in mandatory columns speciﬁed in Granulari ty columns existence check Data Validation 124 AWS Supply Chain Rule Type Rule Datasets Description User Guide Export error records? Data Quality Validation Date Range validation OutboundO rderLine, Supplemen The order_dat e column in the dataset must Yes taryTimeSeries contain dates Forecasting Eligibility Validation Timeseries per Predictor validation OutboundO rderLine in a sane time range: Anywhere from 01/01/190 0 00:00:00 to 12/31/2050 00:00:00. No The timeserie s per predictor must not exceed 5,000,000. "Timeseries per predictor " is calculated by taking the count of unique values for the product_id column and each of the forecast granularity columns and then taking the product of all those counts. Data Validation 125 AWS Supply Chain User Guide Rule Type Rule Datasets Description Forecasting Eligibility Validation Count of active products validation Product The number of active products with records in the OOL dataset must not exceed 800,000. Export error records? No Data Validation 126 AWS Supply Chain User Guide Export error records? No Rule Type Rule Datasets Description Forecasting Eligibility Validation Historical data suﬃciency Outbound order line validation Veriﬁes if at least one product in the dataset has suﬃcien t historical demand data to generate reliable forecasts The forecast horizon must be no greater than 1/3 the time range in the dataset (if training a new auto predictor ) or 1/4 the time range in the dataset (if training an existing auto predictor). There is also a global maximum forecast horizon, which is 500. Data Validation 127 AWS Supply Chain User Guide Export error records? No No Rule Type Rule Datasets Description Forecasting Eligibility Validation Row Count validation Partitioned OutboundO rderLine Forecasting Eligibility Validation Maximum Timeseries validation Partitioned OutboundO rderLine The number of records in the partition ed OOL dataset must not exceed 3,000,000 ,000. There are certain forecast models that have smaller limits that are checked here as well, if those models are being used. The number of distinct timeseries must not exceed the model's limit, if there is one. "Distinct timeseries" is deﬁned as the number of distinct rows in the dataset when product_i d + all forecast granularity columns are considered. Data Validation 128 AWS Supply Chain Rule Type Rule Datasets Description User Guide Export error records? Forecasting Eligibility Validation Data Density validation Partitioned OutboundO rderLine The Data density of the dataset must be at least No 5. Data density is deﬁned as (number of distinct products in the dataset) / (total number of rows in the dataset). In other words it is "average rows per product". Note The rule applies only when Prophet is selected as the forecasti ng algorithm . Data Validation 129 AWS Supply Chain User Guide Demand Pattern and Recommendation Demand Pattern and Recommendation examines the transformed historical demand input at each conﬁgured forecast granularity level (for example, product, location, or channel) to uncover underlying patterns and characteristics in your demand data. Its primary purpose is to identify key demand pattern distribution, such as smooth, intermittent, erratic, and lumpy. It also
supplychain-ug-035	supplychain-ug.pdf	35	distinct products in the dataset) / (total number of rows in the dataset). In other words it is "average rows per product". Note The rule applies only when Prophet is selected as the forecasti ng algorithm . Data Validation 129 AWS Supply Chain User Guide Demand Pattern and Recommendation Demand Pattern and Recommendation examines the transformed historical demand input at each conﬁgured forecast granularity level (for example, product, location, or channel) to uncover underlying patterns and characteristics in your demand data. Its primary purpose is to identify key demand pattern distribution, such as smooth, intermittent, erratic, and lumpy. It also provides statistical insights about length of history and trailing 12-month demand. The analysis automatically triggers after successful data validation during the forecast generation process, and runs in parallel with forecast creation. However, it does not block or delay the forecasting process. The Demand Pattern analysis is triggered as part of the same workﬂow as data validation when you initiate forecast creation. However, any data validation failure prevents both the analysis from being generated and the forecast from being created. By providing this analytical overview, the system helps users understand the patterns in the dataset to improve forecast accuracy. Demand Patterns Components Demand Patterns analysis happens on three dimensions: • Demand Patterns (based on how demand changes over time and in quantity) • Annual Demand (total quantity demanded over a 12-month period) • History Length (the time period for which historical demand data is available) The analysis categorizes your demand patterns into four distinct types: smooth, intermittent, erratic, and lumpy. Each is determined by analyzing the frequency and variability of demand. If there are eligible in-scope products with no historical data, it is grouped under the Zero Forecast Demand section. For more information, see Demand pattern. The distribution of demand patterns across your products provides valuable insights into expected forecast reliability. Products with smooth demand patterns (showing consistent order volumes and frequencies) typically yield the most reliable forecasts, because their behavior is more predictable. In contrast, erratic or lumpy patterns, characterized by irregular spikes and varying order frequencies, generally result in lower forecast reliability due to their unpredictable nature. By understanding this distribution, demand planners can set appropriate expectations and take proactive measures. Demand Pattern and Recommendation 130 AWS Supply Chain User Guide The system also analyzes your trailing 12-month demand (subject to trimming conﬁguration), also known as Annual Demand, immediately preceding your forecast start date. For example, assume the forecast start date is January 15, 2024 (Monday) and the planning bucket is weekly. The system considers the trailing 12 month analysis period to be from January 16, 2023 to January 14, 2024. The trailing 12-month demand analysis helps demand planners distinguish between active and inactive products, while identifying products transitioning between these states - patterns that directly impact forecast reliability. By focusing on recent history rather than older data patterns, you can make more informed decisions about which products need special attention or alternative forecasting approaches, particularly for cases like seasonal items, discontinued products, or items in phase-out. For more information, see Forecast Algorithms. The history length in years is calculated for each forecast granularity (for example, product- location combination) based on the earliest and latest dates available in your preprocessed historical demand data, after adjusting the dates to the default start of the period. This analysis helps determine if products have accumulated enough historical data to generate reliable forecasts, with a minimum of two years typically needed to capture seasonal patterns and long- term trends. Demand Patterns Recommendations The system provides targeted recommendations based on identiﬁed demand patterns to help improve forecast accuracy. For products displaying erratic demand, characterized by irregular spikes in order volume, the system suggests incorporating potential external inﬂuences, such as promotions or price changes. In such cases, you can signiﬁcantly improve forecast accuracy by collaborating with your data administrator to upload relevant demand driver data to the Demand Pattern and Recommendation 131 AWS Supply Chain User Guide Supplementary Time Series table in the data lake. This additional context helps the forecasting models better understand and predict demand ﬂuctuations. For products with insuﬃcient history (less than 2 years) or no history at all, the system recommends leveraging alternate product mapping. This approach allows you to utilize the demand patterns of similar, established products to enhance forecast reliability. Work with your data administrator to upload these product relationships to the Product Alternate table in the data lake. This is particularly important because accurate seasonality and long-term trend detection requires at least 2 full years of historical data. By mapping to alternate products with suﬃcient history, you can establish a more reliable forecast baseline for newer or limited-history products. Demand Pattern and Recommendation Report Access First time forecast creation When creating a forecast for the ﬁrst time, under
supplychain-ug-036	supplychain-ug.pdf	36	leveraging alternate product mapping. This approach allows you to utilize the demand patterns of similar, established products to enhance forecast reliability. Work with your data administrator to upload these product relationships to the Product Alternate table in the data lake. This is particularly important because accurate seasonality and long-term trend detection requires at least 2 full years of historical data. By mapping to alternate products with suﬃcient history, you can establish a more reliable forecast baseline for newer or limited-history products. Demand Pattern and Recommendation Report Access First time forecast creation When creating a forecast for the ﬁrst time, under the Demand Planning module in AWS Supply Chain, choose Create a Plan. The system guides you through three steps: Data Ingestion, Plan Conﬁguration, and ﬁnally, Forecast Generation. After completing data ingestion and plan conﬁguration, choose Generate Forecast to initiate data validation. Upon successful validation, the system performs demand pattern analysis, and you see a hyperlink to access this analysis while your forecast generates. Subsequent forecast creation For subsequent forecasts, choose Generate Forecast. You see a banner displaying three steps: data validation, demand pattern analysis & recommendation, and forecast creation. After data validation is successful and the demand pattern analysis is complete, access the report by choosing its hyperlink in the banner. Report content The Demand Pattern and Recommendations report provides a summary view of exploratory data analysis at your conﬁgured forecast level for a given plan. At the top of the screen, you see ﬁve key pattern cards that show how your products are distributed: Smooth patterns, Intermittent patterns, Erratic patterns, Lumpy patterns, and Products with Zero Historical Demand. Below this summary, you can ﬁnd a detailed table breaking down patterns by the highest conﬁgured level in product hierarchy in the Demand Plan Settings. For example, if your product Demand Pattern and Recommendation 132 AWS Supply Chain User Guide hierarchy conﬁguration follows pattern product id, product group id, then you will see the summary at the product group id. For each category, you can see the following: • # Forecasts, indicating the unique time series are eligible for forecast and its percentage of total • The annual demand volume and its percentage of total • A visual breakdown of demand pattern within that category • A visual breakdown of the length of history available within that category To help you navigate this information, you can do the following: • Use the search box to ﬁnd speciﬁc product categories • Download a detailed report. The report contains detailed analysis for each individual forecast at your conﬁgured granularity level • Sort any product category, # Forecasts, and Annual Demand to focus on speciﬁc metrics. For product categories containing alphanumeric formats or blank values, using the search function may be more eﬀective. Ongoing access After each successful forecast creation, you can revisit this analysis on the Demand Pattern tab in the forecast review pages. In this view, the analysis responds to any ﬁlters you apply in the forecast review. The downloaded report contains analysis speciﬁc to your ﬁltered selection. Forecast Algorithms AWS Supply Chain Demand Planning oﬀers a combination of 25 built-in forecast models to create baseline demand forecasts for products with diverse demand patterns in customers’ datasets. The list of 25 forecast models includes 11 forecast ensemblers (each ensembler is unique based on the set of models that make up the ensembler and/or the metric the ensembler optimizes to) and 14 individual forecast algorithms including statistical algorithms like Autoregressive Integrated and Moving Average (ARIMA) to complex neural network algorithms like CNN-QR, Temporal Fusion Transformer and DeepAR+. Customers have the choice of using forecast ensembler or individual forecast algorithm based on their use case and unique needs. While the forecast ensemblers oﬀer the advantage of customers not having to manually deal with cumbersome tasks such as model selection, hyperparameter tuning and having to simply pick the forecast error metric that is best suited for the customer use case that the ensembler would optimize , the individual forecast Forecast Algorithms 133 AWS Supply Chain User Guide algorithms oﬀer ﬂexibility for customer use cases that and best forecasted with a single model instead of an ensemble. The following table lists the 25 built-in forecast models oﬀered by AWS Supply Chain Demand Planning along with what they are best suited for. Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon Best At least 2 times Ensembler Quality the Yes Ensemble of baseline, AutoGluon best_qual MAPE (Mean Automated Ensemble Yes, Past ity Absolute without and (MAPE) forecast statistic preset Percentag need horizon al , ML/ e Error) for Future Related Deep learning
supplychain-ug-037	supplychain-ug.pdf	37	oﬀered by AWS Supply Chain Demand Planning along with what they are best suited for. Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon Best At least 2 times Ensembler Quality the Yes Ensemble of baseline, AutoGluon best_qual MAPE (Mean Automated Ensemble Yes, Past ity Absolute without and (MAPE) forecast statistic preset Percentag need horizon al , ML/ e Error) for Future Related Deep learning models in the AutoGluon model library. Ensemble of baseline, statistic al , ML/ Deep learning models in the manual Time model Series assignmen t/ selecti on. Automated Ensemble without need for manual model Yes, Past and Future Related Time Series assignmen t/ Yes AutoGluon best_qual ity preset WAPE (Weighted Absolute Percentag e Error) Forecast Model(s) Ensembler AutoGluon Best Quality (WAPE) At least 2 times the forecast horizon Forecast Algorithms 134 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) AutoGluon model library. User Guide Scenario( s) the Supports Related Times as Forecast Inputt - Yes/ No? model is best suited for selecti on. Forecast Model(s) AutoGluon Best At least 2 times Ensembler Quality the Yes Ensemble of baseline, AutoGluon best_qual MASE (Mean Automated Ensemble Yes, Past ity Absolute without and (MASE) forecast statistic preset Scaled need horizon al , ML/ Error) for Future Related Deep learning models in the AutoGluon model library. manual Time model Series assignmen t/ selecti on. Forecast Algorithms 135 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon Best At least 2 times Ensembler Quality the Yes Ensemble of baseline, AutoGluon best_qual RMSE (Root Automated Ensemble Yes, Past ity Mean without and (RMSE) forecast statistic preset Squared need horizon al , ML/ Error) for Future Related Deep learning models in the AutoGluon model library. manual Time model Series assignmen t/ selecti on. Forecast Model(s) AutoGluon Best At least 2 times Ensembler Quality the Yes Ensemble of baseline, AutoGluon best_qual WCD (Weighted Automated Ensemble Yes, Past ity Cumulativ without and (WCD) forecast statistic preset e Deviation ) horizon al , ML/ Deep learning models in the AutoGluon model library. need for manual model Future Related Time Series assignmen t/ selecti on. Forecast Algorithms 136 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon StatEnsem At least 2 times Ensemble of all Yes AutoGluon all MAPE (Mean Automated Ensemble No Ensembler ble the statistic Supported Absolute without (MAPE) forecast al horizon models(on Stats Model Percentag need e Error) for ly) in the AutoGluon model library eto produce forecasts . manual model assignmen t/ selecti on. Forecast Algorithms 137 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon StatEnsem At least 2 times Ensemble of all Yes AutoGluon all WAPE (Weighted Automated Ensemble No Ensembler ble the statistic Supported Absolute without (WAPE) forecast al horizon models(on Stats Model Percentag need e Error) for ly) in the AutoGluon model library eto produce forecasts . manual model assignmen t/ selecti on. Forecast Algorithms 138 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon StatEnsem At least 2 times Ensemble of all Yes AutoGluon all MASE (Mean Automated Ensemble No Ensembler ble the statistic Supported Absolute without (MASE) forecast al horizon models(on Stats Model Scaled need Error) for ly) in the AutoGluon model library eto produce forecasts . manual model assignmen t/ selecti on. Forecast Algorithms 139 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast
supplychain-ug-038	supplychain-ug.pdf	38	StatEnsem At least 2 times Ensemble of all Yes AutoGluon all MASE (Mean Automated Ensemble No Ensembler ble the statistic Supported Absolute without (MASE) forecast al horizon models(on Stats Model Scaled need Error) for ly) in the AutoGluon model library eto produce forecasts . manual model assignmen t/ selecti on. Forecast Algorithms 139 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon StatEnsem At least 2 times Ensemble of all Yes AutoGluon all RMSE (Root Automated Ensemble No Ensembler ble the statistic Supported Mean without (RMSE) forecast al horizon models(on Stats Model Squared need Error) for ly) in the AutoGluon model library eto produce forecasts . manual model assignmen t/ selecti on. Forecast Algorithms 140 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Model(s) AutoGluon StatEnsem At least 2 times Ensemble of all Yes AutoGluon all WCD (Weighted Automated Ensemble No Ensembler ble the statistic Supported Cumulativ without (WCD) forecast al horizon models(on Stats Model e need Deviation for ly) in the AutoGluon model library eto produce forecasts . manual model assignmen t/ selecti on. Forecast Model(s) AWS Supply Ensembler Chain AutoML At least 2 times the forecast horizon Ensemble of all in Not Applicabl AutoML default WQL (Weighted Automated Ensemble Depends on e settings Amazon Forecast AutoML. Quantile Loss) for P10, P50, P90 without need for manual model Selected Models by Ensembler . assignmen t/ selecti on. Forecast Algorithms 141 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized User Guide Scenario( s) the Supports Related / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) model is best suited for Forecast Algorithm CNN- QR At least 4 times CNN- QR Not Applicabl CNN- based WQL (Weighted Best suited the (Convolut e parameter Quantile for Times as Forecast Inputt - Yes/ No? Yes, Past and s Loss) large Future for P10, datasets Related P50, P90 containin Time g Series hundreds of time series. forecast ional horizon Neural Network - Quantile Regressio n) is a machine learning algorithm for time series forecasti ng using causal convoluti onal neural networks (CNNs). Forecast Algorithms 142 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized User Guide Scenario( s) the Supports Related / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) model is best suited for Forecast Algorithm DeepAR + At least 4 times DeepAR + is a Not Applicabl DeepAR default WQL (Weighted Best suited the machine e settings Quantile for Times as Forecast Inputt - Yes/ No? Yes, Past and forecast learning horizon algorithm for time series forecasti ng using recurrent neural networks (RNNs). Loss) large Future for P10, datasets Related P50, P90 containin Time g Series hundreds of time series. Forecast Algorithms 143 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm LightGBM At least 2 times Light Gradient- Not Applicabl LightGBM default WQL (Weighted Best suited No the Boosting e parameter Quantile for forecast Machine horizon (LGBM) s Loss) datasets for P10, where is a tabular machine learning model that uses historica l demand data from past seasons. P50, P90 diﬀerent items share similar demand trends. Less eﬀective on datasets with diverse item character istics and demand patterns. Forecast Algorithms 144 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Prophet At least 4 times Prophet is a Not Applicabl Default Prophet WQL (Weighted Best suited Yes, Past the time e settings Quantile for time and forecast series horizon forecasti Loss) series Future for P10, that Related P50, P90 Time Series have strong seasonal eﬀects and several seasons of historica l data. ng algorithm based on an additive model where non- linear trends are ﬁt with yearly, weekly, and daily seasonali ty. Forecast Algorithms 145 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s
supplychain-ug-039	supplychain-ug.pdf	39	- Yes/ No? Forecast Algorithm Prophet At least 4 times Prophet is a Not Applicabl Default Prophet WQL (Weighted Best suited Yes, Past the time e settings Quantile for time and forecast series horizon forecasti Loss) series Future for P10, that Related P50, P90 Time Series have strong seasonal eﬀects and several seasons of historica l data. ng algorithm based on an additive model where non- linear trends are ﬁt with yearly, weekly, and daily seasonali ty. Forecast Algorithms 145 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Triple Exponenti At least 4 times Exponenti al Not Applicabl Default ETS WQL (Weighted Best suited No al the e Smoothing parameter Quantile for Smoothing forecast (ETS) s Loss) datasets horizon is a for P10, with P50, P90 statistic al model for time series forecasti ng. seasonali ty patterns, computing weighted averages of past observati ons with exponenti ally decreasin g weights. ETS is most eﬀective for time series with fewer Forecast Algorithms 146 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related Times as Forecast Inputt - Yes/ No? model is best suited for than 100 items. Forecast Algorithms 147 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Auto Complex At least 2 times Auto Complex Not Applicabl Default AutoCES WQL (Weighted Best suited No Exponenti the Exponenti e settings Quantile for al forecast al Smoothing horizon Smoothing Loss) complex for P10, seasonal P50, P90 patterns in time series data, including multiple seasonali ty or irregular cycles. (AutoCES) is an advanced variant of exponenti al smoothing , automatic ally adjusts smoothing parameter s, oﬀering accurate forecasts for time series with intricate seasonal Forecast Algorithms 148 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) structure s. User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithms 149 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm ARIMA At least 4 times the ARIMA (Auto- Reg forecast ressive Not Applicabl ARIMA default WQL (Weighted Best suited No e parameter Quantile for s Loss) datasets horizon Integrate for P10, without P50, P90 strong seasonal eﬀects. d Moving Average) is a statistic al model for time series forecasti ng. It combines autoregre ssive, moving average, and diﬀerenc ing component s to Forecast Algorithms 150 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) model trends. User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithms 151 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Seasonal ARIMA At least 2 times SARIMA (Seasonal Not Applicabl Seasonal ARIMA WQL (Weighted Best suited No the Auto- e default Quantile for time forecast Regr horizon essive parameter Loss) series s for P10, with P50, P90 strong seasonal patterns. Integrate d Moving Average) is an extension of ARIMA that includes seasonal component s, It models both non- seaso nal and seasonal trends, ensuring accurate Forecast Algorithms 152 User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) predictio ns for datasets with multiple seasons of historica l data. Forecast Algorithms 153 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario(
supplychain-ug-040	supplychain-ug.pdf	40	seaso nal and seasonal trends, ensuring accurate Forecast Algorithms 152 User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) predictio ns for datasets with multiple seasons of historica l data. Forecast Algorithms 153 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Theta At least 2 times The Theta Not Applicabl Theta method WQL (Weighted Best suited No the model e default Quantile for settings Loss) intermitt for P10, ent P50, P90 demand forecasti ng. forecast is a horizon time series forecasti ng method that combines exponenti al smoothing with a decomposi tion approach to handle trend, seasonali ty, and noise. It uses a linear trend Forecast Algorithms 154 User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) model and non- linear smoothing component s to capture both short- term and long- term patterns, often outperfor ming tradition al methods. Forecast Algorithms 155 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Aggregate - At least 2 times ADIDAaggr egates Not Applicabl ADIDA default WQL (Weighted Best suited No Disaggre the data at e parameter Quantile for gate forecast a higher s Loss) products Intermitt horizon level to for P10, with P50, P90 low or irregular demand, intermitt ent demand. ent Demand Approach (ADIDA) capture broader patterns, then disaggreg ates it for accurate forecasts improves accuracy by reducing noise. Forecast Algorithms 156 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Croston At least 2 times The Croston Not Applicabl Croston default WQL (Weighted Best suited No the method e settings Quantile for Loss) intermitt for P10, ent P50, P90 demand forecasti ng. forecast is horizon designed for intermitt ent demand forecasti ng. It separates demand into two component s the size of non- zero demands and the intervals between them. These component Forecast Algorithms 157 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) s are independe ntly forecaste d and combined. User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithms 158 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Intermitt ent At least 2 times IMAPA is a Not Applicabl IMAPA default WQL (Weighted Best suited No Multiple the forecasti e parameter Quantile for Aggregati forecast ng s Loss) improving on horizon method for P10, accuracy P50, P90 for intermitt ent demand patterns (compared to tradition al methods like exponenti al smoothing ). Predictio n Algorithm (IMAPA) for intermitt ent demand data, where demand is irregular with many zero values. It aggregate s data at multiple levels to capture diﬀerent Forecast Algorithms 159 User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) demand patterns, oﬀering more robust predictio ns for datasets with highly irregular demand compared to methods like Croston. Forecast Algorithms 160 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Moving Average At least 2 times The Moving Not
supplychain-ug-041	supplychain-ug.pdf	41	Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) demand patterns, oﬀering more robust predictio ns for datasets with highly irregular demand compared to methods like Croston. Forecast Algorithms 160 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? Forecast Algorithm Moving Average At least 2 times The Moving Not Applicabl Moving Average WQL (Weighted Best suited No the Average e default Quantile for forecast model parameter Loss) short- horizon forecasts s for P10, term P50, P90 by averaging past data points over a ﬁxed window. forecasts , especiall y in sparse data scenarios . This method performs well on time series with simple trends, providing quick, easy predictio ns without Forecast Algorithms 161 AWS Supply Chain Type Forecast Ensembler Demand History Model(s) in Automated hyper Default Parameter Metric Optimized / Requireme Ensemble s Parameter Algorith nt m Tuning (Yes/ No) User Guide Scenario( s) the Supports Related model is best suited for Times as Forecast Inputt - Yes/ No? requiring complex modeling. Forecast Algorithm Non Parametri At least 4 times NPTS is a Not Applicabl NPTS default WQL (Weighted Best suited No c Time the baseline e parameter Quantile for Series (NPTS) forecast forecasti s Loss) robust horizon ng method for sparse or intermitt ent time series data. It includes variants such as Standard NPTS and Seasonal NPTS. for P10, predictio P50, P90 ns for irregular time series by handling missing data and seasonal eﬀects. It is scalable and eﬀective for irregular demand data. Forecast Algorithms 162 AWS Supply Chain User Guide The following table lists the metrics available in Support Demand Planning forecast models. Metric MAPE WAPE RMSE Metric Descripti on Metric Formula When to use this metric to Link Not Applicable Not Applicable Not Applicable MAPE measures the average magnitude of the errors in a set of forecasts , expressed as a percentage of the actual values. WAPE is a variation of MAPE that considers the weighted contributions of diﬀerent data points. RMSE measures the square root of the average squared diﬀerenc optimize It is commonly used for https:// auto.gluon.ai/ evaluating dev/tutoria the accuracy ls/timeseries/ of predictiv e models, forecasting -metrics. especially in html#auto time series forecasting, gluon.tim eseries.m where all time etrics.MAPE series are treated equal for forecast error evaluation. It is particularly useful when the https:// auto.gluon.ai/ data has varying dev/tutoria importance ls/timeseries/ or when some forecasting observations are more signiﬁcant -metrics. html#auto than others. gluon.tim eseries.m etrics.WAPE RMSE is sensitive to large errors because of the squaring https:// auto.gluon.ai/ dev/tutoria ls/timeseries/ operation, which forecasting Forecast Algorithms 163 AWS Supply Chain Metric Metric Descripti on Metric Formula When to use this metric to Link User Guide es between predicted and actual values. optimize gives more weight to larger errors.In use cases where -metrics. html#auto gluon.tim eseries.m only a few large etrics.RMSE WCD Not Applicable WCD is a measure of cumulative forecast error weighted by a set of predeterm ined weights. Not Applicable mispredictions can be very costly, the RMSE is the more relevant metric. This metric is often used in applications where certain time periods, products, or data points have more importanc e than others, allowing for prioritization in the error analysis. Forecast Algorithms 164 AWS Supply Chain Metric wQL Metric Descripti on Metric Formula When to use this metric to Link User Guide Not Applicable wQL is a loss function that evaluates the performance of a model based on quantiles, with weighted contributions from diﬀerent data points. optimize It’s useful for assessing model https:// auto.gluon.ai/ performance in dev/tutoria scenarios where ls/timeseries/ the importanc forecasting e of diﬀerent -metrics. quantiles (e.g., html#auto 90th percentil gluon.tim e, 50th percentil eseries.m e) or observati etrics.WQL ons varies. It is particula rly useful when there are diﬀerent costs for underpred icting and overpredicting. Forecast Algorithms 165 AWS Supply Chain Metric MASE Metric Descripti on Metric Formula When to use this metric to Link User Guide Not Applicable MASE (Mean Absolute Scaled Error) is a performance metric used to evaluate the accuracy of time series forecasti ng models. It compares the mean absolute error (MAE) of the forecaste d values to the mean absolute error of a naive forecast. optimize MASE is ideal for datasets that are https:// auto.gluon.ai/ cyclical in nature dev/tutoria or have seasonal ls/timeseries/ properties. forecasting For example, -metrics. forecasting for items that are in high html#auto gluon.tim eseries.m demand during etrics.MASE summers and in low demand during winters can beneﬁt from taking into account the seasonal impact. Forecast based on demand drivers To enhance forecast
supplychain-ug-042	supplychain-ug.pdf	42	(Mean Absolute Scaled Error) is a performance metric used to evaluate the accuracy of time series forecasti ng models. It compares the mean absolute error (MAE) of the forecaste d values to the mean absolute error of a naive forecast. optimize MASE is ideal for datasets that are https:// auto.gluon.ai/ cyclical in nature dev/tutoria or have seasonal ls/timeseries/ properties. forecasting For example, -metrics. forecasting for items that are in high html#auto gluon.tim eseries.m demand during etrics.MASE summers and in low demand during winters can beneﬁt from taking into account the seasonal impact. Forecast based on demand drivers To enhance forecast accuracy while conﬁguring your forecast, you can use demand drivers. Demand drivers are related time series inputs that capture product trends and seasons. Instead of depending on historical demand, you can use demand drivers to inﬂuence the supply chain based on various factors. For example, promotions, price changes, and marketing campaigns. Demand Planning supports both historical and future demand drivers. Prequisites to use demand drivers Before ingesting data for demand drivers, make sure that the data meets the following conditions: • Make sure to ingest the demand drivers data in the supplementary_time_series data entity. You can provide both historical and future demand driver information. For information about the data entities that Demand Planning requires, see Demand Planning. Forecast based on demand drivers 166 AWS Supply Chain User Guide If you cannot locate the supplementary_time_series data entity, your instance might be using an earlier data model version. You can contact AWS Support to upgrade your data model version or create a new data connection. • Make sure that the following columns are populated in the supplementary_time_series data entity. • id – This column is the unique record identiﬁer and is required for a successful data ingestion. • order_date – This column indicates the timestamp of the demand driver. It can be both past and future dated. • time_series_name – This column is the identiﬁer for each demand driver. The value of this column must start with a letter, should be 2–56 characters long, and may contain letters, numbers, and underscores. Other special characters are not valid. • time_series_value – This column provides the data point measurement of a particular demand driver at a speciﬁc point in time. Only numerical values are supported. • Select a minimum of 1 and a maximum of 13 demand drivers. Make sure that the aggregation and ﬁlling methods are conﬁgured. For more information on ﬁlling methods, see Demand drivers data ﬁlling method. You can modify the settings at any time. Demand Planning will apply the changes in the next forecast cycle. The following example illustrates how a Demand Plan is generated when the required demand driver columns are ingested in the supplementary_time_series data entity. Demand Planning recommends providing both historical and future demand driver data (if available). This data helps the learning model to learn and apply the pattern to the forecast. The following example illustrates how you can set up some common demand drivers in your dataset. Prequisites to use demand drivers 167 AWS Supply Chain User Guide When you provide leading indicators, Demand Planning highly recommends that you adjust the time series date. For example, say that a particular metric serves as a 20-day leading indicator with a 70% conversion rate. In this case, consider shifting the date in the time series by 20 days and then applying the appropriate conversion factor. While the learning model can learn patterns without such adjustments, aligning leading indicator data with corresponding outcome is more eﬀective in pattern recognition. The magnitude of the value plays a signiﬁcant role in this process, enhancing the model's ability to learn and interpret patterns accurately. Demand driver conﬁguration To use demand drivers, you must conﬁgure them. You can conﬁgure demand drivers only when you've ingested data in the supplementary_time_series data entity. Note If you don't conﬁgure the demand drivers, you can still generate a forecast. However, Demand Planning won't use the demand drivers. Demand drivers data ﬁlling method A ﬁlling method represents (or "ﬁlls") missing values in a time series. Demand Planning supports the following ﬁlling methods. The ﬁlling method that Demand Planning applies depends on the location of the gap in the data. • Back ﬁlling – Applied when the gap is between a product's earlier recorded date and the last recorded date. • Middle ﬁlling – Applied when the gap is between the last recorded data point for a given product and the global last recorded date. • Future ﬁlling – Applied when the demand driver has at least one data point in the future and there is a gap in the future time horizon. Demand driver conﬁguration 168 AWS Supply Chain User Guide Demand Planning utilizes the last 64 data points from the supplementary_time_series data entity corresponding to the
supplychain-ug-043	supplychain-ug.pdf	43	the data. • Back ﬁlling – Applied when the gap is between a product's earlier recorded date and the last recorded date. • Middle ﬁlling – Applied when the gap is between the last recorded data point for a given product and the global last recorded date. • Future ﬁlling – Applied when the demand driver has at least one data point in the future and there is a gap in the future time horizon. Demand driver conﬁguration 168 AWS Supply Chain User Guide Demand Planning utilizes the last 64 data points from the supplementary_time_series data entity corresponding to the demand driver for consideration. Demand Planning supports zero, median, mean, maximum, and minimum options for all three ﬁlling methods. The following example illustrates how demand drivers handle missing data when data is ingested to the price column in the supplementary_time_series data entity for Product 1, that includes both history and future data. Aggregation method Demand Planning uses the aggregation method to facilitate the integration of demand drivers at various levels of granularity by consolidating data over speciﬁc periods and granularity levels. Time period aggregation – For example, when the Inventory demand driver is available at daily level but the forecast is at weekly level, demand planning will apply the aggregation method conﬁgured under the demand plan settings for inventory to use the information for forecasting. Demand driver conﬁguration 169 AWS Supply Chain User Guide Granularity level aggregation – Here is an example of how demand planning uses the granularity level aggregation. out_of_stock_indicator is available daily at product-site level but forecast granularity is only available at product level. Demand Planning will apply the aggregation method conﬁgured under the demand plan settings for this demand driver. Demand driver recommendations While conﬁguring aggregation and ﬁlling methods for demand drivers, a general guideline is to assign mean aggregation for both boolean and continuous data types. To ﬁll a missing value, use zero ﬁlling for boolean data while mean ﬁlling is suitable for continuous data. Note that the choice of aggregation and ﬁlling method conﬁguration depends on the data characteristics and assumptions about missing values. Here is an example. Demand driver recommendations 170 AWS Supply Chain User Guide Demand Planning recommends adjusting the demand driver conﬁguration to best suit your dataset needs. The demand driver conﬁguration will impact the forecast accuracy. On the AWS Supply Chain web application, under Demand planning, Overview, you will view the impact scores associated with demand drivers, aggregated at the demand plan level. These impact scores measure the relative inﬂuence of demand drivers on forecast. A low impact score does not indicate that the demand driver has a minimal eﬀect on forecast values. Instead, it suggests that its inﬂuence on forecast value is comparatively lower than the other demand drivers. When the impact score is zero under certain circumstances, it should be interpreted as the demand driver has no impact on the forecast values. Demand Planning recommends revisiting the aggregation and ﬁlling method conﬁguration applied to that particular demand driver. Product lineage Product lineage refers to the relationship established between products and their previous versions or alternate products. Demand Planning uses product lineage information to create surrogate histories for these products, which serve as forecast inputs for demand predictions. Product lineage supports the following patterns: • A single product has one lineage or alternate product = 1:1 The following example shows an 1:1 scenario. Product lineage 171 AWS Supply Chain User Guide • A single product has more than one product as lineage or alternate = Many:1 Demand Planning supports product lineage relationship modeled as both chain or ﬂattened methods. • Chain format – You can directly model lineage relationships like A to B and B to C. In the following example. Demand Planning will model the lineage relationship as A to B, B to C, and A to C. Predecessor Successor A B B C The following example shows an Many:1 scenario - Chain format • Flattened format – Demand Planning will continue to support lineage information in A to B and A to C format. In the following example, Demand planning will model the lineage relationship as A to B and A to C. B to C is not considered. Product lineage 172 AWS Supply Chain User Guide Predecessor Successor A A Note B C Chain format only supports 6 levels of lineage relationship. If you have more than 6, you can use ﬂattened format to model the lineage relationship. The following example shows an Many:1 scenario - Flattened format • A single product can be lineage or alternate for more than 1 product = 1 : Many To enable the product lineage feature, you can deﬁne the lineage relationship for the diﬀerent versions of the products or alternates/substitutes in the product_alternate data entity. For more information, see
supplychain-ug-044	supplychain-ug.pdf	44	not considered. Product lineage 172 AWS Supply Chain User Guide Predecessor Successor A A Note B C Chain format only supports 6 levels of lineage relationship. If you have more than 6, you can use ﬂattened format to model the lineage relationship. The following example shows an Many:1 scenario - Flattened format • A single product can be lineage or alternate for more than 1 product = 1 : Many To enable the product lineage feature, you can deﬁne the lineage relationship for the diﬀerent versions of the products or alternates/substitutes in the product_alternate data entity. For more information, see Demand Planning. If your instance was created on or after September 11, 2023, you will see product_alternate data entity in the AWS Supply Chain data Connection module. If your instance was created before Product lineage 173 AWS Supply Chain User Guide September 11, 2023, create a new data connection to enable the product_alternate data entity for ingestion. To ingest data into the product_alternate data entity, follow the guidelines below: • product_id – The primary product to create the forecast. • alternative_product_id – Previous version of the product or alternate/substitute product. To consider multiple alternative_product_id for a single product_id, enter them in separate rows. • Demand Planning will consider the data ONLY when the values are provided in the following format. • alternate_type is similar_demand_product. • status is active. • alternate_product_qty_uom is the text percentage. • alternate_product_qty – Enter the proportion of history of the alternate product you want to use for forecasting new products in the alternate_product_qty data ﬁeld. For example, if it is 60%, enter 60. When you have multiple alternative_product_id for a single product_id, the alternate_product_qty does not have to add up to 100. • The eﬀ_start_date and eﬀ_end_date data ﬁelds are required. However, you can leave this ﬁeld empty and Demand Planning will auto-ﬁll with 1000 and 9999 years respectively. When the forecast is created using product lineage data, you will see an indicator Forecast is based on alternate product's history on the Demand Planning page when you ﬁlter by product ID. The following table shows an example of how Demand Planning Product lineage feature works based on the data ingested into the product_alternate data entity. Example Example Example Example Example Example Example Example Example Example Example ColumnRequired 11 10 9 8 7 6 5 4 3 2 1 or Optional product_i d RequiredProduct Product 123 Product 123 Product 123 Product 123 Product 123 Product 123 Product 123 Product 123 Null 123 Product lineage Product 123 174 AWS Supply Chain User Guide Example Example Example Example Example Example Example Example Example Example Example ColumnRequired 11 10 9 8 7 6 5 4 3 2 1 or Optional RequiredProduct Null alternati ve_produc XYZ Product XYZ Product XYZ Product XYZ Product XYZ Product XYZ Product XYZ Product XYZ Null Product XYZ t_id alternate _type RequiredSimilar_D Null Similar_D or a emand_Pro emand_Pro Similar_D emand_Pro Similar_D emand_Pro Similar_D emand_Pro Similar_D emand_Pro Similar_D emand_Pro Similar_D emand_Pro Similar_D emand_Pro Similar_D emand_Pro duct duct diﬀerent duct duct duct duct duct duct duct duct value status* Requiredactive active active inactiveactive active Null active active active active Required100 alternate _product_ qty 60 100 100 Null 100 100 100 100 100 60 alternate _product_ Requiredpercentag e percentag e percentag e percentag e percentag e Null or a percentag e percentag e percentag e percentag e percentag e qty_uom diﬀerent value eﬀ_start _date Required2023-01-0 1 2023-01-0 1 2023-01-0 1 2023-01-0 1 2023-01-0 1 2023-01-0 1 Null 2023-01-0 1 00:00:00 00:00:00 00:00:00 00:00:00 00:00:00 00:00:00 00:00:00 2023-01-0 1 Null 2023-01-0 1 00:00:00 00:00:00 eﬀ_end_d ate Null 2025-12-3 2025-12-3 2025-12-3 2025-12-3 2025-12-3 2025-12-3 2025-12-3 Required2025-12-3 1 1 1 1 1 1 1 1 23:59:59 23:59:59 23:59:59 23:59:59 23:59:59 23:59:59 23:59:59 23:59:59 Null 2025-12-3 1 23:59:59 Product lineage 175 AWS Supply Chain User Guide Example Example Example Example Example Example Example Example Example Example Example ColumnRequired 11 10 9 8 7 6 5 4 3 2 1 or Optional NA Expected behavior 100% of Invalid mapping Invalid mapping Inactive mapping. Invalid mapping Invalid mapping Invalid mapping Ingestion will Ingestion will Invalid mapping Ingestion will product since since since since since fail. fail. since fail. XYZ's alternati alternate alternate alternate status history ve_produc _type _product_ is _product_ from t_id is is 1/1/2023 not qty is qty_uom missing. is to missing. 'similar_ missing. missing or not percentag e. 31/12/202 demand_pr oduct'. 5 will be used to forecast product 123. product_i d and alternati ve_produc t_id are missing. Product lineage 176 AWS Supply Chain User Guide Example Example Example Example Example Example Example Example Example Example Example ColumnRequired 11 10 9 8 7 6 5 4 3 2 1 or Optional NA NA NA NA NA NA NA NA Demand Planning Demand Planning NA will will auto- auto- popu popu late late the the
supplychain-ug-045	supplychain-ug.pdf	45	ve_produc _type _product_ is _product_ from t_id is is 1/1/2023 not qty is qty_uom missing. is to missing. 'similar_ missing. missing or not percentag e. 31/12/202 demand_pr oduct'. 5 will be used to forecast product 123. product_i d and alternati ve_produc t_id are missing. Product lineage 176 AWS Supply Chain User Guide Example Example Example Example Example Example Example Example Example Example Example ColumnRequired 11 10 9 8 7 6 5 4 3 2 1 or Optional NA NA NA NA NA NA NA NA Demand Planning Demand Planning NA will will auto- auto- popu popu late late the the Demand Planning will auto- popu late the eﬀ_start eﬀ_end_d eﬀ_start _date to ate to year year 1000. 9999. This This _date to year 1000 and scenario scenario is is eﬀ_end_d ate valid valid and and data ingestion ingestion will not fail. will not fail. to year 9999. This scenario is valid and ingestion will not fail. The following example explains how Demand Planning will interpret when the status is set as inactive and the product lineage is in chain format. Product lineage 177 AWS Supply Chain User Guide Column Column A B C B C D Status Active Inactive Active Demand planing considers the status of the ﬁrst root and child mapping as the status for the entire chain. A to B Active A to C Active A to D Active B to C Inactive B to D Inactive C to D Active Product lifecycle Product lifecycle describes the lifecycle of a product from introduction to End of Life (EoL). AWS Supply Chain supports forecasting products through it's lifecycle. To enable the Product lifecycle feature, populate the product_introduction_day and discontinue_day columns in the Product data entity. Demand Planning uses the data from these columns to create forecast for a product when the product is active. For more information data entities, see Data entities and columns used in AWS Supply Chain. To enable product lifecycle, make sure the columns id, description, product_available_day, discontinue_day, and is_deleted are populated in the Product data entity. The example below displays how Demand Planning works when data is ingested in the Product data entity. Product lifecycle 178 AWS Supply Chain User Guide Column name Required for Required for Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6 Scenario 7 Data Lake Demand Planning id Yes Yes Product12 Product12 Product12 Product12 Product12 Product12 Product12 3 3 3 3 3 3 3 descripti on Yes Yes Bottle Bottle Bottle Bottle Bottle Bottle Bottle product_a vailable_ No day discontin ue_day No is_delete d No NA Expected behavior No May 1, 2023 May 1, 2023 May 1, 2023 Null Null May 1, 2022 May 1, 2022 No Null December 31, December 31, Null Null May 1, 2023 Past 2023 2023 No No No Yes No Null No No NA Forecast will be Forecast will be Forecast will Forecast will be Assumed that Forecast will be In case of created created not be created the created conﬂict starting starting created for the product for 3 3 since entire is months prior months prior the product planning horizon. active. (or as (or as is one day (May 1). conﬁgure conﬁgure considere d) d) d prior prior inactive. to to May 1, May 1, 2023 to the end 2023 until the between is_delete d and discontin ue_day, is_delete d is considere d. Product lifecycle 179 AWS Supply Chain User Guide Column name Required for Required for Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6 Scenario 7 Data Lake Demand Planning of the discontin planning horizon ue date since there is no (or as conﬁgure d). discontin ue date. For information on how to conﬁgure Product lifecycle, see Create your ﬁrst demand plan. Under Demand Planning settings, you can set your forecast start date depending on the product_available_day in the Product data entity. By default, the forecast starts on the product_available_day. Period refers to the time interval set under Scope (daily, weekly, monthly, or yearly). You can adjust the start date to optimize inventory management. Similar to start date, you can set an end date for your forecast depending on the product_discontinue_day in the Product data entity. By default, forecast will end on the product_discontinue_day. You can adjust the end date to prevent inaccurate forecasting beyond the product shelf life and avoid excess inventory cost. Enter zero if you want the forecast to match the product_available_day and product_discontinue_day. This global setting will apply to all eligible products. When product_available_day and product_discontinue_day are not available, the forecast is created for the entire planning horizon. You can also conﬁgure your system to initialize forecast values for products without historical data or alternate product links. The default value is zero. You can also set the period until which your system
supplychain-ug-046	supplychain-ug.pdf	46	By default, forecast will end on the product_discontinue_day. You can adjust the end date to prevent inaccurate forecasting beyond the product shelf life and avoid excess inventory cost. Enter zero if you want the forecast to match the product_available_day and product_discontinue_day. This global setting will apply to all eligible products. When product_available_day and product_discontinue_day are not available, the forecast is created for the entire planning horizon. You can also conﬁgure your system to initialize forecast values for products without historical data or alternate product links. The default value is zero. You can also set the period until which your system should use the initialize product forecast value based on the time interval set under Scope (daily, weekly, monthly, or yearly). The default value is three periods. This global setting will apply to all eligible products at the intersection of site, customer and channel dimensions, if they are selected as additional forecast granularity. For example, when forecast is set to weekly with Product lifecycle 180 AWS Supply Chain User Guide an initialized value of 10 for 12 periods, and the start forecast is set to three periods before the product_available_day, for a Product X with October 2, 2023 product_available_date, the initialized value of 10 will be applied for each week from September 11, 2023 to December 3, 2023. To change the product_available_day and product_discontinue_day, update the Product data entity in AWS Supply Chain data lake. You can also update the forecast start and stop date. When you change the initialization value and period settings, the changes are applied to all eligible products, including those which were initialized with a diﬀerent value in the previous planning cycles. All the updates are applied to the next forecast creation cycle. Manage demand plans After the forecast is generated, choose Demand Planning, and then choose Manage Demand Plan. On the Demand Planning page, you can view the overall inﬂuence factors used in generating the forecast and the accuracy metrics of the forecast. You can also view the current demand plan. Topics • Overview • Demand plan • Forecast lock Overview Note You can only view the Overview page after the forecast is generated for the ﬁrst time. The Overview tab provides the following information. • Overall Inﬂuence Factors – Indicates the impact score of product metadata attributes and demand drivers (if any), used to generate forecast in the current planning cycle. You can view the inﬂuence factors after the ﬁrst successful forecast generation. A negative value indicates the attributes caused the forecast to go down and vice versa. A zero value indicates that the attribute has no inﬂuence on the forecast result. For information on forecast based on demand drivers, see Forecast based on demand drivers. Manage demand plans 181 AWS Supply Chain User Guide • Accuracy Metrics – After you update the dataset (outbound_order_line) that contains the actual demand for the forecast period, choose Recalculate. You can view the accuracy metrics for the latest demand plan under the Demand Plan tab. Accuracy metrics measure how the accuracy of the current demand plan aligns with the actual demand. Accuracy metrics are available at plan (aggregate) and granular lowest level during forecast generation. The Overview page displays the aggregate level metrics and under Accuracy Metrics, you can choose Download to download the granular metrics. The following are the formulas used to calculate the metrics displayed on the web application. • Mean Absolute Percentage Error (MAPE) – MAPE takes the absolute value of the percentage error between observed and predicted values for each unit of time and averages those values. The formula at granular and plan level is below: A MAPE less than 5% indicates the forecast is acceptably accurate. A MAPE greater than 10% but less than 25% indicates low, but acceptable accuracy, and MAPE greater than 25% indicates very low accuracy and the forecast is not acceptable. • Weighted Average Percentage Error (WAPE) – WAPE measures the overall deviation of forecasted values from observed values. WAPE is calculated by taking the sum of observed values and the sum of predicted values, and calculating the error between those two values. A lower value indicates a more accurate model. The formula at granular and plan level is below: A WAPE less than 5% is considered as acceptably accurate. A WAPE greater than 10% but less than 25% indicates low, but acceptable accuracy and WAPE greater than 25% indicates very low accuracy. See the following example: Overview 182 AWS Supply Chain User Guide The metrics are not calculated when actual is zero or null. When a new forecast is generated subsequently, the previous reported metrics will no longer be available on the web application. Make sure the latest outbound_order_line dataset is updated and choose Recalculate to view the updated metrics. The accuracy metrics reﬂect the accuracy of the
supplychain-ug-047	supplychain-ug.pdf	47	below: A WAPE less than 5% is considered as acceptably accurate. A WAPE greater than 10% but less than 25% indicates low, but acceptable accuracy and WAPE greater than 25% indicates very low accuracy. See the following example: Overview 182 AWS Supply Chain User Guide The metrics are not calculated when actual is zero or null. When a new forecast is generated subsequently, the previous reported metrics will no longer be available on the web application. Make sure the latest outbound_order_line dataset is updated and choose Recalculate to view the updated metrics. The accuracy metrics reﬂect the accuracy of the current demand plan for all time periods that have an actual demand value in the current executed forecast. For example, if your current planning cycle has forecast from January to December 2023 with monthly forecasts and you updated the actual data for January 2023, accuracy metrics will be computed for January 2023. Similarly, if your current planning cycle has forecast from January to December 2023 with monthly forecasts and you updated the actual data for January 2023 and February 2023, accuracy metrics will be computed for January 2023 and February 2023. The Demand Planning web application will display the aggregated metric for Jan-Feb-2023 and the export ﬁle will display the granular details. Note When you modify the Time interval or Hierarchy conﬁguration and regenerate the forecast, the accuracy metrics will not be displayed since the accuracy metric values are not relevant. Demand pattern You can expand the individual metrics to view the demand characteristics such as Smooth Demand, Intermittent Demand, Erratic Demand, and Lumpy Demand. The segments are derived based on the actual demand used in the last forecast. When one or more of the four segments are missing in the Demand Planning web application, it indicates that the Demand Planning web application could not ﬁnd any product aligned with the patterns associated with the missing segments. Overview 183 AWS Supply Chain User Guide The following intermediate results are calculated: Note Records with zero demand are not considered for ADI and CV² computation. • Average Demand Interval (ADI) – Represents the average time between consecutive demands. ADI = total number of periods / number of demand buckets • Squared Coeﬃcient of Variation (CV²) – Measures the variability in demand quantities. CV² = (standard deviation of a population / average value of the population)² The following cut-oﬀs are applied to derive the segments: • Smooth Demand (ADI less then 1.32 and CV² less than 0.49) is highly regular in time and quantity, making it easy to forecast with low error margins. • Intermittent Demand (ADI greater than or equal to 1.32 and CV² lesser than 0.49) exhibits little variation in quantity but high variation in demand interval, leading to higher forecast error margins. • Erratic Demand (ADI less then 1.32 and CV² greater than or equal to 0.49) has regular occurrence in time but high variations in quantity, resulting in shaky forecast accuracy. • Lumpy Demand (ADI greater than or equal to 1.32 and CV² greater than or equal to 0.49) is characterized by large variations in both quantity and time, making it unforecastable. Forecast validation By default, forecast validation is enabled. To make sure the forecast generated is accurate, Demand Planning will monitor and update you on the forecast quality or accuracy. If Demand Planning determines the forecast requires additional validation, Demand Planning will delay publishing the forecast and you will see a message that displays the date and time when the forecast will be published on the AWS Supply Chain web application. You can also opt-out and Demand Planning will not monitor your forecast. For more information on how to opt-out, see Opt-out preference. You can view the last published demand plan in read-only mode. Overview 184 AWS Supply Chain Lags User Guide Lags represent the time interval between when the forecast was created and the actual forecast was realized. You can conﬁgure up to three forecast lags when you conﬁgure demand plan. For more information, see Create your ﬁrst demand plan. The forecast accuracy metrics displays the analysis based on the lag intervals deﬁned. Forecasts for the deﬁned lags are generated for every planning cycle and the accuracy metrics can only be evaluated after the corresponding number of planning cycles. For example, if you choose lag six, accuracy metrics for lag six forecast will be calculated after six planning cycles. Note When you change the lag conﬁguration, the drop-down values displayed are the newly selected lags. Choose Refresh Metrics to view the latest metrics. When you change the time interval (daily/weekly/monthly/yearly), or hierarchy (product/site/customer/channel) granularity, the previous lag metrics will no longer be available when you choose Refresh Metrics. The recalculation results will display the latest demand planning cycle as the only cycle in history. Choose Export Metrics
supplychain-ug-048	supplychain-ug.pdf	48	metrics can only be evaluated after the corresponding number of planning cycles. For example, if you choose lag six, accuracy metrics for lag six forecast will be calculated after six planning cycles. Note When you change the lag conﬁguration, the drop-down values displayed are the newly selected lags. Choose Refresh Metrics to view the latest metrics. When you change the time interval (daily/weekly/monthly/yearly), or hierarchy (product/site/customer/channel) granularity, the previous lag metrics will no longer be available when you choose Refresh Metrics. The recalculation results will display the latest demand planning cycle as the only cycle in history. Choose Export Metrics to download a detailed ﬁle that includes granular data corresponding to the aggregated metrics displayed on the web application. The downloaded ﬁle will contain the following information: • Timestamp - Forecasted Period, Forecast Creation Date, Last Actual Period, Lag • XYZ segment (smooth, intermittent, erratic or lumpy) • Granularity - Product/site/customer/channel as conﬁgured • Baseline forecasts - P10, P50 and P90 • Actual demand • Metrics - Bias Units, Bias %, MAPE, SMAPE (at granular level, MAPE and WAPE are the same) Overview 185 AWS Supply Chain Demand plan User Guide After the forecast is generated, you can review the forecast values on the Demand Plan tab. The Enterprise demand plan is a single workbook that serves as a collaborative platform to work together. It provides a centralized location for you to consolidate and synchronize the forecasting eﬀort. The Demand Plan table displays the following information: • Forecasted Demand – Displays the system generated forecast and includes the following three values: • Lower Bound – Forecast prediction that is typically higher than the actual demand around 90 percent of the time. • Median Demand – Forecast prediction that is typically higher than the actual demand 50 percent of the time (central estimate). • Upper Bound – Forecast prediction that is typically higher than the actual demand 10 percent of the time. Note Lower and Upper Bound information is only displayed when a product_id is selected. Median Demand is displayed at both aggregate level and when a single product id is selected. • Demand Plan – Median Demand is replicated in this row to allow for overrides. • Actual Demand – Displays demand history for the current and prior years. When comparing historical data on a weekly basis, Demand Planning will reference the closest Monday in the previous year. This is because Demand Planning considers Monday as the starting day of the week. Due to variations between years and leap years, the corresponding week in the previous year might not have the exact same date. For example, to compare if historical sales data for the week of 6/3/2023 is available, which is a Monday, Demand Planning will reference the week with the closest Monday in the previous year, which is 7/2/2022. • Prior Forecast Versions – The last published demand plan displays. This will be blank during the ﬁrst forecast creation because no history is available. • Lifecycle and Events – Displays the products in the demand plan that are New Product Introductions (NPI) or products that are nearing End of Life (EoL). When you hover over the NPI Demand plan 186 AWS Supply Chain User Guide or EoL icons, when more than one product is selected, you can view the number of products and the list of products. When only one product is selected, you can view the product metadata. , product available day in case of NPI, discontinue day in case of EoL, and forecast start and stop date. Note You will only see the number of products that are new or nearing EoL listed when the product category is set to all or when a higher level in product hierarchy is selected. You can use the Graph toggle button to hide or show the graph view. You can hide or show the speciﬁc value by choosing the eye icon. When you ﬁlter by products, you can hover over the i help icon to view the product description, unit of measure (UoM), product available date, and discontinue date. Viewing the forecast To view the forecast, complete the following steps: 1. On the Enterprise demand plan page, you can see the timestamp of the forecast generated. If the Enterprise demand plan is in active state, you can use the ﬁlters and make adjustments. 2. On the Enterprise demand plan page, under All, choose Change category/product to change the generated forecast view. By default, the forecast displayed represents the total forecast demand for all products within the deﬁned scope or time horizon. 3. On the Select Category/Product page, you can select the product from the list or use the search box to search for a particular product by Product ID or Description. 4. Choose Apply. You can now view the ﬁltered
supplychain-ug-049	supplychain-ug.pdf	49	the timestamp of the forecast generated. If the Enterprise demand plan is in active state, you can use the ﬁlters and make adjustments. 2. On the Enterprise demand plan page, under All, choose Change category/product to change the generated forecast view. By default, the forecast displayed represents the total forecast demand for all products within the deﬁned scope or time horizon. 3. On the Select Category/Product page, you can select the product from the list or use the search box to search for a particular product by Product ID or Description. 4. Choose Apply. You can now view the ﬁltered forecast for the selected product or category. Note If you had chosen optional hierarchies during forecast conﬁguration, the summary box will display the count of site, customer, and channel the selected product is sold. 5. Under Reﬁne your search, if you chose optional hierarchies during forecast conﬁguration, you can ﬁlter for Site, Channel, or Customer to further reﬁne your forecast. For example, if you chose Site and Channel hierarchy during forecast conﬁguration, the ﬁlters for Site and Channel will be available on the Demand Plan page. Demand plan 187 AWS Supply Chain User Guide 6. In the Time interval dropdown list, select the time interval to view the forecast. You can use this ﬁlter to adjust the time hierarchy and view the forecast in both table and graph form. The lowest value corresponds to the forecast granularity time interval setting. For example, if the time interval is Weekly, you can view the forecast at Weekly, Monthly and Yearly. You can also use the Viewing window start and Viewing window end to narrow down the period that you want to view in the forecast, both in table and graph view. You can view the historical sales for 28 days, 52 weeks, 48 months, and 10 years. Time interval example 1 Demand Plan is generated at daily time-intervals per conﬁguration. You can view the Demand Plan at weekly time interval by selecting the option on the Time Interval ﬁlter on the Demand Plan page. The system will aggregate values into weeks with Monday as the starting day of the week. You can also view the demand plan in monthly time interval by using the Time Interval ﬁlter and selecting the monthly option. System will aggregate values into Gregorian calendar month with start day as 1, because demand plan is available at daily granularity. Time interval example 2 Demand plan is generated at weekly time-interval per conﬁguration. You can view the Demand plan at monthly time interval by selecting the Time Interval ﬁlter. The time boundaries for month will not be strict Gregorian calendar month. Demand plan 188 AWS Supply Chain Adding an override User Guide This section describes how to manually edit the forecast to override the projected demand. Note Manual forecast overrides from one planning cycle are automatically saved and reapplied on the next planning cycle. 1. Under Demand Plan, you can add overrides on the graph by moving the dot to the desired value or update the values directly on the Demand Plan row in the table. 2. On the Edit Quantity page, under Change, select if you want to increase, decrease, or ﬁxed amount the demand. 3. Choose Bulk edit to bulk edit the forecast and add an override. The Edit your forecast page appears. 4. Under Change, select the dropdown to increase or decrease the demand, or enter a value. 5. Under Reason Code, select from one of the options between Promotion, Holiday, Seasonal, New Product, Product Rampdown or Others. The reason code is mandatory to successfully process the override. It is optional to add more descriptive notes to a forecast override. 6. Choose Save and Update. When you create an override, the impact can be viewed throughout the relevant levels of hierarchies. You can create many overrides but only the last override will be considered. After an override is created, a clock icon appears under Demand Plan. When you choose the clock icon, you can view the most recent change in the planning cycle. Choose View more changes to view past updates. 7. To make multiple overrides at the same time, from the Edit Quantity, choose Go to bulk editing. You can also choose Bulk Edit against Demand Plan. Note You can bulk edit only from the table. 8. On the Edit your forecast page, you can select all check boxes or a check box for each time period that you want to update, and then enter the updates. Demand plan 189 AWS Supply Chain 9. Choose Save and Update. The Forecasted Demand is updated. Exporting data plan ﬁles User Guide You can export Demand Plan, Forecast Demand, Prior Forecast Versions, and Actual Demand History from Demand Planning as individual .csv ﬁles. Note The exported .csv ﬁle
supplychain-ug-050	supplychain-ug.pdf	50	to bulk editing. You can also choose Bulk Edit against Demand Plan. Note You can bulk edit only from the table. 8. On the Edit your forecast page, you can select all check boxes or a check box for each time period that you want to update, and then enter the updates. Demand plan 189 AWS Supply Chain 9. Choose Save and Update. The Forecasted Demand is updated. Exporting data plan ﬁles User Guide You can export Demand Plan, Forecast Demand, Prior Forecast Versions, and Actual Demand History from Demand Planning as individual .csv ﬁles. Note The exported .csv ﬁle will contain the entire demand plan, despite which ﬁlters were active on the Demand Planning page at the time of export. To export the data plan, complete the following steps: 1. On the Enterprise demand plan page, select the vertical ellipsis. 2. Choose Export Data Plan. 3. On the Export page, select the required data you would like to download. 4. Choose Export. The ﬁle is downloaded on your local computer. Demand plan 190 AWS Supply Chain User Guide Importing forecast overrides You can use the import forecast overrides option to import the forecast overrides using a .csv ﬁle. To upload the forecast overrides through a .csv ﬁle, complete the following steps: 1. On the Enterprise demand plan page, select the vertical ellipsis. 2. Choose Import Forecast Overrides. The Import Forecast Overrides page appears. 3. Under Upload ﬁles, choose Download CSV template to download the .csv ﬁle you need to use to add the override values. The .csv ﬁle will contain the headers from the dataset you used to generate the forecast. The .csv ﬁle can only contain upto 1000 rows and the ﬁle size should be within 5 MB. 4. After the .csv ﬁle is updated, you can drag and drop the ﬁles or choose select ﬁles to add the ﬁle. 5. Choose Upload overrides. If the upload fails, check the following: • Make sure the required ﬁelds override_start_date, override_end_date, value, and reason_code are populated. • The supported reason codes are Promotion Holiday, Seasonal, New Product, Product Rampdown, and Others. Demand plan 191 AWS Supply Chain User Guide • Make sure the override_start_date and override_end_date is the ﬁrst day of the week or month depending on your conﬁguration. 6. Under Import Forecast Overrides Status, you will see the status of all the forecast overrides you uploaded. You can ﬁlter the forecast override status by Data Uploaded, User ID, or upload status. Demand Plan scheduler Schedulers in Demand Planning determine when forecasts are generated and demand plans are ﬁnalized. Schedulers can be conﬁgured to operate automatically at set time intervals (auto schedulers) or triggered manually. Auto-schedulers ensure that the planning process runs smoothly and consistently accordingly to predeﬁned timelines, while manual schedulers gives you the ﬂexibility to initiate forecast refreshes and ﬁnalize demand plans. • Manual refresh and release – Make sure you choose Manual under Demand Plan Scheduler when you conﬁgure demand planning. To start a forecast refresh, on the Demand Plan page, select the three dots on the top-right, and choose Generate Forecast. Select Finalize demand plan, if the demand plan is ﬁnal and ready to be released to downstream processes. Once the demand plan is ﬁnal, the information is published to the Forecast data entity in Data Lake and to Amazon S3. The status on the demand plan page for this plan is changed to Published. You can view the Amazon S3 link under Settings > Organization, Demand Planning, Publish Demand Plans. You can see the Generate forecast button to start the next planning cycle. When the Finalize demand plan is not selected, Demand Planning will publish the forecast as an interim version to the Forecast data entity in Data Lake. The status is changed to Closed. You can see the Generate forecast button to start the next planning cycle. Demand planning will initiate a new forecast as set in the demand planning conﬁguration page and will use the same start date as the previous plan. • Automatic refresh and release – Make sure you choose Auto under Demand Plan Scheduler when you conﬁgure demand planning. For more information, see Create your ﬁrst demand plan. Demand plan 192 AWS Supply Chain Forecast lock User Guide You can use the forecast lock feature to lock speciﬁc periods in your forecast to prevent any further edits or adjustments. To conﬁgure the forecast lock, enter a number between zero and time horizon -1 in the Demand Plan settings page to lock the ﬁrst x forecast period. The default value is 0, indicating no periods are locked. The forecast lock is not applied to the initial forecast but will take eﬀect from the second demand planning cycle carrying over the ﬁnalized values from the previous demand plan. In the Demand Plan,
supplychain-ug-051	supplychain-ug.pdf	51	192 AWS Supply Chain Forecast lock User Guide You can use the forecast lock feature to lock speciﬁc periods in your forecast to prevent any further edits or adjustments. To conﬁgure the forecast lock, enter a number between zero and time horizon -1 in the Demand Plan settings page to lock the ﬁrst x forecast period. The default value is 0, indicating no periods are locked. The forecast lock is not applied to the initial forecast but will take eﬀect from the second demand planning cycle carrying over the ﬁnalized values from the previous demand plan. In the Demand Plan, locked periods are indicated by a lock icon. The change history icon will display the reason code PLAN_LOCKED for audit purpose at the most granular level. Once the forecast period is locked, the lock applies to all products within that timeframe. When the forecast granularity is changed, forecast overrides from the prior planning cycles are not carried over to the current planning cycle. The prior forecast and accuracy metrics will also not display any data in the Demand plan and any prior forecast locks are no longer valid. It takes two consecutive forecast executions in the modiﬁed granularity to apply a new forecast lock. You can unlock forecast periods by setting the conﬁguration to zero and starting a new forecast. The example below displays how intra-cycle forecast refresh scheduler works (when it's disabled) with forecast lock in the following settings: • Demand plan granularity – Weekly • Forecast horizon selected – 5 • intra-cycle forecast refresh schedule – Disabled • Final forecast publish – 7th day of the week • Lock period – 2 Forecast lock 193 AWS Supply Chain User Guide The example below displays how intra-cycle forecast refresh scheduler works (when it's enabled) with forecast lock in the following settings: • Demand plan granularity – Weekly • Forecast horizon selected – 5 • intra-cycle forecast refresh schedule – Enabled • Final forecast publish – 7th day of the week • Interim forecast publish – 3rd day of the week • Lock period – 2 Forecast lock 194 AWS Supply Chain User Guide Forecast model analyzer Forecast model analyzer is a self-service tool that you can use to execute forecast experiments on multiple forecast models (forecast period in past and future). Once executed, you can review the results of the diﬀerent forecast models. Using accuracy metrics and visual comparison between forecasts and actual demand, you can choose the required forecast model that suits your business Forecast model analyzer 195 AWS Supply Chain User Guide data patterns. You can execute the forecast model analyzer at the same time the production demand plan is running without any interference between each other or vice-versa. Note Forecast model analyzer is an optional work ﬂow. If you do not have multiple forecast models to compare, you can continue to use the default forecast model recommendations provided by AWS Supply Chain. The forecast model analyzer supports two main evaluation scenarios: • Back test scenario – You set the forecast start date in the past. In this scenario, forecasts are created and accuracy metrics are calculated and reported for forecast periods of overlap with actual demand periods. • Forward forecast scenario – You do not set the forecast start date and there is no overlap between forecast and actual data. In this scenario, forecasts are created but since actual demand data is not available (for future periods), accuracy metrics are not calculated or reported. You can still verify how the demand is forecasted against recent trend and prior year(s) demand. Make sure the demand plan settings are conﬁgured before you execute the forecast model analyzer. The forecast model analyzer inherits the demand plan settings for time interval and hierarchy granularity, while providing the ﬂexibility to adjust the forecast horizon and optionally select the forecast start date. You can choose to execute a back test or a forward forecast scenario. The default is forward forecast scenario where you do not specify a forecast start date and it is based on the last order date in the actual demand history. For more information, see Create your ﬁrst demand plan. However, if you choose to run a back test scenario, you can override the forecast start date and select a date in the past for back testing purposes. When the selected forecast start date is later than the outbound_order_line dataset end date, the default planning cycle last order date in the actual demand history is used. When the selected forecast start date is before the outbound_order_line start date or if the length of the demand history is insuﬃcient, the forecast will fail and display an error. For more information, see Prequisites before uploading your dataset. It is recommended to select the ﬁrst of the month for monthly intervals or
supplychain-ug-052	supplychain-ug.pdf	52	scenario, you can override the forecast start date and select a date in the past for back testing purposes. When the selected forecast start date is later than the outbound_order_line dataset end date, the default planning cycle last order date in the actual demand history is used. When the selected forecast start date is before the outbound_order_line start date or if the length of the demand history is insuﬃcient, the forecast will fail and display an error. For more information, see Prequisites before uploading your dataset. It is recommended to select the ﬁrst of the month for monthly intervals or Monday for weekly intervals. If you choose a diﬀerent date, Demand Planning will automatically adjust to the nearest default date. For example, if you selected Wednesday as the forecast start date, Demand Planning Forecast model analyzer 196 AWS Supply Chain User Guide will select the next Monday as the forecast start date for weekly intervals. Similarly, selecting May 10th 2024 will result in June 1st 2024 as the planning cycle start date for monthly intervals. Note Make sure you have at least four times the historical demand data for the forecast period you enter. After reviewing the model analyzer results, you can select or change the choice of forecast algorithm in the forecast analyzer tool. Alternatively, you can choose not to use model analyzer and proceed to directly selecting or changing the choice of forecast algorithm to be used. AWS Supply Chain will pick the default forecast method for your dataset when the model analyzer is not used. Forecast Model Analyzer produces forecasts and forecast metrics from across multiple models. The list of models included in the section called “Forecast Algorithms”. Viewing the forecast model analyzer details To view the generated forecast model analyzer details, complete the following steps: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Demand Planning and then choose Forecast Model Analyzer. 2. Under Forecast Model Analyzer, you can view the meta data for each iteration of model analyzer including forecast summary that includes key metrics (such as the count of products, sites, channels and customers for which forecast were created), forecast scope such as time- interval, forecast horizon, forecast start date, the list of datasets used, forecast granularity, and input data used. 3. Under Forecast(s) Vs. Actual Demand, you can view a graph that displays the actual demand history, prior year demand, and the forecast to analyze trends and seasonality. You can adjust the Viewing window start and Viewing window end to review historical periods. Depending on the conﬁgured time-interval, you can view the historical sales for 28 days, 52 weeks, 48 months, and 10 years. You can view and compare up to ﬁve forecast results simultaneously. 4. Under Measures, choose Edit to edit the selected forecast models. 5. Under Model Overview and Selection, the tables displays a summary of the forecast methods that were evaluated. In a back testing scenario, the table also displays aggregate forecast Viewing the forecast model analyzer details 197 AWS Supply Chain User Guide accuracy metrics such as, WAPE, Bias %, MAPE and sMAPE. Additionally, you can choose Select to select the forecast model. The change will be applied during the subsequent forecast cycle. 6. Choose Apply Selection to Demand Plan. You can view up to two forecast model analyzer results simultaneously. The most recent analyzer result remains fully interactive, allowing you to select and apply the preferred forecast method after careful evaluating the products. This will be applied in the next forecast generation. The previous analyzer result is rendered as read-only. You can export both the results of the forecast method with actual demand history. The exported data includes detailed information at the forecast period and granularity level, forecast by the P10/50/90 quantiles. For back test scenarios, the export will include actual demand data and corresponding accuracy metrics. You can modify the forecast selection method using the forecast model analyzer or under demand plan settings anytime. The changes will be applied during the subsequent forecast cycle. The demand plan page will show meta data around the forecast method for current and the next forecast model. Manage Demand Plan settings You can update the Demand Planning settings at any time to make sure that your forecasts are more accurate and take eﬀect when the forecast is successfully generated. Note Your prior forecast versions will be unavailable when you modify the Time Interval and Hierarchy levels on the Demand Plan page, because those prior versions will no longer align with the new forecast settings. When you modify the Time interval or Hierarchy conﬁguration and when you regenerate the forecast, the accuracy metrics will not be displayed since the accuracy metric values are not relevant. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose
supplychain-ug-053	supplychain-ug.pdf	53	settings at any time to make sure that your forecasts are more accurate and take eﬀect when the forecast is successfully generated. Note Your prior forecast versions will be unavailable when you modify the Time Interval and Hierarchy levels on the Demand Plan page, because those prior versions will no longer align with the new forecast settings. When you modify the Time interval or Hierarchy conﬁguration and when you regenerate the forecast, the accuracy metrics will not be displayed since the accuracy metric values are not relevant. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Organization, choose Demand Planning. The Demand Planning Setting page appears. Manage Demand Plan settings 198 AWS Supply Chain User Guide Use the steps in Create your ﬁrst demand plan to edit the Demand Planning conﬁguration settings. Role-based access control AWS Supply Chain Demand Planning oﬀers two default access levels: • Manage Access • Full demand planning capabilities (create, conﬁgure, generate forecasts) • Add overrides and publish demand plans • Export plans and reports • Access data validations, demand pattern analysis, and Model Analyzer • View Access • View created and published demand plans • View demand pattern analysis (Demand patterns tab in the Forecast review page) Topics • Managing user access Managing user access AWS Supply Chain administrators can modify roles and permissions. Topics • Adding new users • Modifying existing user access • Creating custom roles • Dataset requirements Adding new users To add new users, follow these steps: Role-based access control 199 AWS Supply Chain User Guide 1. Choose Settings, Users and Permissions, and Users. 2. Choose Add New User and search for user. 3. Assign permission role. Modifying existing user access To modify existing user access, follow these steps: 1. Choose Settings, Users and Permissions, and Users. 2. From the Permission Role drop-down menu, select the appropriate role. Note Users can have only one permission role. For multiple access privileges, create a custom role. Creating custom roles To create custom roles, follow these steps: 1. Choose Settings, Users and Permissions, and Create New Role. 2. Enter Role Name and choose Manage or View access in the Demand Planning section. 3. Conﬁgure dataset access. 4. Choose Save. Dataset requirements The following are important dataset requirements: • Default roles automatically include access to all required datasets. • Custom roles must be granted access to seven essential datasets: asc_adp_dp_segmentation, asc_adp_forecast, asc_adp_planning_cycle_accuracy, outbound_order_line, product, product_alternate, and supplementary_time_series. • Access to "asc_adp_dp_segmentation" is speciﬁcally required for demand pattern and recommendation functionality. Managing user access 200 AWS Supply Chain User Guide Supply Planning AWS Supply Chain supports two types of supply plans to help you accurately plan inventory to meet demand. Note You can only choose one supply plan per AWS Supply Chain instance to conﬁgure in AWS Supply Chain. To create multiple supply plans, you can create a new AWS Supply Chain instance under the same AWS account. • Auto Replenishment • Manufacturing Plan Topics • Auto Replenishment • Manufacturing Plans • Planning conﬁguration data Auto Replenishment You can use the Auto Replenishment feature to determine the amount of inventory to hold and when to order more inventory by automating inventory management. Auto Replenishment streamlines the inventory management process by monitoring inventory, forecasted demand, and automatically reordering items based on conﬁgured inventory policy, ordering schedules, minimum order quantities, and vendor lead times. You can use Auto Replenishment to generate purchase order requests that can be imported into your ERP or purchasing systems to create purchase orders (POs) for your suppliers. Key inputs Auto Replenishment relies on the following inputs to make accurate and informed calculations for inventory replenishment: Auto Replenishment 201 AWS Supply Chain User Guide • Demand – Demand data is the fundamental input for replenishment calculations. This data helps AWS Supply Chain understand the demand either in terms of past sales or future forecasts to be able to determine inventory requirements for future time buckets. You can provide demand forecasts or past sales history as an input for demand data. If demand forecasts are not available, you can provide sales history, and AWS Supply Chain will use historical consumption rate for replenishment calculations. • Inventory – Auto Replenishment uses on-hand inventory and on-order inventory as an input for replenishment calculations. On-hand inventory is the available inventory at locations that can be used to fulﬁll demands. On-order inventory is the open purchase or transfer orders that are inbound to the stocking location. Demand will be calculated from on-hand and on-order inventory to determine net supply requirements. • Lead time – Lead time is the time it takes for an order to be placed and the items to be received. Lead time helps AWS Supply Chain determine how far in advance it must place orders. For items
supplychain-ug-054	supplychain-ug.pdf	54	– Auto Replenishment uses on-hand inventory and on-order inventory as an input for replenishment calculations. On-hand inventory is the available inventory at locations that can be used to fulﬁll demands. On-order inventory is the open purchase or transfer orders that are inbound to the stocking location. Demand will be calculated from on-hand and on-order inventory to determine net supply requirements. • Lead time – Lead time is the time it takes for an order to be placed and the items to be received. Lead time helps AWS Supply Chain determine how far in advance it must place orders. For items that are ordered or procured from suppliers, lead time will refer to supplier/vendor lead time, which is the time it takes for a supplier to fulﬁll an order and deliver the goods. Any time required for internal order processing, quality checks, or handling should be included as part of the lead time. For items or products that are transferred from an enterprise’s internal locations, such as distribution centers or fulﬁllment centers, lead time will refer to transportation time, which is the time required for transportation and delivery from a source location to a destination location. • Sourcing rules – You can use sourcing rules to model supply chain network topology. Use sourcing rules to deﬁne relationships between diﬀerent levels of locations (for example, regional DC to central DC) or relationships between suppliers and their sites. These relationships can be modeled at a product group or region level, or at a product or site level. • Sourcing schedules – Use Auto Replenishment to regularly monitor and replenish items with every run, or conﬁgure predeﬁned schedules for items to be replenished. Use a sourcing schedule to deﬁne ordering schedules based on suppliers or shipping schedules, and on transportation schedules. You can deﬁne a sourcing schedule to replenish items multiple times a week, once a week, or during speciﬁc weeks of the month. • Inventory policy – Inventory policy is a key input to determine the target inventory level that is used to drive replenishment requirements. You can conﬁgure inventory policy at the most detailed product level, site level, or at an aggregate level such as product group, product segment, site, or region. Auto Replenishment supports absolute inventory level, days of cover, and service level inventory policies. You can deﬁne the target value for the conﬁgured inventory policy, and AWS Supply Chain uses the target value to determine the target inventory level. Key inputs 202 AWS Supply Chain User Guide For more information on data ﬁelds required for supply planning, see Supply Planning. Planning process Replenishment requirements are calculated based on the conﬁgured network topology for an item. The following is a sample network topology that we use to describe various calculations involved in generating replenishment orders. Auto Replenishment generates transfer requirements from spoke nodes to hub nodes (for example, regional DCs to the central DC), and it generates purchase requirements from hub nodes to suppliers (for example, central DC to suppliers). The following steps are involved in generating replenishment orders. These steps are repeated for each product and site combination that is in scope for replenishment planning. Requirements from downstream nodes are propagated upstream based on sourcing rules information, and the process repeats at the upstream node until it reaches the root node for that item. Planning process 203 AWS Supply Chain User Guide • Demand processing – AWS Supply Chain prepares the historical demand or forecast data based on the replenishment plan conﬁguration. Demand or forecasts are processed at the level of product, site, day, or week based on the replenishment plan conﬁguration settings. Sales history or forecast data are aggregated at the product and site level if they are provided at a more detailed level, such as product, site, customer or product, site, channel. Similarly, day to week aggregation occurs if a replenishment plan is conﬁgured at the week level. In the preceding example, demand is taken from spoke nodes, which are regional DCs, and it is aggregated at the product, site, and day/week level. If consumption or demand based inventory policy is used, the last 30 days of demand (sales history) is used to calculate average consumption. • Target inventory level – Use the demand or forecasts along with the conﬁgured inventory policy to determine target inventory level for a speciﬁc time period. Auto Replenishment supports two diﬀerent replenishment models. • Forecast-driven replenishment • Consumption-based replenishment AWS Supply Chain generates inventory targets based on the forecast. These inventory targets are determined based on lead time and sourcing schedules to ensure inventory levels account for the variability in demand and supply lead times. • Transfer or purchase requirements – AWS Supply Chain nets demand in each period from the supply (on-hand + on-order inventory) to project inventory into future time.
supplychain-ug-055	supplychain-ug.pdf	55	inventory level – Use the demand or forecasts along with the conﬁgured inventory policy to determine target inventory level for a speciﬁc time period. Auto Replenishment supports two diﬀerent replenishment models. • Forecast-driven replenishment • Consumption-based replenishment AWS Supply Chain generates inventory targets based on the forecast. These inventory targets are determined based on lead time and sourcing schedules to ensure inventory levels account for the variability in demand and supply lead times. • Transfer or purchase requirements – AWS Supply Chain nets demand in each period from the supply (on-hand + on-order inventory) to project inventory into future time. AWS Supply Chain maintains the projected inventory levels at the same level as the target inventory level calculated in the previous step. The diﬀerence between projected inventory level and target inventory level is the net supply requirement or reorder quantity (RoQ). AWS Supply Chain applies minimum order quantity, or it orders multiples to generate the ﬁnal transfer requirements or purchase requirement (POR). AWS Supply Chain uses the transfer or vendor lead time to determine the order by date. The default for lot size is 1.0, and the minimum order quantity is 0. Calculation logic Planning process 204 AWS Supply Chain User Guide rounding=f(RoQ,MOQ,Lot_Size) =Lot_Size×Max(RoQ,MOQ) The preceding formula describes the rounding logic in Auto Replenishment. AWS Supply Chain ﬁrst compares the reorder quantity RoQ and minimum order quantity MOQ, gets the ﬁnal order proposal, and then multiplies by the lot size factor for the actual quantity. The lot size is conﬁgured in the sourcing rules entity with the ﬁeld qty_multiple. • Requirement propagation – For spoke nodes, AWS Supply Chain uses sourcing rules to look up parent nodes and propagate transfer requirements to the upstream node. AWS Supply Chain oﬀsets the required delivery date by transfer lead time to determine the required date at the parent node. AWS Supply Chain only supports single sourcing. When this step is completed for all child or spoke nodes under a hub node, AWS Supply Chain repeats the previous steps on the hub node. This process is repeated until it reaches the root node in an item’s topology. Auto Replenishment only shows purchase order requests for vendor-facing sites. There are two kinds of vendor-facing sites: • Vendor-facing sites that supply other sites • Vendor-facing sites that don't supply other sites For vendor facing-sites that supply other sites, the reorder quantity is the reorder quantity from its child sites, plus the independent reorder quantity from its own demand. For vendor- facing sites that don't supply other sites, the reorder quantity is computed based on the demand Planning process 205 AWS Supply Chain User Guide forecast of the site. The independent reorder quantity for vendor-facing sites follows the same logic in the reorder quantity computation. The dependent demand is the summation of all the child sites. If the days of coverage is 7, the RoQ is the summation of the quantity of all orders in the covered period. The following example shows a scenario in the planning horizon where there is only one order for each site, and it explains the computation. Inventory policies Auto Replenishment supports three diﬀerent inventory policies. Each policy computes a plan based on a diﬀerent algorithm, and each policy requires diﬀerent inputs. Topics • Absolute inventory level • Days of Cover • Service level Absolute inventory level If you use absolute quantities to manage your inventory levels, you can use this policy setting to calculate target inventory level and RoQ. The absolute inventory level policy uses the conﬁgured target inventory level instead of computed inventory level (position). The target inventory level is the value of target_inventory_qty . Inventory policies 206 AWS Supply Chain Inputs and defaults User Guide The absolute inventory level policy requires forecast, lead time, and conﬁguration for absolute inventory level policy, as shown in the following table. Data required Entity Field Value Notes Inventory policy inventory_policy ss_policy abs_level Inventory policy inventory_policy target_in ventory_qty Inventory level quantity Forecast forecast NA Lead time Lead time transport ation_lane vendor_le ad_time NA NA NA NA NA NA > NA > Mean or forecast quantities. > Lead time from a source location to a destination. Lead time from a vendor to a destination location. target_inventory_qty from inventory_policy data entity used at the target inventory level Calculating reorder quantity The inputs for the reorder quantity (RoQ) calculation is the target inventory level and the current inventory level. If the inventory level record is missing, AWS Supply Chain generates a plan exception to review. Inventory policies 207 AWS Supply Chain Calculation logic User Guide The reorder quantity is the diﬀerence between the target inventory level and the current inventory level. If the current inventory level is higher than the target inventory level, the reorder quantity is 0. The goal of absolute policy is to make sure
supplychain-ug-056	supplychain-ug.pdf	56	target_inventory_qty from inventory_policy data entity used at the target inventory level Calculating reorder quantity The inputs for the reorder quantity (RoQ) calculation is the target inventory level and the current inventory level. If the inventory level record is missing, AWS Supply Chain generates a plan exception to review. Inventory policies 207 AWS Supply Chain Calculation logic User Guide The reorder quantity is the diﬀerence between the target inventory level and the current inventory level. If the current inventory level is higher than the target inventory level, the reorder quantity is 0. The goal of absolute policy is to make sure that on each review date there is enough on-hand inventory to match the desired inventory level. The inner max function computes the extra demand before the target review date (the ﬁrst review date after delivery). The covering period starts from the expected deliver date and ends with the target review date. If the current on-hand inventory or delivery date is able to cover demand for a speciﬁc period, the reorder quantity is 0. The max function determines if you must order extra. The outer max function computes the deﬁcit of inventory and determines whether an order should be placed. The reorder quantity calculation for sites that supply to other sites is calculated according to the logic explained in the Days of Cover (DOC) inventory policy. Days of Cover If you use Days of Cover (DoC) to manage your inventory levels, then this would be an appropriate policy setting to drive the calculation of target inventory levels and RoQ. DoC inventory policy uses the conﬁgured days of coverage. This policy doesn’t consider sourcing schedule (vendor review calendar) or vendor lead times to compute DOC. DOC is based on the target_doc_limit ﬁeld in the inventory_policy data entity. Note that, for weekly planning, target_doc_limit still uses unit of day. A coverage of 2 weeks translates to 14 days. DoC policy can be used with forecast (doc_fcst) or demand (doc_dem). The diﬀerence between doc_fcst and doc_dem is the forecast source. doc_fcst is based on forecast, while doc_dem is based on the demand history in outbound_order_line. The forecast based days of coverage uses P50 of forecast, while the demand based planning uses the last 30 days of demand history to calculate average consumption rate. Inventory policies 208 AWS Supply Chain Inputs and defaults User Guide Target inventory level or Target inventory position (TIP) is the desired inventory position or level on a given date. Inventory position includes inventory on hand, in-transit, or on-order, while the inventory level is only the inventory on-hand. Inventory position is used for service level (sl) inventory policy, and inventory level is used for doc_fcst, doc_dem, and abs_level inventory policies. DOC policy requires forecast, lead time, and conﬁguration for inventory policy. For doc_fcst policy, you must provide the following information: Data required 1 Entity Field Value Notes Inventory policy inventory_policy ss_policy doc_fcst Inventory policy inventory_policy target_doc_limit Number of days Forecast forecast NA Lead time Lead time transport ation_lane vendor_le ad_time NA NA NA NA NA NA > NA > Mean or forecast quantities. > Lead time from a source location to a destination. Lead time from a vendor to a destination location. For inventory policy based on days of coverage, the days to cover is the target_doc_limit value. Calculation logic for DOC_fcst policy Inventory policies 209 AWS Supply Chain User Guide Calculation Logic for doc_dem policy The goal of days of coverage policy is to make sure on each review date that there is enough on- hand inventory to cover the conﬁgured days of coverage. The ﬁrst part of the formula computes the days of coverage from the next review date until the end of days of coverage conﬁgured. The total covering period is DOCP,S for product P and site S. The second part of the formula computes the extra demand before the target review date (the ﬁrst review date after delivery). The covering period starts from the expected deliver date and ends with the target review date. If the current on-hand inventory on the delivery date is able to cover demand of this period, the system reorders 0. The max function determines whether we must order extra. Calculating reorder quantity The input for the reorder quantity calculation is the target inventory level and the current inventory level. If the inventory level record is missing, the system generates plan exceptions for you to review. The reorder quantity of product P, site S, and date D is the diﬀerence between the target inventory level and the current inventory level. If the current inventory level is higher than the target inventory level, the reorder quantity is 0. Service level If you use in-stock percentage to manage your inventory levels, you can use this policy setting to drive the calculation of target inventory level
supplychain-ug-057	supplychain-ug.pdf	57	The input for the reorder quantity calculation is the target inventory level and the current inventory level. If the inventory level record is missing, the system generates plan exceptions for you to review. The reorder quantity of product P, site S, and date D is the diﬀerence between the target inventory level and the current inventory level. If the current inventory level is higher than the target inventory level, the reorder quantity is 0. Service level If you use in-stock percentage to manage your inventory levels, you can use this policy setting to drive the calculation of target inventory level and replenishment. Inputs and defaults For sl policy, Supply Planning requires the following ﬁelds. If these ﬁelds are empty, the default value is set to null, and the application throws an exception. Inventory policies 210 AWS Supply Chain User Guide Data required Entity Field Value Notes Inventory policy inventory_policy ss_policy sl Service level is abbreviated as sl. > Inventory policy inventory_policy target_sl percentage value For example, 0.8 > Forecast forecast NA Lead time Lead time transport ation_lane vendor_le ad_time NA NA NA NA NA Sourcing schedule or sourcing_ schedule and Vendor schedule sourcing_ schedule_details NA NA Mean or forecast quantities. > Lead time from a source location to a destination. Lead time from a vendor to a destination location. Deﬁnes the calendar or days during which vendors accept orders. Calculating target inventory level Target Inventory Position (TIP) is used for service level (sl) inventory policy. TIP represents the desired inventory position on a given date. TIP includes on-hand and on-order inventory. The inputs required for service-level policy are forecast, lead time, sourcing schedule (plus sourcing schedule details), and conﬁguration for service level. Inventory policies 211 AWS Supply Chain User Guide TIP is based on forecast distribution. Supply Planning applies the critical ratio (CR or service_level) to forecast distribution, computes the demand, and sums up on days to cover. The available method to apply the critical ratio (service level) to forecast distribution is listed in the following. First, Supply Planning applies a CR to distribution in forecast (P10/P50/P90) by using linear interpolate. Supply Planning uses P10 for target_sl=0.1, P50 for target_sl=0.5, and P90 for target_sl=0.9. For a percentile that doesn’t exist in the forecast entity, Supply Planning uses a linear interpolate approach. Supply Planning computes other percentiles of demand forecast based on P10/P50/P90. Here are formulas for computing P40 (target_sl=0.4) and P75 (target_sl=0.75): P40=50−1040−10 ×(P50−P10)+P10 P75=90−5075−50×(P90−P50)+P50 When Supply Planning gets demand, the demand is summed up to use arbitrary summation by days to cover. Days to cover starts from the upcoming deliver date until the deliver date after the upcoming deliver date. Inventory policies 212 AWS Supply Chain User Guide As shown in the previous ﬁgure, the yellow period is the days to cover. The beginning of the days to cover does not start from the ﬁrst day of the planning horizon. The reason is that Supply Planning doesn’t order for days that cannot be covered. Supply Planning assumes that all lost sales are not recoverable. R1: the ﬁrst review date based on the sourcing schedule. R2: the second review date based on the sourcing schedule. LT_R1: the lead time for putting order on R1. LT_R2: the lead time for putting order on R2. R_R1: the review period based on sourcing schedule. RD_R1: the ﬁrst review date after R1, equaled to R1+R_R1. DD_R1: the deliver date if submit order is on R1; DD_R1 = R1 + LT_R1. DD_R2: the deliver date if submit order is on R2; DD_R2 = R2 + LT_R2. The following example shows the TIP computation. Inventory policies 213 AWS Supply Chain User Guide Calculating reorder quantity The inputs for the sl reorder quantity calculation are the target inventory level and the current inventory level. Supply Planning throws an exception if the inventory level record is missing. The reorder quantity is the diﬀerence between the target inventory position and the current inventory level. If the current inventory position is higher than the target inventory position, then the reorder quantity is set to 0. Conﬁguring Auto Replenishment By using Auto Replenishment, you can view the amount of inventory to hold and when to order more inventory by automating inventory management. Topics • Using Supply Planning for the ﬁrst time • Overview • Purchase order requests • Plan exceptions • Supply planning settings Conﬁguring Auto Replenishment 214 AWS Supply Chain User Guide Using Supply Planning for the ﬁrst time You can deﬁne how and when you want to plan your supply chain. Note When you log in to Supply Planning for the ﬁrst time, you can view the onboarding pages that highlight its key features. This helps you to get familiar with the Supply Planning capabilities. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply
supplychain-ug-058	supplychain-ug.pdf	58	management. Topics • Using Supply Planning for the ﬁrst time • Overview • Purchase order requests • Plan exceptions • Supply planning settings Conﬁguring Auto Replenishment 214 AWS Supply Chain User Guide Using Supply Planning for the ﬁrst time You can deﬁne how and when you want to plan your supply chain. Note When you log in to Supply Planning for the ﬁrst time, you can view the onboarding pages that highlight its key features. This helps you to get familiar with the Supply Planning capabilities. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply Planning. The Supply Planning page appears. 2. Choose Get Started. 3. On the Choose your plan page, select Auto Replenishment. 4. Choose Get Started. 5. On the Supply Planning page, choose Next. You can read through the description to understand what Supply Planning oﬀers, or you can choose Next to the Supply Planning Setup page. 6. On the Supply Planning Setup page, there are four steps to conﬁgure Supply Planning: • Name and Scope – Enter the name of the supply plan, and select the products and regions to be included in the supply plan. • Horizon and Schedule – Deﬁne the time frame for Supply Planning to generate plan schedules. • Inputs – Deﬁne how you want Supply Planning to use process demand forecasts. • Output – Choose the Supply Planning output to publish to your Amazon S3 connector. You can also use material deviation percentage for material plans. 7. Under Horizon and Schedule, you can do the following: • Planning Horizon – You can set the planning period by deﬁning the following: • Start day of the week – You can deﬁne your weekly supply planning. For example, if your Start day of the week is Monday, and today is July 3, then the supply planning period will be from July 3 to 9. • Time Bucketization – Deﬁne the time details. Daily and Weekly options are supported. Conﬁguring Auto Replenishment 215 AWS Supply Chain User Guide • Time Horizon – Deﬁne the planning time horizon. The supported range is from 1 to 90 days, or from 1 to 104 weeks. • Plan Schedule – Deﬁne when your supply plans must be executed. • Planning Frequency – Deﬁne how frequently you want to execute the supply plan. • Start Time – Deﬁne when to start planning on a scheduled day. • Release Times – Deﬁne the time Supply Planning releases the approved purchase orders into the ERP system. • Demand and Forecast – Deﬁne the source for demand forecasts. • Demand Planning – Supply Planning will use the published forecasts from Demand Planning . • External – Supply Planning with use the demand forecasts ingested into the Forecast data entity in data lake. • Past days for average demand calculation in consumption-based planning – For product, site combinations with inventory policy set as doc_dem, Supply Planning looks at the past days of sales history from the OutboundOrderLine data entity to determine the average daily demand. You can choose between 30, 60, 90, 180, 270, or 365 days and Supply Planning will consider the corresponding number of days of historical sales data when generating the average. • Forecast Netting – Independent demand includes both actual customer orders and forecasted demand. Forecast Netting oﬀers four diﬀerent methods to manage and conslidate these demand measures. By combining actual customer needs with forecast data eﬀectively, businesses can better manage inventory levels and improve operational processes. Selecting the appropriate netting method helps align supply with demand, reducing ineﬃciencies and enhancing customer satisfaction. • Do not change forecasted demand Do not change forecasted demand – Rely solely on forecasted demand to drive supply planning, discregarding actual customer orders. • Replace forecasted demand with actual orders if higher than forecast – If both forecasted demand and actual customer orders fall within the same time bucket, use the higher of the two values. • Add actual orders to forecasted demandAdd actual orders to forecasted demand – If both forecasted demand and actual customer orders fall within the same time bucket, add the two values toghether. • Enable demand time fence and forecast consumption – Forecasted demand within the demand time fence is ignored. Ourside the time fence, forecasted demand is adjusted Conﬁguring Auto Replenishment 216 AWS Supply Chain User Guide by substrating actual order quantity within the forecast consumption window. To use this option, users should also specify the demand time fence days, forecast consumption backward days, and forecast consumption forward days. • Demand Time Fence Days –The number of days between the current date and the demand time fence date. All forecasts on or before the demand time fence date will be ignored by the planning engine. • Forecast Consumption Backward Days –The number of
supplychain-ug-059	supplychain-ug.pdf	59	within the demand time fence is ignored. Ourside the time fence, forecasted demand is adjusted Conﬁguring Auto Replenishment 216 AWS Supply Chain User Guide by substrating actual order quantity within the forecast consumption window. To use this option, users should also specify the demand time fence days, forecast consumption backward days, and forecast consumption forward days. • Demand Time Fence Days –The number of days between the current date and the demand time fence date. All forecasts on or before the demand time fence date will be ignored by the planning engine. • Forecast Consumption Backward Days –The number of days that the planning engine will go backward to ﬁnd a matching forecast entry to consume starting from the due date of the sales order. • Forecast Consumption Forward Days– The number of days that the planning engine will go forward to ﬁnd a matching forecast entry to consume starting from the due date of the sales order. • Carry over unmet demand (backorders) in your planning? – Select Yes to carry over the orders that are not fulﬁlled in the current time period to the next time period. • Supply – Deﬁne your supply related inputs. • Past Due Orders – When an order in the InboundOrderLine data entity is not delivered and the expected delivery date is before the execution date, by default, Supply Planning ignores this order. However, you can conﬁgure the number of past due days to be considered for inbound inventory to reorder stock. For example, if you set the Past Due Orders for 7 days and if an order was expected 4 days ago, the item will still be considered for inbound inventory. 8. Choose Continue. 9. Choose Finish. Overview You can view the overall supply plan for your organization, as shown in the following example page. Conﬁguring Auto Replenishment 217 AWS Supply Chain User Guide • Supply Network – Under supply network, you can view the current products, sites, and suppliers in the current supply plan. • Inventory and Orders – Displays the total inventory across sites, including inventory on-hand and the inventory that is currently on-order with the suppliers. • Purchase Plan – Displays the system-generated purchase order requests to replenish inventory at sites. • Need Approval – Supply Planning uses the approval criteria you set under Settings to ﬂag purchase order requests for approval. • Scheduled for Release – Approved or auto-approved purchase order requests scheduled to be released to outbound connectors at the time you scheduled under Settings. • Plan to Purchase Order Conversion – Purchase order requests converted to POs in your ERP or purchasing systems. To calculate the accurate metrics, Purchase Order data coming from your source system must carry the reference back to the Purchase Order Request ID published to the outbound. This metric helps planners identify purchase order requests that are not converted to POs and take corrective actions. • Purchase Order Automation Percentage – Percentage of Purchase Order Requests that are auto-approved and released to outbound without user overrides to order quantity. Conﬁguring Auto Replenishment 218 AWS Supply Chain User Guide • Supply Insights – You can view all the purchase orders that are currently in-progress or awaiting approval. You can choose each insight to view and take action on. For more information, see Plan exceptions. You can download the supply plan report, which includes the inputs, intermediate calculations, and outputs for an auto-replenishment plan to your local computer. 1. On the Supply Planning Overview page, choose Export. The Export Supply Plan window appears. 2. Choose Download. Purchase order requests You can view current purchase order request details and status. 1. You can use the Filters option to ﬁlter your purchase orders according to your search criteria. Your can search purchase orders based on vendors, products, sites, order value, order quantity, and requested delivery date. 2. Choose Apply to apply your ﬁlter criteria to the current purchase orders, and choose Save ﬁlter group to save the search ﬁlter. Conﬁguring Auto Replenishment 219 AWS Supply Chain User Guide 3. Under Order Quantity, choose Edit to view and update the quantity. You can update the quantity based on the following inputs: • On-Hand – Inventory currently in-stock. • On-Order – Total product quantity of released purchase orders in the selected site. • Reorder Quantity – The product quantity required to meet the inventory. • Required – Reorder quantity required to meet the inventory and fulﬁll the forecast. • Minimum – Minimum order quantity deﬁned under VendorProduct.min_order_unit in the dataset. Supply Planning rounds the number to meet the minimum quantity. • Suggested – Final reorder quantity after adjustment. • Days of Cover – Number of days to replenish. 4. Choose Update to update the quantity request. 5. Under Product, choose the product to view the planned demand for
supplychain-ug-060	supplychain-ug.pdf	60	• On-Order – Total product quantity of released purchase orders in the selected site. • Reorder Quantity – The product quantity required to meet the inventory. • Required – Reorder quantity required to meet the inventory and fulﬁll the forecast. • Minimum – Minimum order quantity deﬁned under VendorProduct.min_order_unit in the dataset. Supply Planning rounds the number to meet the minimum quantity. • Suggested – Final reorder quantity after adjustment. • Days of Cover – Number of days to replenish. 4. Choose Update to update the quantity request. 5. Under Product, choose the product to view the planned demand for the product. Conﬁguring Auto Replenishment 220 AWS Supply Chain User Guide 6. Under Planned Demand, select the site to view the replenishment plan. 7. The Replenishment Plan tab appears. Note The Replenishment Plan page will appear empty. Make sure to select the product and site to view the demand forecast. 8. Choose Change Product/Site. The Choose a product and site combination page appears. 9. Under Product, enter the product. 10. Under Site, enter the site. 11. Choose Apply. 12. Under Enter order quantity, you can update the suggested Order Quantity. 13. Choose Update and Approve. 14. Under Actions, choose Approve to approve a purchase order. 15. You can also use the Show dropdown to ﬁlter your purchase orders based on status and release time. Conﬁguring Auto Replenishment 221 AWS Supply Chain Plan exceptions User Guide You can view the list of product-site combinations that could not be planned. The Exception Type column displays the root cause of the exemption. You can provide the missing information, such as inventory policy-related attributes or lead times through data connectors, or you can upload the updated dataset in Amazon S3. Under Product, you can choose multiple exceptions to delete or choose the Product header to delete all exceptions. Once selected, from the Actions drop-down, choose Delete Exception(s). Supply planning settings You can deﬁne how and when you want to plan and execute purchase orders. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. Choose Enterprise and Conﬁguration, and then choose Supply Planning. The Plan Settings page appears. 2. Follow the steps in Using Supply Planning for the ﬁrst time to edit the Supply Planning conﬁguration settings. 3. Under Reset Plan, choose Reset Plan to delete the existing plan and start a new supply plan. Note Only an administrator can reset a supply plan. The Reset entire plan page appears. 4. Choose Yes, reset the plan to delete the current supply plan and all the existing purchase orders requests. 5. Choose Save. Business workﬂow Auto Replenishment provides the following workﬂow for you to manage your inventory replenishment process. Business workﬂow 222 AWS Supply Chain User Guide • Generate replenishment plan – Supply Planning generates the replenishment plan according to the conﬁgured schedule. Recent input data required to generate replenishment plans is retrieved from the AWS Supply Chain data lake. Supply Planning uses conﬁguration data, transactional data, and plan settings to generate the replenishment plan that includes purchase order requests. • Review plan exceptions – Supply Planning generates Plan Exceptions for products and site combinations that do not have either required conﬁguration data (lead time, sourcing schedule, and so on) or required transactional data, such as on-hand inventory. Planners can review exceptions and provide required data before the next planning cycle in order to correct the issues and generate the replenishment plan. • Review and approve purchase order requests – Generated purchase order requests are either auto-approved or ﬂagged for manual approval, depending on the conﬁgured approval criteria in the plan settings. Planners can review, override, or approve purchase order requests by using AWS Supply Chain. • Users can manually update the order quantity, order-by date, and expected delivery date for system-generated purchase order requests. Once updated, users can mark these orders as Firmed and rerun the plan in ad-hoc mode by choosing Run Plan in the top-right corner of the page. When the plan runs, the system preserves Firmed purchase order requests and recalculates all planning measures on the Replenishment Plan page. It then automatically synchronizes the updated planning data with the supply_plan entity in the Data Lake. The next scheduled plan run will clear Firmed purchase order requests and generate new ones based on current data. • Publish to outbound – Approved (auto or manual) purchase order requests are published to the outbound Amazon S3 at the conﬁgured schedule in Plan Settings. You can integrate these purchase order requests to your ERP or purchasing systems for execution. Purchase order requests that get converted to purchase orders are ingested back to the AWS Supply Chain data lake by using inbound connectors. AWS Supply Chain expects these purchase orders to carry the reference to the original purchase order request.
supplychain-ug-061	supplychain-ug.pdf	61	The next scheduled plan run will clear Firmed purchase order requests and generate new ones based on current data. • Publish to outbound – Approved (auto or manual) purchase order requests are published to the outbound Amazon S3 at the conﬁgured schedule in Plan Settings. You can integrate these purchase order requests to your ERP or purchasing systems for execution. Purchase order requests that get converted to purchase orders are ingested back to the AWS Supply Chain data lake by using inbound connectors. AWS Supply Chain expects these purchase orders to carry the reference to the original purchase order request. This reference helps in tracking the conversion of purchase order requests to purchase orders. Business workﬂow 223 AWS Supply Chain User Guide Manufacturing Plans Manufacturing Plans helps you to determine production, transfer, and material requirements for multiple levels of sub-assemblies and components in a bill of material (BOM). Manufacturing Plans uses ﬁnished goods forecasts, BOMs, sourcing rules, on-hand inventory, on-order inventory, and lead times to determine net material, transfer, and production requirements. Manufacturing Plans propagates ﬁnished goods forecasts through the BOMs and applies sourcing rules to determine production, transfer, and material requirements. You can use this capability if you have in-house manufacturing or use outsourced manufacturers to make ﬁnished products or sub-assemblies. You can input plans to your purchasing systems to help create purchase orders for components with suppliers, production planning systems for detailed production scheduling and performance, and labor and production capacity planning systems to manage mid- to long-term capacities. Material plans (also called component forecasts) can also be shared with your contract manufacturers or with component suppliers through N-Tier Visibility. By sharing or publishing the Material Plans, you can provide better demand signals to upstream suppliers so that they can plan their inventory to meet future demand. By using N-Tier Visibility, suppliers can provide commitments on component forecasts back to you. For information on N-Tier Visibility, see N-Tier Visibility. Key inputs Manufacturing Plans depends on various inputs to make accurate and informed calculations for generating material, transfer, and production plans. Manufacturing Plans uses the same list of inputs as Auto Replenishment for inventory target calculation and net requirements determination for a product or site combination. For information on Auto Replenishment inputs, see Key inputs. In addition, Manufacturing Plans also requires the following inputs: • Bill of Material (BOM) – The BOM data entity is used to capture relationships between ﬁnished goods and various sub-assemblies and components that are required to make the ﬁnished goods. BOMs can contain multiple levels of components under a ﬁnished good, including alternates. Alternate or substitute components can be modeled under the same parent by using the alternate_group ﬁeld. AWS Supply Chain only supports priority-based alternates. Components with the lowest priority are selected by the planning process. Suppliers or vendors that supply components are not part of the BOM. This information is derived from sourcing rules and vendor management-related data entities. • Production process – This process is used to model the production step for manufacturing ﬁnished goods. The sourcing rule contains a reference to the production process that's used Manufacturing Plans 224 AWS Supply Chain User Guide to support the Manufacture type of rule. AWS Supply Chain only supports a single step manufacturing process. The component requirement date is determined based on production lead time and setup time, as deﬁned in the production process entity. Lead time is the oﬀset from the ﬁnished goods demand date, which is used to determine the requirement date for components. For information on data ﬁelds required for Supply Planning, see Supply Planning. Planning process Manufacturing Plans include material, transfer, and production plans. These plans are created based on the conﬁgured network topology for an item. The following illustration shows the steps involved in generating these plans. These steps are repeated for each product or site combination that is in the scope of a Manufacturing Plan. The steps and logic for Demand Processing, Inventory Target calculation, and Net Requirements calculation are common between Manufacturing Plans and Auto Replenishment. For more information, see Planning process and Inventory policies. • Production requirements – For products with site combinations with sourcing rule type Manufacture, Supply Planning uses the production process referenced in the sourcing rule to calculate production requirements. Make type should be used for ﬁnished goods or sub- assemblies that go through a production process. Lead times and setup times from the production_process data entity, along with the BOM, is used to determine the material or component requirements. Supply Planning also applies the frozen horizon deﬁned in the production process or the default setting to freeze supply during this time period and move all requirements to the ﬁrst time period after the frozen time horizon. • BOM explosion – For products or sites with sourcing rules of type Manufacture, Supply
supplychain-ug-062	supplychain-ug.pdf	62	in the sourcing rule to calculate production requirements. Make type should be used for ﬁnished goods or sub- assemblies that go through a production process. Lead times and setup times from the production_process data entity, along with the BOM, is used to determine the material or component requirements. Supply Planning also applies the frozen horizon deﬁned in the production process or the default setting to freeze supply during this time period and move all requirements to the ﬁrst time period after the frozen time horizon. • BOM explosion – For products or sites with sourcing rules of type Manufacture, Supply Planning uses the BOM deﬁned in the product_bom entity to determine production requirements for Planning process 225 AWS Supply Chain User Guide sub-assemblies and material requirements for component items. Supply Planning traverses the tree structure deﬁned in the BOM for the ﬁnished good or sub-assembly item. If there are multiple components for a parent item with the same alternate group, Supply Planning prioritizes one of the component items that belong to the same alternate group. Component material requirements are calculated from the start date until the end date of the planning horizon, as deﬁned in the planning settings. After component requirements are determined, Supply Planning applies Demand Processing and Target Inventory level calculation steps to determine net component requirements by considering inventory policy, lead times, and on- hand and on-order inventories. Conﬁguring Manufacturing Plans Conﬁgure Manufacturing Plans to generate material, transfer, and production requirements for components and ﬁnished good items. Using Supply Planning for the ﬁrst time You can deﬁne how and when you want to plan your supply chain. When you log in to Supply Planning for the ﬁrst time, you can view the onboarding pages that highlight its key features. This helps you to get familiar with the Supply Planning capabilities. Note Make sure that the required data is ingested before conﬁguring Manufacturing Plans. For information on the data ﬁelds required for Supply Planning, see Supply Planning. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply Planning. The Supply Planning page appears. 2. Choose Get Started. 3. On the Choose your plan page, select Manufacturing Plans. 4. Choose Get Started. 5. On the Supply Planning page, choose Next. You can read through the description to understand what Supply Planning oﬀers, or you can choose Next to get to the Supply Planning Set-up page. Conﬁguring Manufacturing Plans 226 AWS Supply Chain User Guide 6. On the Material Plan Changes page, you can view all the material plans that deviated from the predeﬁned supply plan. Under Supply Insights, you can search for a particular material plan in the Search box, by Required Date and Insight Type. You can also choose a particular material plan to view more details. 7. Choose Get Started. 8. On the Supply Planning Set-up page, there are four steps to conﬁgure Manufacturing Plans: • Name and Scope • Horizon and Schedule • Inputs • Output 9. On the Name and Scope page, under Plan Name, enter a name for your plan. Under Supply Planning Scope, select all the product groups and regions that must be included in the supply plan. Note If you do not see the Product Groups or Regions that you ingested through Supply Chain data lake, ingest the Product BOM through the API and make sure that all the other datasets, such as Product, ProductHierarchy, Site, Geography, and SourcingRule, are already ingested. 10. Choose Continue. 11. On the Horizon and Schedule page, you can do the following: • Planning Horizon – You can set the planning period by deﬁning the following: • Start day of the week – You can deﬁne your weekly supply planning. For example, if your Start day of the week is Monday, and today is July 3, then the supply planning period will be from July 3 to 9. • Time Bucketization – Deﬁne the time details. Daily and Weekly options are supported. • Time Horizon – Deﬁne the planning time horizon. The supported range is from 1 to 90 days, or from 1 to 104 weeks. Conﬁguring Manufacturing Plans 227 AWS Supply Chain User Guide • Plan Schedule – Deﬁne when your supply plans must be executed. • Planning Frequency – Deﬁne how frequently you want to execute the supply plan. • Start Time – Deﬁne when to start planning on a scheduled day. • Release Times – Deﬁne the time Supply Planning releases the approved purchase orders into the ERP system. • Demand and Forecast – Deﬁne the demand forecast for Supply Planning. • Demand Planning – Supply Planning will use the forecast information from the demand plan generated from Demand Planning . • External – Supply Planning with use the Forecast data entity to extract the demand forecasts for Supply Planning.
supplychain-ug-063	supplychain-ug.pdf	63	plans must be executed. • Planning Frequency – Deﬁne how frequently you want to execute the supply plan. • Start Time – Deﬁne when to start planning on a scheduled day. • Release Times – Deﬁne the time Supply Planning releases the approved purchase orders into the ERP system. • Demand and Forecast – Deﬁne the demand forecast for Supply Planning. • Demand Planning – Supply Planning will use the forecast information from the demand plan generated from Demand Planning . • External – Supply Planning with use the Forecast data entity to extract the demand forecasts for Supply Planning. • Past days for average demand calculation in consumption-based planning – For each product-site combination, Supply Planning looks at the past 30 days of sales history from the OutboundOrderLine data entity to determine the average daily demand. You can choose between 30, 60, 90, 180, 270, or 365 days and Supply Planning will consider the corresponding number of days of historical sales data when generating the average. • Forecast Netting – Independent demand includes both actual customer orders and forecasted demand. Forecast Netting oﬀers four diﬀerent methods to manage and conslidate these demand measures. By combining actual customer needs with forecast data eﬀectively, businesses can better manage inventory levels and improve operational processes. Selecting the appropriate netting method helps align supply with demand, reducing ineﬃciencies and enhancing customer satisfaction. • Do not change forecasted demand – Rely solely on forecasted demand to drive supply planning, discregarding actual customer orders. • Replace forecasted demand with actual orders if higher than forecast – If both forecasted demand and actual customer orders fall within the same time bucket, use the higher of the two values. • Add actual orders to forecasted demand– If both forecasted demand and actual customer orders fall within the same time bucket, add the two values toghether. • Enable demand time fence and forecast consumption– Forecasted demand within the demand time fence is ignored. Ourside the time fence, forecasted demand is adjusted by substrating actual order quantity within the forecast consumption window. To use this option, users should also specify the demand time fence days, forecast consumption backward days, and forecast consumption forward days. Conﬁguring Manufacturing Plans 228 AWS Supply Chain User Guide • Demand Time Fence Days –The number of days between the current date and the demand time fence date. All forecasts on or before the demand time fence date will be ignored by the planning engine. • Forecast Consumption Backward Days –The number of days that the planning engine will go backward to ﬁnd a matching forecast entry to consume starting from the due date of the sales order. • Forecast Consumption Forward Days– The number of days that the planning engine will go forward to ﬁnd a matching forecast entry to consume starting from the due date of the sales order. • Carry over unmet demand (backorders) in your planning? – Select Yes to carry over the orders that are not fulﬁlled in the current time period to the next time period. • Supply – Deﬁne your supply related inputs. • Past Due Orders – When an order in the InboundOrderLine data entity is not delivered and the expected delivery date is before the execution date, by default, Supply Planning ignores this order. However, you can conﬁgure the number of past due days to be considered for inbound inventory to reorder stock. For example, if you set the Past Due Orders for 7 days and if an order was expected 4 days ago, the item will still be considered for inbound inventory. 12. Choose Continue. 13. On the Output page, you can do the following: • Plan Outputs – Select the type of supply plan that you want Supply Planning to generate. • Plan Insights – Set the deviation criteria to generate supply plan insights. 14. Choose Finish. 15. (Optional) Choose Invite Partners to invite suppliers into your supply plan. You can also choose Skip for now to return to Supply Planning. Plan overview You can view the overall manufacturing plan for your organization. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply Planning. The Supply Planning page appears. Conﬁguring Manufacturing Plans 229 AWS Supply Chain 2. Choose Get Started. 3. On the Choose your plan page, select Manufacturing Plan. The Manufacturing Plan page appears. User Guide 4. Choose Export to download the Material Plans, Production Plans, or Transfer Plans to your Amazon S3 bucket. 5. Choose the Plan Overview tab. • Plan Summary – Displays the overall manufacturing plan. Note Plan Summary metrics will not be available for new users. You can view the Plan Summary metrics after the next supply planning cycle. • Inventory On-hand – Displays the current inventory on-hand in dollars. • Open POs – Displays
supplychain-ug-064	supplychain-ug.pdf	64	Manufacturing Plans 229 AWS Supply Chain 2. Choose Get Started. 3. On the Choose your plan page, select Manufacturing Plan. The Manufacturing Plan page appears. User Guide 4. Choose Export to download the Material Plans, Production Plans, or Transfer Plans to your Amazon S3 bucket. 5. Choose the Plan Overview tab. • Plan Summary – Displays the overall manufacturing plan. Note Plan Summary metrics will not be available for new users. You can view the Plan Summary metrics after the next supply planning cycle. • Inventory On-hand – Displays the current inventory on-hand in dollars. • Open POs – Displays the current open purchase orders and the required dollars. • Suppliers – Displays the total number of active suppliers. • Purchase Requirements – Displays the total quantity of end components required and their total cost. Conﬁguring Manufacturing Plans 230 AWS Supply Chain User Guide • Plan Exceptions – Displays exceptions for missing datasets or issues in any of the data entities. • Supply Insights – Supply Insights are only generated for all Material Plan changes end components when they satisfy the deviation percent change compared with the previous plan. You can select each insight to view it and take action it. You can use the Search box to search based on Product Name or Site Name, or you can search for speciﬁc supply insights by using the Required Date Start and Required Date End. Plan outputs You can view the overall manufacturing plan for your organization. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply Planning. The Supply Planning page appears. 2. Choose Get Started. 3. On the Choose your plan page, select Manufacturing Plans. The Manufacturing Plan page appears. 4. Choose the Plan Outputs tab. Choose Filters to ﬁlter the list based on Products or Sites. Conﬁguring Manufacturing Plans 231 AWS Supply Chain User Guide • Material Plan – Displays the overall material plan for end components from the supply plan generated. • Transfer Plan – Displays the overall transfer plan for any materials or ﬁnished goods between sites from the supply plan generated. • Production Plan – Displays the overall production plan for ﬁnished goods from the supply plan generated. 5. Under Material Plan and Material Requirements, you can view the supply details for each item. 6. Under Item, choose the Supply Plan Details for the selected item. The Supply Plan Details page appears. The Supply Plan Details section displays item details and attributes. Choose View all attributes to view all the attributes of an item. Under Supply Plan, you can view the supply plan for the selected item. You can view the supply plan for a speciﬁc date range by using Start Date and End Date. • Demand Forecast – Displays the demand forecast or dependent demand related to an item or site. • Inventory – Displays the on-hand inventory level related to an item or site. Conﬁguring Manufacturing Plans 232 AWS Supply Chain User Guide • Open Order – Displays open order quantities based on the expected_delivery_date for an item or site. Supported order types are Purchase order, Transfer order, or Manufacturing order. • Inventory Target – Target inventory level calculated based on the inventory policy and order schedule. For more information, see Inventory policies. • Planned Supply – Displays the planned supply. • Total Supply – The sum of open orders and planned supply. • Projected Ending on Hand – The projected order ending on hand. Projected Ending On Hand (EOH) is calculated based on Demand, Supply, and Inventory. EOH(T0) = Inventory(T0) + Open Orders(T0) + Planned Supply(T0) - Demand Forecast(T0) EOH(T1) = EOH(T0) + Open Orders(T1) + Planned Supply(T1) - Demand Forecast(T1). 7. You can also view the overall Supply Planning for an item: • Material Plan – Displays the material plan related to an item or site. • Transfer Plan – Displays the transfer plan related to an item or site. • Production Plan – Displays the production plan related to an item or site. • Purchase Orders – Displays the input purchase orders used in generating the supply plan. • Transfer Orders – Displays the input transfer orders used in generating the supply plan. • Production Orders – Displays the input production orders used in generating the supply plan. Plan exceptions You can view the overall manufacturing exceptions for your organization. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply Planning. The Supply Planning page appears. 2. Choose Get Started. 3. On the Choose your plan page, select Manufacturing Plans. The Manufacturing Plans page appears. 4. Choose the Plan Exceptions tab. Conﬁguring Manufacturing Plans 233 AWS Supply Chain User Guide You can use the Filters icon to ﬁlter exceptions based on Product and Site. Choose View all to view all the available
supplychain-ug-065	supplychain-ug.pdf	65	– Displays the input production orders used in generating the supply plan. Plan exceptions You can view the overall manufacturing exceptions for your organization. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Supply Planning. The Supply Planning page appears. 2. Choose Get Started. 3. On the Choose your plan page, select Manufacturing Plans. The Manufacturing Plans page appears. 4. Choose the Plan Exceptions tab. Conﬁguring Manufacturing Plans 233 AWS Supply Chain User Guide You can use the Filters icon to ﬁlter exceptions based on Product and Site. Choose View all to view all the available ﬁlters. Importing product_bom data To import product_bom data using the AWS CLI, follow the procedure below: Note You can only use AWS CLI to import product_bom data into AWS Supply Chain. 1. Make a note of your instance ID where you want to import your product_bom data. Your URI format for your supply chain data bucket will be "s3://aws-supply-chain- data-INSTANCE_ID/product_bom.csv". 2. Use the following command to upload your product_bom data to the Amazon S3 instance bucket. aws s3 cp Path To Local Product BOM CSV$S3_BOM_URI "s3://aws-supply-chain- data-INSTANCE_ID/product_bom.csv". 3. Use the following command to invoke the create bill of materials import job. aws supplychain create-bill-of-materials-import-job --instance-id $INSTANCE_ID --s3uri "s3://aws-supply-chain-data-INSTANCE_ID/product_bom.csv" Note Make sure to use the same destination Amazon S3 URI that you used when uploading the CSV in step 2. 4. Make a note of the job ID returned. 5. Use the following command to view the imported result. aws supplychain get-bill-of-materials-import-job --instance-id $INSTANCE_ID --job-id job-id from step 4 For more information on AWS Supply Chain API see the AWS Supply Chain API Reference. Conﬁguring Manufacturing Plans 234 AWS Supply Chain Business workﬂow User Guide Supply Planning provides the following workﬂow to manage your manufacturing plans. • Generate plan – Supply Planning generates the manufacturing plan according to the conﬁgured schedule. The latest input data required to generate the plan is received from the AWS Supply Chain data lake. Supply Planning uses conﬁguration data, transactional data, and plan settings to generate the manufacturing plan, which includes material, transfer, and production plans. The Manufacturing Plan is generated for the conﬁgured planning horizon in terms of the number of time periods. You can create plans with either daily or weekly details, and you can create them on a daily or weekly frequency. If multiple plans are created within the same planning cycle (daily or weekly), new plans will override the existing plans. Existing plans are versioned after a new plan is generated at the beginning of a new planning cycle (for example, a new week). • Review plan exceptions – Supply Planning generates plan exceptions for products or site combinations that do not have either required conﬁguration data (lead time, sourcing schedule, and so on) or required transactional data, such as on-hand inventory. Planners can review exceptions and provide required data, and then they can rerun the plan to correct the issues and generate the supply plan for relevant product and site combinations. • Review manufacturing plan – Supply planners can review and manage material, transfer, and production plans by navigating to the Plan Overview, Plan Outputs, Supply Plan Details, and Supply Demand Pegging tabs in the AWS Supply Chain web application. The Supply Planning module generates Material Plan Change insights for products and sites where the required quantity deviation exceeds the conﬁgured threshold, relative to the most recent plan. Planners can conﬁgure the display of detailed inputs, such as forecasts, inventory levels, orders, and other relevant data that contribute to the calculation of the plan's output. Business workﬂow 235 AWS Supply Chain User Guide • The Supply Plan Details page oﬀers a comprehensive timeline view, displaying key metrics such as forecast, inventory, open orders, and planned supply. This allows planners to assess and adjust plans as needed. • The Supply Demand Pegging page provides a detailed list of all pegging records that link supply orders to their corresponding demand orders. Each pegging record includes information about the supply order (for example, on-hand inventory, purchase orders, planned purchase orders, planned manufacture orders, and planned transfer orders), the demand order (for example, sales orders, forecasted demands, and planned order demands), the pegged quantity, and the associated end demand. This view enables users to analyze how speciﬁc supply quantities are allocated to fulﬁll various demand orders, and vice versa. Users can interact with the data by selecting any demand quantity to view all supply orders linked to it or selecting any supply quantity to see all demand orders tied to that supply. From this view, users can also navigate to the End Demand Pegging page by clicking the End Demand Product for a more consolidated overview of a speciﬁc end demand. • The End Demand Pegging page provides a comprehensive view of the entire pegging
supplychain-ug-066	supplychain-ug.pdf	66	the associated end demand. This view enables users to analyze how speciﬁc supply quantities are allocated to fulﬁll various demand orders, and vice versa. Users can interact with the data by selecting any demand quantity to view all supply orders linked to it or selecting any supply quantity to see all demand orders tied to that supply. From this view, users can also navigate to the End Demand Pegging page by clicking the End Demand Product for a more consolidated overview of a speciﬁc end demand. • The End Demand Pegging page provides a comprehensive view of the entire pegging tree for a speciﬁc end demand, such as a sales order or forecast. It oﬀers full visibility into all related supply and demand orders associated with the end demand, including planned transfer orders, planned manufacture orders, purchase orders, and intermediate demands. This view allows users to trace the entire supply chain ﬂow, from the top-level demand to every linked supply and dependent demand orders, oﬀering a clear insight into how supply orders are structured to meet customer or forecasted needs. These views help users eﬃciently manage and track supply and demand allocation across the supply chain. • Planned order adjustments – Users can manually update the order quantity, order-by date, and expected delivery date for system-generated planned orders, including Planned Purchase Orders, Planned Transfer Orders, and Planned Production Orders. After making updates, users can mark these orders as Firmed to ensure they are preserved during planning runs. To run the plan in ad-hoc mode, users can choose Run Plan located in the top-right corner of the page. When the plan runs, the system retains all Firmed planned orders, recalculates planning measures on the Supply Plan Details page, and reﬂects any changes in upstream sites or bill of material (BOM) components in the updated plan output. In addition to modifying existing planned orders, users can create new Planned Transfer Orders directly from the Transfer Plan page by selecting Create New Transfer Order from the Action menu. After the ad-hoc plan run is complete, the system automatically synchronizes the updated planning data with the supply_plan and Business workﬂow 236 AWS Supply Chain User Guide supply_demand_pegging entities in the Data Lake. During the next scheduled planning run, the system will clear all previously Firmed planned orders and generate new ones based on the latest data inputs. • Publish to outbound – Supply plans are published to the outbound Amazon S3 connector at the conﬁgured time scheduled under Plan Settings. You can integrate these plans into your ERP, purchasing, or production planning systems for execution. • Publish to N-Tier visibility – Material plans can optionally be published to the suppliers through N-Tier visibility. Material plans are published to N-Tier visibility based on the schedule that's conﬁgured under Plan Settings. N-Tier visibility further publishes the material plan to onboarded suppliers based on collaboration settings. Planning conﬁguration data This section lists all the required ﬁelds used by Supply Planning and describes how each ﬁeld is used. For information on data ﬁelds required for Supply Planning, see Supply Planning. Topics • Product • Site • Trading partner • Vendor product • Vendor lead time • Sourcing rule • Inventory policy • Sourcing schedule • Bill of Material (BOM) • Production process • Supply planning parameters • Transactional data Planning conﬁguration data 237 AWS Supply Chain Product User Guide The product entity deﬁnes the list of items or products that must be included in the planning. The purchase order requests use unit_cost ﬁeld from the Product entity to determine the order value or amount. The Product entity also contains the product group corresponding to a speciﬁc product, which is a foreign key into a product_hierarchy entity. Product groups can be used in conﬁguring inventory policies, sourcing schedules, lead times, and so on, at the aggregate level. Site The Site entity deﬁnes the list of sites or locations that must be included in the planning. The Site entity also contains Regions corresponding to a speciﬁc site, which is a foreign key into a Geography entity. Regions can be used in conﬁguring inventory policies, sourcing schedules, lead times, and so on, at the aggregate level. Trading partner The Trading_partner entity deﬁnes the list of suppliers. tpartner_type should be set to Vendor when uploading supplier information. Vendor product Products supplied by each supplier are deﬁned in the vendor_product entity. This entity also contains vendor-speciﬁc cost information. Vendor lead time Vendor lead time is the time period between placing an order to a vendor and receiving the order. This data is deﬁned in the VendorMgmt category under the vendor_lead_time data entity. Vendor lead time follows the following override logic: • Product level vendor lead time overrides product group level vendor lead time. • Site level vendor lead time overrides region level vendor
supplychain-ug-067	supplychain-ug.pdf	67	deﬁnes the list of suppliers. tpartner_type should be set to Vendor when uploading supplier information. Vendor product Products supplied by each supplier are deﬁned in the vendor_product entity. This entity also contains vendor-speciﬁc cost information. Vendor lead time Vendor lead time is the time period between placing an order to a vendor and receiving the order. This data is deﬁned in the VendorMgmt category under the vendor_lead_time data entity. Vendor lead time follows the following override logic: • Product level vendor lead time overrides product group level vendor lead time. • Site level vendor lead time overrides region level vendor lead time. • Region level vendor lead time overrides company level vendor lead time. To look for a record, Supply Planning uses the following ﬁelds: • company_id Product 238 AWS Supply Chain • region_id • site_id • product_group_id • product_id The following is an example of the override logic: User Guide The following is an example of how Supply Planning calculates vendor lead time: Prioritization order is product > product_group > site > dest_geo (region) > product segment > company. Sourcing rule Supply Planning generates a plan based on the supply chain network topology deﬁned under the sourcing_rules entity. The supported sourcing rule types are transfer, buy, and manufacture. Sourcing rules follow the product_id > product_group_id > company_id override logic. Supply Planning retrieves the transportation lead time by referencing transportation_lane_id and accessing transit_time in transportation_lane. There are two steps to retrieve the transfer lead time. Sourcing rule 239 AWS Supply Chain User Guide 1. Find transportation_lane_id in sourcing_rules. Only the sourcing rules that have both to_site_id and from_site_id are eligible for retrieving transfer_lead_time. 2. Use transportation_lane_id to look up transportation_lane. When there are multiple records with the same to_site_id and product_id (product_group_id) in the sourcing_rule entity, only the records with the highest priority (the smallest number) will be used. Sourcing rules example: Based on the preceding deﬁnition, Supply Planning selects the following sourcing rule SR1: Laptop at site TX0 is sourced from site IL0 via transportation_lane_9. sourcing_ rule_id product_i d product_g roup_id sourcing_ rule_type from_site _id to_site_i d sourcing_ priority transport ation_lan SR1 laptop SR2 laptop SR3 laptop electroni cs electroni cs electroni cs transfer IL0 TX0 transfer NJ1 TX0 transfer IL0 TX0 1 2 1 e_id transport ation_lan e_9 transport ation_lan e_21 transport ation_lan e_11 When multiple records with the same priority exist for the same combination of to_site_id, product_id (or product_group_id), the reorder quantity will be distributed among the available sourcing options based on the sourcing_ratio ﬁeld. Note that multiple sourcing is currently only supported for the buy sourcing rule type. Multi-sourcing example: Sourcing rule 240 AWS Supply Chain User Guide sourcing_ rule_id product_i d product_g roup_id sourcing_ rule_type tpartner_ id to_site_i d sourcing_ priority sourcing_ ratio SR1 laptop SR2 laptop electroni cs electroni cs buy supplier1 TX0 buy supplier2 TX0 1 1 4 6 Both sourcing rules, SR1 and SR2, are selected, and the order quantity will be allocated between Supplier 1 and Supplier 2 in a 4:6 ratio. Inventory policy Supply Planning searches for a record in the dataset by using the following ﬁelds: • site_id • geodesic • company_id • product_id • product_group_id • segment_id Supply Planning uses ss_policy to determine the inventory policy. The override logic uses the following priority: product_id > product_group_id > site_id > and dest_geo_id > segment_id > company_id. The supported ss_policy values are abs_level, doc_dem, doc_fcst, and sl. The following example displays the override priority logic. Inventory policy 241 AWS Supply Chain User Guide The following is an example of the ss_policy value based on the override logic. Sourcing schedule Note Sourcing schedule is an optional entity. If this entity is not provided, Supply Planning uses a continuous review process to generate required_date based on when products are needed. Supply Planning uses sourcing schedule to generate purchase plans by using the following steps: • Find sourcing_schedule_id in sourcing_schedule. • Find the schedule by using sourcing_schedule_id in sourcing_schedule_details. Supply Planning searches for the following ﬁelds in sourcing_schedule_id under sourcing_schedule. • to_site_id • tpartner_id or from_site_id Sourcing schedule 242 AWS Supply Chain User Guide Based on the sourcing path in sourcing rules, Supply Planning determines whether to use from_site_id or tpartner_id. Supply Planning reads the value in the sourcing_schedule_id ﬁeld to determine the next step. Supply Planning reads the schedule details under sourcing_schedule_details with the following ﬁelds: • sourcing_schedule_id • company_id • product_group_id • product_id sourcing_schedule_details follows the override logic, product_id > product_group_id > company_id. The following is an example of the override logic in sourcing_schedule_details. The following are the selected schedules after applying the override logic. The actual schedule can be from one row to multiple rows, based on the complexity of the schedule. For the ﬁeld week_of_month, only one number is allowed in each row. For multiple weeks of the
supplychain-ug-068	supplychain-ug.pdf	68	Planning reads the value in the sourcing_schedule_id ﬁeld to determine the next step. Supply Planning reads the schedule details under sourcing_schedule_details with the following ﬁelds: • sourcing_schedule_id • company_id • product_group_id • product_id sourcing_schedule_details follows the override logic, product_id > product_group_id > company_id. The following is an example of the override logic in sourcing_schedule_details. The following are the selected schedules after applying the override logic. The actual schedule can be from one row to multiple rows, based on the complexity of the schedule. For the ﬁeld week_of_month, only one number is allowed in each row. For multiple weeks of the month, multiple records are required (see the following example). For the ﬁeld day_of_week, both integer and name of day are allowed (Sun: 0, Mon: 1, Tue: 2, Wed: 3, Thu: 4, Fri: 5, Sat: 6). In the sourcing schedule details, weekly planning requires week_of_month. While in daily planning, week_of_month can be empty, which means every week. See the following examples. Sourcing schedule 243 AWS Supply Chain User Guide Note that for weekly planning, week_of_month is required if day_of_week is provided. The following example shows the dates that can be used for daily planning. Date 8/1/2023 8/12/2023 NA NA Day of the week Week of the month NA NA 2 5 NA NA NA NA The following example can be used for both daily and weekly planning. Date 8/1/2023 8/12/2023 NA Sourcing schedule Day of the week Week of the month NA NA 2 NA NA 1 244 AWS Supply Chain Date Day of the week Week of the month User Guide NA NA NA NA NA NA NA NA NA 2 2 2 2 5 5 5 5 5 2 3 4 5 1 2 3 4 5 Bill of Material (BOM) Product BOM is used in Manufacturing Plans when sourcing_rule is set to Manufacture. For information on how to ingest Product BOM, see the AWS Supply Chain API Reference document. Production process production_process_id is referenced in the sourcing_rule and product_bom entities. These ﬁelds are used to consume lead time information to make or assemble a BOM. Supply planning parameters In supply_planning_parameters entity, planner_name of the supply planner can be assigned at product_id level. Planner name will be displayed on the planned orders generated by the supply planning engine. Transactional data Topics Bill of Material (BOM) 245 AWS Supply Chain • Forecast • Sales history or demand • Inventory level • Inbound orders Forecast User Guide Supply Planning uses two diﬀerent sources and types of forecast. You can use the following source systems to retrieve forecast source: • External – Supply Planning uses the data that is being ingested into the data lake forecast entity. • Demand Planning – Supply Planning uses the forecasts from Demand Planning. • None – Supply Planning uses the sales or demand history data from the outbound order line. Supply Planning supports two types of forecast: deterministic and stochastic. Deterministic forecasts contain only the mean of the forecast. Stochastic forecasts contain P10/P50/P90, sometimes along with mean. When mean is not provided with stochastic forecasts, Supply Planning uses P50(median) as mean. Each forecast record has four ﬁelds to represent the demand forecast: • mean(double) • p10(double) • p50(also known as median, double) • p90(double) Based on the conﬁgured inventory policy, diﬀerent ﬁelds in this entity are required. For sl, p10/ p50/90 is required; for doc_fcst, policy p50 or mean is required. Supply Planning uses p50 as an approximation of the mean, and for doc_dem and abs_level, none of the forecast ﬁelds are required. Daily planning Forecasts may be diﬀerent for daily planning compared to weekly planning. Here is an example of the daily and weekly planning forecast requirement. Transactional data 246 AWS Supply Chain User Guide Weekly planning You can use the daily planning forecast example for weekly planning, or you can also use the following example for weekly planning. Sales history or demand Inventory policy doc_dem requires demand history to compute the historical average demand. Supply Planning gets the demand history from the outbound_order_line entity under the Outbound category. Supply Planning uses the following ﬁelds: • ship_from_site_id(string) • product_id(string) • actual_delivery_date(timestamp); when missing, use promised_delivery_date(timestamp) As part of the calculation, Supply Planning uses historical outbound order lines with delivery dates in the past 30 days. The target ﬁeld used for quantity is quantity_delivered; when missing, use quantity_promised. If quantity_promised is missing, then ﬁnal_quantity_requested will be used. If all are missing, then 0 will be used. For example, if you use Supply Planning for product “laptop” at site “TX0” on July 1, 2023, the record in outbound_order_line where product_id=laptop, ship_from_site_id=TX0, and actual_delivery_date is from June 1, 2023 to June 30, 2023. Supply Planning adds all the records and divides by 30 days to get the daily demand. Transactional data 247 AWS Supply Chain Inventory level User
supplychain-ug-069	supplychain-ug.pdf	69	order lines with delivery dates in the past 30 days. The target ﬁeld used for quantity is quantity_delivered; when missing, use quantity_promised. If quantity_promised is missing, then ﬁnal_quantity_requested will be used. If all are missing, then 0 will be used. For example, if you use Supply Planning for product “laptop” at site “TX0” on July 1, 2023, the record in outbound_order_line where product_id=laptop, ship_from_site_id=TX0, and actual_delivery_date is from June 1, 2023 to June 30, 2023. Supply Planning adds all the records and divides by 30 days to get the daily demand. Transactional data 247 AWS Supply Chain Inventory level User Guide Supply Planning requires a beginning inventory level to start the planning process. Supply Planning searches for the inventory level under the entity inv_level data entity. Supply Planning searches for a record with the following ﬁelds: • product_id • site_id Supply Planning uses on_hand_inventory to determine the inventory level. Inbound orders Supply Planning uses inbound_order_line to retrieve the in-ﬂight order quantity. If an order is delivered during the planning horizon, the quantity is considered as part of the existing supply. Supply Planning searches for a record under inbound_order_line with the following ﬁelds: • order_receive_date; when missing, use expected_delivery_date • product_id • to_site_id The following are the supported Order Types: PO (Purchase), TO (Transfer), and MO (Production or Manufacturing). Supply Planning uses the quantity_received; when missing, use quantity_conﬁrmed then quantity_submitted to determine the on-order quantity. Transactional data 248 AWS Supply Chain User Guide N-Tier Visibility You can use N-Tier Visibility for the following: • Forecast collaboration allows you to share component level forecasts generated from a supply plan with your trading partners and get their supply commitments. AWS Supply Chain only supports component forecasts generated by Supply Planning to be published to trading partners. • Purchase Order (PO) collaboration allows you to share purchase orders and obtain conﬁrmations from your trading partners on quantities and delivery dates. Purchase order collaboration is enabled only on POs associated with Work Orders that are part of Work Order Insights. Topics • Using N-Tier Visibility for the ﬁrst time • N-Tier Visibility dashboard • Responding to requests as a Partner • N-Tier Visibility settings If you are an AWS Supply Chain partner, you can do the following: 1. Reviewing and accepting partner invites 2. Reviewing and accepting purchase orders 3. Reviewing and accepting forecast commits Using N-Tier Visibility for the ﬁrst time You can use N-Tier Visibility with Supply Planning or Work Order Insights to extend visibility beyond your organization to your external trading partners. This visibility lets you align and conﬁrm orders with suppliers, improving the accuracy of planning and execution processes. Using N-Tier Visibility for the ﬁrst time 249 AWS Supply Chain Note User Guide You can update the Forecast Commits and Purchase Orders response timeline anytime in AWS Supply Chain. On the AWS Supply Chain web application, choose the Settings icon, Organization, Forecast Commits, or Purchase Orders to update. Note When you use N-Tier Visibility for the ﬁrst time, you'll be able to view the onboarding pages that highlight the key features. This helps you to get familiar with the N-Tier Visibility capabilities. 1. Open the AWS Supply Chain web application. 2. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. 3. On the Connect with your partners page, choose Next. You can read through to understand what N-Tier Visibility oﬀers, or choose Next until you get to the Conﬁgure N-Tier Visibility Settings. 4. Under Setup forecast response time, you can do the following: • Set response timeline – Deﬁne the number of days by when the Partner should respond to your data request. • Auto accept responses – Deﬁne a threshold limit for which you can let N-Tier Visibility auto accept responses from the Partner. • Auto reject responses – Deﬁne a threshold limit for which you can let N-Tier Visibility auto reject responses from the Partner. • EDI connection settings – Deﬁne if you would like N-Tier Visibility to use EDI for collaboration on forecast commits with partners. 5. Choose Continue. 6. Under Setup your Purchase Order response timeline, you can do the following: • Set response timeline – Deﬁne the number of days by when the Partner should respond to your purchase order requests. Using N-Tier Visibility for the ﬁrst time 250 AWS Supply Chain User Guide • Auto accept responses – Deﬁne a threshold limit for which you can let N-Tier Visibility auto accept responses from the Partner. • Auto reject responses – Deﬁne a threshold limit for which you can let N-Tier Visibility auto reject responses from the Partner. • EDI connection settings – Deﬁne if you would like N-Tier Visibility to use EDI for collaboration on purchase orders with partners. 7. Choose Finish. N-Tier Visibility dashboard You can user the n-tier
supplychain-ug-070	supplychain-ug.pdf	70	when the Partner should respond to your purchase order requests. Using N-Tier Visibility for the ﬁrst time 250 AWS Supply Chain User Guide • Auto accept responses – Deﬁne a threshold limit for which you can let N-Tier Visibility auto accept responses from the Partner. • Auto reject responses – Deﬁne a threshold limit for which you can let N-Tier Visibility auto reject responses from the Partner. • EDI connection settings – Deﬁne if you would like N-Tier Visibility to use EDI for collaboration on purchase orders with partners. 7. Choose Finish. N-Tier Visibility dashboard You can user the n-tier dashboard to navigate through partner onboarding and collaboration. The N-Tier Visibility dashboard displays the following tabs: • Partner Network – Displays the summary and onboarding status of your partners. You can also invite partners to onboard to N-Tier Visibility. • Purchase Orders – Displays purchase orders and receive conﬁrmations from your partners on quantities and delivery dates. • Forecast Commits – Displays component-level forecasts generated from a supply plan with your partners and supply commitments. N-Tier Visibility dashboard 251 AWS Supply Chain User Guide Partner Network You can view the list of partners that are imported through the AWS Supply Chain data lake into the AWS Supply Chain network. 1. Open the AWS Supply Chain web application. 2. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. 3. Under Partner Overview, you can view the following: Partner Network 252 AWS Supply Chain User Guide • Onboarded – Displays the number of partners who have accepted the invite and are Onboarded into the AWS Supply Chain network. • Pending invites – Displays the number of partners who have not yet accepted the invite. • Expired invites – Displays the number of partners who were invited but whose invite has expired due to no response. • Accept rate – Displays the overall partner invite accept rate. 4. Under Partners, you can view the partners that are imported through the AWS Supply Chain data lake into the AWS Supply Chain network. You can use the Search ﬁeld to search for a speciﬁc partner, and you can use the Show, Product Group or Finished Good dropdown to ﬁlter your partners based on the invite status, partner group, or ﬁnished goods. • Partner name – Displays the partner name. • Partner ID – Displays the partner ID. • DUNS – Displays the supplier DUNS number. • Open Supplier ID – Displays the open partner hub ID. • Contact name – Displays the partner's contact name. • Contact email – Displays the partner's contact email. • Invite date – Displays the date when the partner was invited. • Onboard status – Displays the partner invite status. • Not invited – The partner is yet to be invited. • Pending sign up – The partner is invited but has not yet responded. • Active – The partner has accepted the invite and is active in the AWS Supply Chain network. • Invite expired – The partner was invited but the invite expired due to no response. • Invite declined – The partner declined the invite. 5. To view your partners in a list or map view, use the List or Map toggle button on the right. 6. Choose Invite partners to invite new partners from the dataset into the AWS Supply Chain network. For more information on inviting partners, see Inviting partners. Partner Network 253 AWS Supply Chain Purchase Orders User Guide You can view the list of purchase order data requests that are published to your partners. Purchase orders collaboration can only be enabled through Work Orders. For more information, see Order Planning and Tracking. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. The N-Tier Visibility page appears. 2. Choose the Purchase Orders tab. 3. Under Purchase Orders, you can view the details of all the purchase order data requests that are published to your partners from the generated order insight. You can select any purchase order to review the purchase order details. 4. Select the Status dropdown to ﬁlter purchase orders based on collaboration status. 5. Choose Review for purchase orders with a For review collaboration status. These purchase orders require your review if the partner's response on date or quantity deviate from conﬁgured acceptance threshold. The Purchase Order details page appears. 6. Under Review the Purchase Order Update, review the purchase order quantity and delivery date submitted by the partner, and then you can accept or reject the response. You can read the reason for the update under Update details from the partner. 7. To accept the purchase order update, choose Accept response. The Accept update window appears. Choose Accept update. 8. To reject the purchase order update, choose Reject and send.
supplychain-ug-071	supplychain-ug.pdf	71	For review collaboration status. These purchase orders require your review if the partner's response on date or quantity deviate from conﬁgured acceptance threshold. The Purchase Order details page appears. 6. Under Review the Purchase Order Update, review the purchase order quantity and delivery date submitted by the partner, and then you can accept or reject the response. You can read the reason for the update under Update details from the partner. 7. To accept the purchase order update, choose Accept response. The Accept update window appears. Choose Accept update. 8. To reject the purchase order update, choose Reject and send. The Reject PO update and send feedback window appears. Enter the rejection details and choose Reject and send. The purchase orders will be sent back to your partner and provided an updated response. Purchase Orders 254 AWS Supply Chain User Guide Viewing purchase orders in EDI format Note You will only see this conﬁguration if you selected Yes to use EDI Connection Settings when setting up N-Tier Visibility. You can view the Purchase Orders data received through EDI. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. The N-Tier Visibility page appears. 2. Choose the Purchase Orders tab. The Conﬁrm or Update Pending Purchase Orders page appears. 3. From the Actions drop-down, choose Export EDI data. The .json ﬁle with the purchase orders information is downloaded to your local computer and also downloaded to the Amazon S3 folder created as part of the outbound connection setup for Supply Planning. Forecast Commits You can view the forecast commit data requests that are published to your partners. These data requests are triggered from AWS Supply Chain supply planning. For more information, see Supply Planning. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. The N-Tier Visibility page appears. 2. Choose the Forecast Commits tab. The Forecast Commit page appears. 3. Under Forecast commit, you can view the details of all the forecast data requests from the generated supply plan. You can select any forecast commit to review the forecast commit details. Forecast Commits 255 AWS Supply Chain User Guide 4. Select the Status, Partner, or Site dropdown to ﬁlter the forecast commits based on the collaboration status, partner, or site. 5. Choose Review for forecast commits with a For review collaboration status. The Forecast commit details page appears. 6. Under Review the Forecast Commit update, review the committed forecast and deviation. You can decide to accept or reject the response, or you can decline and close the forecast commit. You can read the reason for the update under Latest update details from the partner. 7. If you want to accept the forecast commit update, choose Accept response. The Accept update window appears. Choose Accept update. 8. If you want to reject the forecast commit update, choose Reject and send. The Reject Forecast update and send feedback window appears. Enter the rejection details and choose Reject and send. 9. If you want to decline and close the forecast commit request, choose Decline and close. The Decline and close Forecast Commit window appears. Enter the details and choose Decline and close. Viewing forecast commits when EDI is enabled Note You will only see this conﬁguration if you selected Yes to use EDI Connection Settings when setting up N-Tier Visibility. You can only export forecast commits data in EDI format. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. The N-Tier Visibility page appears. 2. Choose the Forecast Commits tab. The Conﬁrm or Update Forecast Commits page appears. 3. From the Actions drop-down, choose Export EDI data. Forecast Commits 256 AWS Supply Chain User Guide The .json ﬁle with the forecast commits information is downloaded to your local computer and also downloaded to the Amazon S3 folder created as part of the outbound connection setup for Supply Planning. Responding to requests as a Partner As a Partner, you can accept or decline Partner requests, review purchase orders and forecast commits. Reviewing and accepting partner invites As a Partner, you should have received an email to join the AWS Supply Chain network. Select the link on the email to review and accept the invite. Note When you are accepting invites for the ﬁrst time, you can view the onboarding pages that highlight the key features. This helps you to get familiar with the AWS Supply Chain capabilities. 1. On the AWS Supply Chain login page, enter the username. You will be sent a veriﬁcation code to the same email address from which you received the invite to join. 2. On the Additional veriﬁcation required page, under Veriﬁcation code, enter the veriﬁcation code from the email. 3. On the Choose your password page, create a password to sign into
supplychain-ug-072	supplychain-ug.pdf	72	to review and accept the invite. Note When you are accepting invites for the ﬁrst time, you can view the onboarding pages that highlight the key features. This helps you to get familiar with the AWS Supply Chain capabilities. 1. On the AWS Supply Chain login page, enter the username. You will be sent a veriﬁcation code to the same email address from which you received the invite to join. 2. On the Additional veriﬁcation required page, under Veriﬁcation code, enter the veriﬁcation code from the email. 3. On the Choose your password page, create a password to sign into AWS Supply Chain. 4. Choose Create AWS Builder ID. 5. On the Complete your user proﬁle page, the ﬁrstname and lastname are auto-populated. Enter your Job title and timezone. 6. Choose Next. 7. On the Let's add your organization's information page, choose Upload logo to upload your organization's logo and enter the Organization name. 8. Choose Complete setup. Responding to requests as a Partner 257 AWS Supply Chain User Guide The N-Tier Visibility page appears. 9. On the N-Tier Visibility page, under Partner Network, you can view all the invites that you have received. 10. Select a partner to accept or decline the invite. The N-Tier Visibility page is displayed with the partner details. 11. Choose Accept connection. You will see the Invite accepted message. Note If you choose to decline the invite, you must provide a reason on the Decline connection invite page. Reviewing and accepting purchase orders As a Partner, you should have received an email to review the purchase orders. Select the link on the email to review and accept the purchase orders. Note When you are accepting invites for the ﬁrst time, you'll be able to view the onboarding pages that highlight the key features. This helps you to get familiar with the AWS Supply Chain capabilities. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. The N-Tier Visibility page appears. 2. Choose the Purchase Orders tab. 3. Under Review Purchase Orders, you can view all the purchase orders that must be reviewed and conﬁrmed. 4. Choose Conﬁrm to accept the purchase order update. 5. Choose Update to update the purchase order quantity and delivery date. Reviewing and accepting purchase orders 258 AWS Supply Chain User Guide The Update the Purchase Order window appears. Enter the reason for the purchase order and details, and choose Conﬁrm. 6. You can choose Collaboration history to read the purchase order updates and reason for the purchase order. Reviewing and accepting forecast commits As a Partner, you should have received an email to review the forecast commits. Select the link on the email to respond to the request. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose N-Tier Visibility. The N-Tier Visibility page appears. 2. Choose the Forecast Commits tab. 3. Under Review Forecast Commits, you can view all the forecasts based on the status. • Forecast Requests – Displays all the forecast commit requests that are still pending review or awaiting response. • Forecasts Import – Displays all the forecasts that are imported. • Forecasts Export – Displays all the forecasts that are exported to edit oﬄine. After you update, import the changes back. 4. Select the Status, Requester, or Site dropdown to ﬁlter the forecasts based on the collaboration status, requester, or site. 5. Choose Review for forecast commits with a For review collaboration status. The Forecast commit details page appears. 6. Select the blue link on the speciﬁc date to edit the forecast, or you can bulk edit the committed forecast for the complete forecast timeline. The Edit quantity page appears. Under the Change dropdown, select the reason for the edit, and under Quantity, enter the quantity. 7. Choose Save and update. 8. Choose Save and conﬁrm to accept the forecast commit. 9. Choose Decline to decline the forecast commit request. Reviewing and accepting forecast commits 259 AWS Supply Chain User Guide N-Tier Visibility settings You can update the forecast commits and purchase orders response settings in AWS Supply Chain. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. The Settings page appears. 2. Choose Organization, Forecast Commits, or Purchase Orders, depending on what you want to edit. For information on how to update the settings, see Using N-Tier Visibility for the ﬁrst time. N-Tier Visibility settings 260 AWS Supply Chain User Guide Sustainability Using Sustainability, you can request data from your partners who have accepted your invitation to join your network. You can use the Simple reporting feature to request diﬀerent types of data from your partner network. You can enter detailed information on the type of data you are requesting from your partners. Responses to your data requests
supplychain-ug-073	supplychain-ug.pdf	73	Settings page appears. 2. Choose Organization, Forecast Commits, or Purchase Orders, depending on what you want to edit. For information on how to update the settings, see Using N-Tier Visibility for the ﬁrst time. N-Tier Visibility settings 260 AWS Supply Chain User Guide Sustainability Using Sustainability, you can request data from your partners who have accepted your invitation to join your network. You can use the Simple reporting feature to request diﬀerent types of data from your partner network. You can enter detailed information on the type of data you are requesting from your partners. Responses to your data requests are downloaded to your Amazon S3 bucket everyday at 9 am. Topics • Using Sustainability for the ﬁrst time • Sustainability dashboard • Responding to requests as a Partner • Sustainability settings If you are a AWS Supply Chain partner, you can do the following: 1. Reviewing and accepting partner invites 2. Reviewing or responding to data requests Using Sustainability for the ﬁrst time You can use Sustainability to request and collect carbon emissions data and other compliance data from suppliers. Note When you use Sustainability for the ﬁrst time, you'll be able to view the onboarding pages that highlight the key features. This helps you to get familiar with the Sustainability capabilities. 1. Open the AWS Supply Chain web application. 2. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. 3. On the Compliance and Sustainability page, choose Next. Using Sustainability for the ﬁrst time 261 AWS Supply Chain User Guide You can read through the page to understand what Sustainability oﬀers, or you can choose Next to go the Sustainability dashboard. Sustainability dashboard You can invite partners by using the AWS Supply Chain data lake connectors and by mapping the partner information to Partners or Partner's point-of-contact from Amazon S3 or other ERP systems. Make sure that the partner list or partner point-of-contact does not contain duplicate information and that it is up-to-date before you upload the partner information dataset. You can also manually add and invite partners. For more information on how to upload your data, see Data lake. Sustainability dashboard 262 AWS Supply Chain User Guide Partner Network You can view the partners in your scn network. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. The Sustainability page appears. 2. On the Sustainability dashboard page, choose the Partner Network tab. Partner Network 263 AWS Supply Chain User Guide • Getting Started – You can choose Invite Partners to invite Partners into your AWS Supply Chain network, and you can choose Create data requests to request data from your partners. • Partner Overview – The Onboarding metrics section displays the partners who are currently onboarding, invites that are pending acceptance by partners, expired invites and acceptance rate. The Data requests section displays data request details from the partners, including the status of data requests. • Partners – You can view the list of partners that were imported through data lake, or you can invite new partners. Under Partners, you can use the Search ﬁeld to search for a speciﬁc partner, and you can use the Show dropdown to ﬁlter your partners based on invite status. • Partner name – Displays the partner name. • Partner ID – Displays the partner ID. The partner ID link to your source system. • Supplier DUNS – Displays the partner DUNS. • Open Supplier ID – Displays the open partner hub ID. • Contact name – Displays the partner's contact name. • Contact email – Displays the partner's contact email. • Invite date – Displays the date when the partner was invited. • Portal status – Displays the status of the invitation. • Not invited – Partner is not yet invited. • Pending sign up – Partner is invited but hasn't responded to the invite. • Active – Partner has accepted the invite and is active. Partner has to be active to receive data requests. • Invite expired – Partner was sent the invite but the invite expired without any response. • Invite declined – Partner declined the invitation. You can choose a partner under Partner name to view partner details and details of the data request that are speciﬁc to the partner. To resend a partner invite, choose a partner with an Expired portal status and, under the Actions dropdown, choose Resend invite. Partner Network 264 AWS Supply Chain Inviting partners User Guide You can invite or add new partners from the dataset into the AWS Supply Chain network. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. The Sustainability page appears. 2. Choose the Partner Network tab. 3. On the Partner Network page, choose Invite partners. The Invite Partners page appears. 4. Under Select
supplychain-ug-074	supplychain-ug.pdf	74	and details of the data request that are speciﬁc to the partner. To resend a partner invite, choose a partner with an Expired portal status and, under the Actions dropdown, choose Resend invite. Partner Network 264 AWS Supply Chain Inviting partners User Guide You can invite or add new partners from the dataset into the AWS Supply Chain network. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. The Sustainability page appears. 2. Choose the Partner Network tab. 3. On the Partner Network page, choose Invite partners. The Invite Partners page appears. 4. Under Select partners to invite, to add an existing partner, under Partner name, select the partner from the list. 5. To add a new partner, choose Add a partner manually. On the Enter new partner details page, enter the Partner details and Account administrator information, and then choose Add new partner. 6. On the Select partners to invite page, you will see the partners that you added manually under Manually entered partners. 7. Choose Continue. 8. On the Review invite message, choose Add custom text to add a customized message to the partner invite. Partner Network 265 AWS Supply Chain User Guide 9. Choose Save content. 10. Choose Send Invites. Data requests You can request data from your partners that have accepted your invite and are in the AWS Supply Chain network. The Portal status under Partners must display Active before you request data. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. The Sustainability page appears. 2. Choose the Data Requests tab. You can view the current partners and the data request status, or you can create a new data request. 3. Under Data Requests, you can view the overall status of your data requests to partners. • Total requests – Displays the total number of data requests that you have submitted. • Total partners – Displays the total number of suppliers from which you have requested data. • In progress – The data request has been created or will be worked on by the data provider (supplier). Data requests 266 AWS Supply Chain User Guide • Submitted – Displays the data requests submitted to partners. • Rework requested – Displays the number of data request responses that you rejected and sent back to the partner to edit their response and resubmit. • Reviewed – Displays the total number of data requests reviewed by partners. • Declined – Displays the number of partners who declined your data request. • Canceled – Displays the number of data requests that have been canceled because they are not needed. 4. You can use the Search ﬁeld to search for a partner. 5. You can use the Show dropdown to ﬁlter partners depending on the status of the data request. 6. Choose Due date risk to view all the partners who haven't responded to the data request and are nearing the due date. 7. Choose Overdue to view all the partners who haven't responded to the data request and the due date has passed. 8. From the Partner list, you can choose a partner with a Pending status, and you can use the Actions dropdown to send a reminder. Creating data requests You can use the simple reporting template to request any type of data from your partners. For example, you can request compliance information such as product brochure, safety report, or lab testing results of a product. You can also upload your own form for the partner to download, update information, and repload to answer the data requst. To create a data request, do the following: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. The Sustainability page appears. 2. Choose the Data Requests tab. 3. On the Data Requests page, choose Create data request. The Create data requests page appears. Data requests 267 AWS Supply Chain User Guide 4. On the Create data requests page, under Select data request type, select the data request type. 5. Under Select data request options, enter the details for the data request. 6. Under Select the task input options, select Ask for a text response to receive the data request response in a text ﬁeld. 7. Select Ask for a ﬁle response if you want your partners to upload a response ﬁle to your data request. 8. Choose Save template to save the details you entered and reuse again for additional data requests (due date and notes ﬁeld will not be saved, as these change per data request). The Save template page appears. 9. Enter the name and description for your new template and choose Save template. Make sure you enter a name and description that is meaningful since you will use the name and description to
supplychain-ug-075	supplychain-ug.pdf	75	the data request response in a text ﬁeld. 7. Select Ask for a ﬁle response if you want your partners to upload a response ﬁle to your data request. 8. Choose Save template to save the details you entered and reuse again for additional data requests (due date and notes ﬁeld will not be saved, as these change per data request). The Save template page appears. 9. Enter the name and description for your new template and choose Save template. Make sure you enter a name and description that is meaningful since you will use the name and description to ﬁnd the template, understand it's usage, and reuse to request data. Under Saved templates, you will see the template listed under Data request type. Data requests 268 AWS Supply Chain User Guide 10. Choose Continue to send the data request. 11. Choose Cancel if you only want to create a new template for you and your team. The create data request ﬂow will be canceled. 12. On the Select partners to request data page, under Partner name, select the partner to request data. You can choose from the partners listed under Partner name or invite a new partner. For information on how to invite partners, see Inviting partners. 13. Under Selected partners, review the partner details and choose Send Request. The invited partner will receive an email invite requesting data. Data requests examples Here are some examples on how you can structure the Simple Reporting data form to meet your needs. Collect compliance documents from partners To collect compliance documents from your partners, you can do the following: • Data request name – Q1 2023 Sample Compliance Document Collection • Additional Notes – We are collecting [name of document] from our suppliers to fulﬁll our Q1 2023 compliance documents needed for [purpose for collecting documents] for the products we buy from you. • Task instructions – Please upload [name of document] for the products we have purchased from you in Q1 2023. The information on this document should be similar to the reference document we have uploaded for you to review. In the Task Response ﬁeld, provide us any comments you have about the document provided. • Ask for a text response – Select No to make this ﬁeld mandatory. Data requests 269 AWS Supply Chain User Guide • Ask for a ﬁle response – Select Yes to make this ﬁeld mandatory. Collect emissions documents To collect emissions information, you can do the following: • Data request name – 2023 Emissions Collection • Additional Notes – To achieve our Climate Pledge Goals, we are collecting emissions data so that we have the information needed to understand our carbon footprint. Providing us with carbon data on the services your provide are needed for us to fully disclose our carbon emission. • Task instructions – Please download the provided Emissions form, answer the questions in the form, and upload it when complete. Please ensure that you are only providing emissions information for the year 2023 and ensure that the form is signed. • Ask for a text response – Not selected • Ask for a ﬁle response – Select Yes to make this ﬁeld mandatory. Data requests 270 AWS Supply Chain User Guide Collect pilot ESG data To collect pilot ESG data, you can do the following: • Data request name – ESG Pilot Questionnaire V1 • Additional Notes – Thank you for agreeing to pilot our ESG questionnaire. In Q2 next year, we must disclose our impact on environmental and social indicators to meet compliance requirements. We need information from you so that we can complete our report. • Task instructions – Download the provided questionnaire, answer the questions in the form, and upload it when complete. Indicate in the task response box how much time it took you to complete the questionnaire. • Ask for a text response – Select Yes to make this ﬁeld mandatory. • Ask for a ﬁle response – Select Yes to make this ﬁeld mandatory. Data requests 271 AWS Supply Chain User Guide Emission data forms You can use the emission data forms to collect scope 1, 2, and 3 emissions from your partner network at the granularity level of a country or facility. The following are the data request emission forms available. • Supplier Emissions by country • Supplier Emissions by facility Additionally, you can use the Supplier Emissions by facility form to request address information for each facility. These forms can also be used to collect revenue information about products or services provided by the partner that can be used to measure year over year changes per products produced and sold. You can also use these forms to conﬁgure the sections to show or hide for your partners. You can also set the
supplychain-ug-076	supplychain-ug.pdf	76	at the granularity level of a country or facility. The following are the data request emission forms available. • Supplier Emissions by country • Supplier Emissions by facility Additionally, you can use the Supplier Emissions by facility form to request address information for each facility. These forms can also be used to collect revenue information about products or services provided by the partner that can be used to measure year over year changes per products produced and sold. You can also use these forms to conﬁgure the sections to show or hide for your partners. You can also set the hierarchical level of information for emissions collection to optional or mandatory when setting up the form. Data requests 272 AWS Supply Chain User Guide To send a data request emission form, follow the procedure below: 1. Conﬁgure the data request type and the data request options. For information on how to conﬁgure the data request type and option, see Creating data requests. 2. Under Reporting timeline, enter the reporting year of your partner. 3. Under Electricity and scope emissions conﬁguration, select the top-level headings to be displayed for the partner. For example, in the below screen shot, Scope 3 emissions is not selected and will not be displayed to the partner. Once you select a section or a sub-section to request emission information from your partner, it becomes mandatory for your partner to provide information for all the sections selected. For example, in the screen shot below, under Scope 1 > Type 1 - Stationary combustion emissions total, there are two sub-types that are selected and your partner must provide information for these ﬁelds. Data requests 273 AWS Supply Chain User Guide 4. Select Product Categories to request product category information from your partner on volumes manufactured, sold, and revenue. Data requests 274 AWS Supply Chain User Guide 5. Under Add product categories, you can select a category from a predeﬁned industry list, or choose your own products. For example, in the below screen shot, there are four products and one unit of measure added. Your partner will provide details for these products as applicable to them. 6. Under Add product category unit of measure, you can select a category from a predeﬁned industry list, or choose your own unit of measure. 7. Under Additional questions, you can upload additional documents with supplementary questions to ask your partner. Make sure you enter the details of the supplementary questions in the data request description for the partner to understand and answer the supplementary questions. Transportation emission forms You can use the transport emission Global Logistics Emissions Council (GLEC) data forms to collect the emission reports from transportation routes by parcels delivered or by account. The following are the transportation emission request forms available. • Transportation Emissions (GLEC) by Parcel v0.1 – You can collect emissions from transport routes in accordance with the GLEC standard for parcels delivered. • Transport Emissions (GLEC) by Account – You can collect emissions from transportation routes in accordance with the GLEC standard per account. To send a transport emissions data request form, follow the procedure below: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose Sustainability. The Sustainability page appears. 2. Choose the Data Requests tab. Data requests 275 AWS Supply Chain User Guide 3. On the Data Requests page, choose Create data request. The Create data requests page appears. 4. Depending on your request type, under Data request type, choose Transport Emissions (GLEC) by Parcel v0.1 or Transport Emissions (GLEC) by Account 5. Under Transport Emissions (GLEC) by Parcel v0.1, enter a name, due date, and description for the data request. 6. Under Data request information, the .csv template to request information from the partner is auto-populated. You can add any additional notes. 7. Choose Continue. 8. Under Select partners to request data, select the partners you would like to request transport emissions information. 9. Choose Continue. 10. Under Selected partners, choose Send data request. 11. If the formatting in the .csv ﬁle is not in the correct format, the system automatically changes the data request Status to Rework requested. You can select the data request to view the information that needs to be reworked. Data requests 276 AWS Supply Chain User Guide Responding to requests as a Partner As a Partner, you can accept or decline Partner requests, review and respond to data requests. Reviewing or responding to data requests You will receive a daily digest letting you know if you have received any data requests within the last 24 hour period. Select the link in the email to view any new data requests. 1. On the Sustainability page, under Data Requests, you will see all the data requests from your partners. 2. Under Title, choose the data request that
supplychain-ug-077	supplychain-ug.pdf	77	needs to be reworked. Data requests 276 AWS Supply Chain User Guide Responding to requests as a Partner As a Partner, you can accept or decline Partner requests, review and respond to data requests. Reviewing or responding to data requests You will receive a daily digest letting you know if you have received any data requests within the last 24 hour period. Select the link in the email to view any new data requests. 1. On the Sustainability page, under Data Requests, you will see all the data requests from your partners. 2. Under Title, choose the data request that you want to view or take action on. 3. On the Sustainability page, under Please complete the following sections, review and provide the requested information. 4. Choose Submit response. 5. You can choose to Download the data request. The download option downloads the template requested by the partner. 6. You can also choose to Decline to answer the data request. You will be prompted to provide a reason for choosing to decline to answer. Responding to requests as a Partner 277 AWS Supply Chain User Guide You can export data in bulk and the data responses are exported every 24 hours to your Amazon S3 bucket. The folder structure would be s3://aws-supply-chain-data-Instance ID/ export/DisclosureDataResponse/YYYY/MM/DD/Execution ID. Under your Amazon S3 folder, you will ﬁnd an audit history and a data response ﬁle for each data type. Reviewing and accepting partner invites As a Partner, you should have received an email to join the AWS Supply Chain network. Select the link on the email to review and accept the invite. Note When you are accepting invites for the ﬁrst time, you can view the onboarding pages that highlight the key features. This helps you to get familiar with the AWS Supply Chain capabilities. 1. On the AWS Supply Chain login page, enter the username which is the partner's email address. You will be sent a veriﬁcation code to the same email you received the invite to join. 2. On the Additional veriﬁcation required page, under Veriﬁcation code, enter the veriﬁcation code from the email. Note If you plan to use the same computer to log into AWS Supply Chain, after you use the veriﬁcation code to access AWS Supply Chain for the ﬁrst time, choose Trusted device on your computer to access AWS Supply Chain without the veriﬁcation code the next time. 3. On the Choose your password page, create a password to sign into AWS Supply Chain. 4. On the Complete your user proﬁle page, the ﬁrstname and lastname are auto-populated. Enter your title and timezone. 5. Choose Next. 6. On the Let's add your organization's information page, choose Upload logo to upload your organization's logo, and then enter the Organization name. 7. Choose Complete setup. Reviewing and accepting partner invites 278 AWS Supply Chain User Guide The Sustainability page displays. 8. On the Sustainability page, under Partner Network, you can view all the invites that you have received. 9. Review and select a partner to accept or decline the invite. The Sustainability page displays with the partner details. 10. Choose Accept connection. You will see the Invite accepted message. Note If you choose to decline the invite, you must provide a reason on the Decline connection invite page. Reviewing or responding to emission data forms After you receive an emission data form request, you will view the request details and check the collaboration history. 1. Under Add country, enter the countries where you have facilities and products within those facilities. Reviewing or responding to emission data forms 279 AWS Supply Chain User Guide 2. Choose Add emission information to add emission information for each country. 3. Enter the emission information. All ﬁelds are mandatory. Reviewing or responding to transportation (GLEC) emission data forms After you receive a transportation emission data form request, you will view the request details and check the collaboration history. Reviewing or responding to transportation (GLEC) emission data forms 280 AWS Supply Chain User Guide Under Transport Emissions by Parcel, download the .csv ﬁles, populate the .csv with the transport emissions, and upload the ﬁle. Choose Submit. Make sure the information you populate in the .csv ﬁle is in the correct format. If not, you will receive a rework request explaining the issue in the .csv ﬁle. Sustainability settings To enhance your account security, you can use multifactor authentication. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. The Settings page appears. 2. Choose Account Proﬁle. 3. Under multifactor authentication, choose Multifactor Authentication Setup. You will be redirected to AWS Access Portal. For information on AWS Access Portal, see Using the AWS access portal.. Sustainability settings 281 AWS Supply Chain User Guide Amazon Q in AWS Supply Chain Note Powered
supplychain-ug-078	supplychain-ug.pdf	78	is in the correct format. If not, you will receive a rework request explaining the issue in the .csv ﬁle. Sustainability settings To enhance your account security, you can use multifactor authentication. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. The Settings page appears. 2. Choose Account Proﬁle. 3. Under multifactor authentication, choose Multifactor Authentication Setup. You will be redirected to AWS Access Portal. For information on AWS Access Portal, see Using the AWS access portal.. Sustainability settings 281 AWS Supply Chain User Guide Amazon Q in AWS Supply Chain Note Powered by Amazon Bedrock: AWS implements automated abuse detection. Because Amazon Q in AWS Supply Chain is built on Amazon Bedrock, users can take full advantage of the controls implemented in Amazon Bedrock to enforce safety, security, and the responsible use of artiﬁcial intelligence (AI). Amazon Q in AWS Supply Chain is an interactive generative artiﬁcial intelligence (GenAI) assistant that helps you operate your supply chain more eﬃciently by analyzing the data in your AWS Supply Chain Data Lake, providing important operational and ﬁnancial insights, and answering immediate supply chain questions. For example, you can ask Amazon Q in AWS Supply Chain, "What is my demand forecast over the next two weeks for Apples in Austin?" and you will get an accurate answer within seconds. Topics • Enabling Amazon Q in AWS Supply Chain • Creating and assigning custom user roles to access Amazon Q in AWS Supply Chain • Using Amazon Q in AWS Supply Chain • Sample questions you can ask Amazon Q in AWS Supply Chain • Cross-Region calls with Amazon Q in AWS Supply Chain Enabling Amazon Q in AWS Supply Chain Note Only an AWS Supply Chain administrator can enable Amazon Q in AWS Supply Chain. To enable Amazon Q in AWS Supply Chain, perform the following procedure: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Organization, choose Organization Proﬁle. Enabling Amazon Q in AWS Supply Chain 282 AWS Supply Chain User Guide The Organization Proﬁle page appears. 3. Under Enable access for Amazon Q..., slide the Amazon Q in AWS Supply Chain button to enable Amazon Q in AWS Supply Chain and ask questions regarding your supply chain. 4. Choose Save. The Conﬁrm Amazon Q in AWS Supply Chain access window appears. 5. Choose Acknowledge. The Amazon Q dialog window should automatically appear on the right side of the page. You can hide or unhide the page by choosing the Amazon Q icon. Prerequisites for existing AWS Supply Chain users Note If your AWS Supply Chain instance was created before the Amazon Q in AWS Supply Chain release, you will need to follow the procedure below to update the instance permissions. To update the instance role in the IAM console, perform the following steps: 1. Make sure all the permissions listed under KMS policy are added to the KMS key policy used in the AWS Supply Chain instance. Prerequisites for existing AWS Supply Chain users 283 AWS Supply Chain User Guide 2. In the IAM console, ﬁnd the instance role with the AWS Supply Chain InstanceId. You can ﬁnd the AWS Supply Chain InstanceId in the AWS Supply Chain console. 3. Attach the following policy as an inline policy to the role. { "Version": "2012-10-17", "Statement": [ { "Sid": "AccessKmsToEnableAscQ", "Effect": "Allow", "Action": "kms:CreateGrant", "Resource": "{{kmsKeyArn}}", "Condition": { "ForAllValues:StringEquals": { "kms:GrantOperations": [ "Encrypt", "Decrypt", "GenerateDataKey", "GenerateDataKeyWithoutPlaintext", "DescribeKey" ] }, "StringLike": { "kms:ViaService": "scn..amazonaws.com" }, "Bool": { "kms:GrantIsForAWSResource": true } } }, { "Sid": "AccessKmsToInteractWithAscQ", "Effect": "Allow", "Action": [ "kms:Decrypt", "kms:DescribeKey", "kms:GenerateDataKey" ], "Resource": "{{kmsKeyArn}}", "Condition": { "StringLike": { "kms:ViaService": "scn..amazonaws.com" Prerequisites for existing AWS Supply Chain users 284 AWS Supply Chain User Guide } } } ] } Replace the kmsKeyArn with the actual AWS KMS Key Arn used in the AWS Supply Chain instance. Creating and assigning custom user roles to access Amazon Q in AWS Supply Chain To create and assign custom user roles in AWS Supply Chain, perform the following procedure: Note If you are an AWS Supply Chain administrator or have a custom user role with administrator privileges, you can access Amazon Q across all datasets without any additional permission requirements after Amazon Q is enabled on your account. This section is only applicable if you want to grant Amazon Q access permissions to non-administrator users. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Users and Permissions, choose Permission Roles. The Permission Roles page appears. 3. Choose Create New Role. The Manage Permission Role page appears. 4. Under Role Name, enter a name for the role. 5. Choose the module or administrator access for the permission role you are creating. Creating
supplychain-ug-079	supplychain-ug.pdf	79	Amazon Q across all datasets without any additional permission requirements after Amazon Q is enabled on your account. This section is only applicable if you want to grant Amazon Q access permissions to non-administrator users. 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Users and Permissions, choose Permission Roles. The Permission Roles page appears. 3. Choose Create New Role. The Manage Permission Role page appears. 4. Under Role Name, enter a name for the role. 5. Choose the module or administrator access for the permission role you are creating. Creating and assigning custom user roles to access Amazon Q in AWS Supply Chain 285 AWS Supply Chain Note User Guide You must choose an administrator role or AWS Supply Chain module to enable Amazon Q in AWS Supply Chain. Amazon Q in AWS Supply Chain cannot be enabled independently. 6. Slide the Amazon Q in AWS Supply Chain button to create a user role to view and interact with Amazon Q in the AWS Supply Chain web application. 7. Under Additional Data Permissions, view the datasets that are automatically listed as per the user role you selected. 8. Choose Save. Updating existing custom user roles to access Amazon Q in AWS Supply Chain To update an existing user permission role in AWS Supply Chain, perform the following procedure: 1. In the left navigation pane on the AWS Supply Chain dashboard, choose the Settings icon. 2. Under Users and Permissions, choose Permission Roles. The Permission Roles page appears. 3. Under Role, select the role for which you would want to add the Amazon Q in AWS Supply Chain permission role and choose the Edit icon. The Manage Permission Role page appears. 4. Slide the Amazon Q in AWS Supply Chain button to add Amazon Q in AWS Supply Chain permission role. 5. Choose Save. Using Amazon Q in AWS Supply Chain After enabling Amazon Q in AWS Supply Chain, perform the following procedure: 1. On the AWS Supply Chain dashboard, choose the Amazon Q icon. Updating existing custom user roles to access Amazon Q in AWS Supply Chain 286 AWS Supply Chain User Guide The Amazon Q dialog window should automatically appear on the right side of the page. You can hide or unhide the page by choosing the Amazon Q icon. 2. Choose a question from the list of sample questions displayed. Using Amazon Q in AWS Supply Chain 287 AWS Supply Chain User Guide You can ask any questions regarding AWS Supply Chain from anywhere in the web application. Amazon Q in AWS Supply Chain will customize your answers using the context from the page you are in to provide more accurate responses. You can start with the default prompted questions or ask your own question. Sample questions you can ask Amazon Q in AWS Supply Chain Sample questions you can ask Amazon Q in AWS Supply Chain 288 AWS Supply Chain User Guide AWS Supply Chain module Sample question Sample answer Demand Planning Create demand plan summary Note Make sure the demand plan is published before using Amazon Q in Demand Planning. How to improve forecast accuracy? Sample questions you can ask Amazon Q in AWS Supply Chain 289 AWS Supply Chain User Guide AWS Supply Chain module Sample question Sample answer Supply Planning What products are at a stock- out risk? What is current lead time for all products? Sample questions you can ask Amazon Q in AWS Supply Chain 290 AWS Supply Chain User Guide AWS Supply Chain module Sample question Sample answer Are any purchase orders delayed? What products have unmet demand? Sample questions you can ask Amazon Q in AWS Supply Chain 291 AWS Supply Chain User Guide AWS Supply Chain module Sample question Sample answer Work Order Insights Which campaigns have work orders at watch status? What suppliers are contribut ing to current work orders What work orders may need to be rescheduled due to delays? Cross-Region calls with Amazon Q in AWS Supply Chain Amazon Q in AWS Supply Chain has a dependency on Amazon Kendra for retrieving relevant search results from public documentation that may be used to answer your questions. Amazon Kendra is available in a subset of AWS Regions that Amazon Q in AWS Supply Chain supports. Amazon Q in AWS Supply Chain calls Amazon Kendra local endpoints when Amazon Kendra is available locally in an AWS Region. When Amazon Kendra is not available locally, Amazon Q in AWS Supply Chain calls Amazon Kendra’s endpoints in a diﬀerent AWS Region. In these cross-region calls, Amazon Q in AWS Supply Chain may send your prompts to Amazon Kendra. Amazon Q in AWS Supply Chain Region Amazon Kendra Region Region Code Region Name Region Code Region Name eu-central-1 Europe (Frankfurt) eu-west-1
supplychain-ug-080	supplychain-ug.pdf	80	Amazon Kendra is available in a subset of AWS Regions that Amazon Q in AWS Supply Chain supports. Amazon Q in AWS Supply Chain calls Amazon Kendra local endpoints when Amazon Kendra is available locally in an AWS Region. When Amazon Kendra is not available locally, Amazon Q in AWS Supply Chain calls Amazon Kendra’s endpoints in a diﬀerent AWS Region. In these cross-region calls, Amazon Q in AWS Supply Chain may send your prompts to Amazon Kendra. Amazon Q in AWS Supply Chain Region Amazon Kendra Region Region Code Region Name Region Code Region Name eu-central-1 Europe (Frankfurt) eu-west-1 Europe (Ireland) Cross-Region calls with Amazon Q in AWS Supply Chain 292 AWS Supply Chain User Guide Data entities and columns used in AWS Supply Chain This chapter describes the data entities and columns supported by each AWS Supply Chain module. Note The data entities listed in this chapter are required for each AWS Supply Chain module. For data entities required for Data Lake ingestion, see Data entities supported in AWS Supply Chain. Topics • Sustainability • N-Tier Visibility • Supply Planning • Insights • Order Planning and Tracking • Demand Planning Sustainability The table below list the data entities and columns used by Sustainability for partner invitations and onboarding. Note How to read the table: • Required – The column name is mandatory in your dataset and you must populate the column name with values. • Optional – The column name is optional. For enhanced feature output, it is recommended to add the column name with values. • Not required – Data entity not required. Sustainability 293 AWS Supply Chain User Guide Data entity Column trading_p artner id tpartner_type geo_id eﬀ_end_date Is the column used by Sustainability? Required Required – When you ingest data from SAP or EDI, the default value for string is SCN_RESERVED_NO_VA LUE_PROVIDED. When you upload data using the Amazon S3 connector, you must enter a value or use SCN_RESERVED_NO_VA LUE_PROVIDED for successful ingestion. Required – When you ingest data from SAP or EDI, the default value for string is SCN_RESERVED_NO_VA LUE_PROVIDED. When you upload data using the Amazon S3 connector, you must enter a value or use SCN_RESERVED_NO_VA LUE_PROVIDED for successful ingestion. Required – You must enter a value for eﬀ_start_date and eﬀ_end_date. If you don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. Sustainability 294 AWS Supply Chain User Guide Data entity Column eﬀ_start_date trading_p artner_poc tpartner_id email N-Tier Visibility Is the column used by Sustainability? Required – You must enter a value for eﬀ_start_date and eﬀ_end_date. If you don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. Required Required The table below list the data entities and columns used by N-Tier Visibility. Note How to read the table: • Required – The column name is mandatory in your dataset and you must populate the column name with values. • Optional – The column name is optional. For enhanced feature output, it is recommended to add the column name with values. • Not required – Data entity not required. Data entity Column trading_p artner id N-Tier Visibility Is the column used by N-Tier Visibility? Required 295 AWS Supply Chain User Guide Data entity Column description company_id tpartner_type geo_id Is the column used by N-Tier Visibility? Required Optional Required – When you ingest data from SAP or EDI, the default value for string is SCN_RESERVED_NO_VA LUE_PROVIDED. When you upload data using the Amazon S3 connector, you must enter a value or use SCN_RESERVED_NO_VA LUE_PROVIDED for successful ingestion. Required – When you ingest data from SAP or EDI, the default value for string is SCN_RESERVED_NO_VA LUE_PROVIDED. When you upload data using the Amazon S3 connector, you must enter a value or use SCN_RESERVED_NO_VA LUE_PROVIDED for successful ingestion. N-Tier Visibility 296 AWS Supply Chain User Guide Data entity Column eﬀ_end_date eﬀ_start_date trading_p artner_poc product product_h ierarchy site sourcing_ rules tpartner_id email id id id sourcing_rule_id Is the column used by N-Tier Visibility? Required – You must enter a value for eﬀ_start_date and eﬀ_end_date. If you don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. Required – You must enter a value for eﬀ_start_date and eﬀ_end_date. If you don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. Required Required Required – Data entity is optional but id is used to generate Partner Network View. Required – Data entity is optional but sourcing_rule_id is used to generate Partner Network View. supply_plan supply_plan_id Required N-Tier Visibility 297 AWS Supply Chain User Guide Data entity Column Is the column used by N-Tier Visibility? snapshot_date creation_date tpartner_id product_id to_site_id from_site_id plan_quantity plan_type plan_need_by_date quantity_uom Optional Optional Required Required Required Optional Required Required Required Optional Supply Planning The table below list the data
supplychain-ug-081	supplychain-ug.pdf	81	eﬀ_start_date and eﬀ_end_date. If you don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. Required Required Required – Data entity is optional but id is used to generate Partner Network View. Required – Data entity is optional but sourcing_rule_id is used to generate Partner Network View. supply_plan supply_plan_id Required N-Tier Visibility 297 AWS Supply Chain User Guide Data entity Column Is the column used by N-Tier Visibility? snapshot_date creation_date tpartner_id product_id to_site_id from_site_id plan_quantity plan_type plan_need_by_date quantity_uom Optional Optional Required Required Required Optional Required Required Required Optional Supply Planning The table below list the data entities and columns used by Supply Planning. Note How to read the table: • Required – The column name is mandatory in your dataset and you must populate the column name with values. • Optional – The column name is optional. For enhanced feature output, it is recommended to add the column name with values. • Not required – Data entity not required. Supply Planning 298 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? site id Required description Required Required Required geo_id Required - Without this ﬁeld, ﬁlters cannot group Required - Without this ﬁeld, ﬁlters cannot group sites by category such as sites by category such as region, country, state, zip region, country, state, zip code and so on. code and so on. site_type NA company_id Optional latitude longitude is_active NA NA NA Optional NA NA Required - Identiﬁes if a site needs to be considered for Required - Identiﬁes if a site needs to be considered for planning. Note, set the value planning. Note, set the value to False if a site should not to False if a site should not to be considered. If the ﬁeld to be considered. If the ﬁeld is kept blank or null, the site is kept blank or null, the site will be considered. will be considered. open_date end_date NA NA transport ation_lane id Required from_site_id Required to_site_id Required NA NA Required Required Required Supply Planning 299 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? product_g roup_id Required Required transit_time Required Required time_uom Required - Supported values include Day. Required - Supported values include Day. distance Not required Not required distance_uom Not required Not required eﬀ_start_date Optional eﬀ_end_date Optional product_id Optional Optional Optional Optional emissions _per_unit emissions _per_weight Not required Not required Not required Not required company_id Optional Optional Supply Planning 300 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? from_geo_id to_geo_id Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 301 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? carrier_t partner_id Required. When you ingest data from SAP or Required. When you ingest data from SAP or service_type EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 302 AWS Supply Chain User Guide
supplychain-ug-082	supplychain-ug.pdf	82	SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 302 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? trans_mode Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. cost_per_unit Optional cost_currency Optional product id Required description Required Optional Optional Required Required product_g roup_id Required - Without this ﬁeld, ﬁlters cannot group Required - Without this ﬁeld, ﬁlters cannot group by product category such as by product category such as dairy, clothes, and so on. dairy, clothes, and so on. is_deleted Required - Identiﬁes if a product needs to be considered for planning. Set the ﬁeld to False to consider this product and True to not consider the product. If this ﬁeld is left blank or Required - Identiﬁes if a product needs to be considered for planning. Set the ﬁeld to False to consider this product and True to not consider the product. If this ﬁeld is left blank or null, then the value will be defaulted to True. null, then the value will be defaulted to True. Supply Planning 303 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? product_h ierarchy product_type Not required Not required parent_pr oduct_id Optional Optional base_uom Optional unit_cost Optional unit_price Optional id Required Optional Optional Optional Required description Required – This ﬁeld is used by ﬁlters to group by a Required – This ﬁeld is used by ﬁlters to group by a product category such as product category such as dairy, clothes, and so on. dairy, clothes, and so on. parent_pr oduct_gro up_id Optional – This ﬁeld is used by ﬁlters to support Optional – This ﬁeld is used by ﬁlters to support multiple product category multiple product category hierarchy such as dairy, full hierarchy such as dairy, full fat milk and so on. fat milk and so on. geography id Required description Required Required Required parent_geo_id Optional – This ﬁeld is used by ﬁlters to support multiple location hierarchy such as USA → USA-EAST. Optional – This ﬁeld is used by ﬁlters to support multiple location hierarchy such as USA → USA-EAST. trading_p artner id Required description Optional Required Optional Supply Planning 304 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? country Optional Optional eﬀ_start_date Required – You must enter a value for eﬀ_start_date Required – You must enter a value for eﬀ_start_date and eﬀ_end_date. If you and eﬀ_end_date. If you don't have a value, enter don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. eﬀ_end_date Required – You must enter a value for eﬀ_start_date Required – You must enter a value for eﬀ_start_date and eﬀ_end_date. If you and eﬀ_end_date. If you don't have a value, enter don't have a value, enter 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. 1900-01-01 00:00:00 for eﬀ_start_date, and 9999-12-31 23:59:59 for eﬀ_end_date. time_zone Optional is_active Optional Optional Optional tpartner_type Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 305 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? geo_id Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default
supplychain-ug-083	supplychain-ug.pdf	83	When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 305 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? geo_id Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. inbound_order id Required order_type Required Required Required order_status Not required Not required to_site_id Required Optional submitted _date tpartner_id Required Optional Required. When you ingest data from SAP or Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED for successful ingestion. VED_NO_VALUE_PROVIDED for successful ingestion. Supply Planning 306 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? inbound_o rder_line id Required order_id Required order_type Required Required Required Required status Not required Not required product_id Required to_site_id Required Required Required from_site_id Not required Not required quantity_ submitted quantity_ conﬁrmed quantity_ received expected_ delivery_date submitted _date Required – You must set one quantity ﬁeld. Required – You must set one quantity ﬁeld. Optional – You must set one quantity ﬁeld. Optional – You must set one quantity ﬁeld. Optional – You must set one quantity ﬁeld. Optional – You must set one quantity ﬁeld. Required Required Not required Not required incoterm Not required Not required company_id Optional Optional tpartner_id Required – This ﬁeld is required for successful ingestion. Required – This ﬁeld is required for successful ingestion. quantity_uom Not required Not required Supply Planning 307 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? reservation_id Not required Not required reference _object_type Optional – This ﬁeld is used for associating purchase Optional – This ﬁeld is used for associating purchase order requests to purchase order requests to purchase orders to track plan to PO orders to track plan to PO conversion in the ERP. conversion in the ERP. reference _object_id Optional – This ﬁeld is used for associating purchase Optional – This ﬁeld is used for associating purchase order requests to purchase orders to track plan to PO order requests to purchase orders to track plan to PO conversion in the ERP. conversion in the ERP. inv_policy site_id Required id Required dest_geo_id Required Required Required Required product_id Optional – Either product_i d or product_group_id is Optional – Either product_i d or product_group_id is required. required. product_g roup_id Optional – Either product_i d or product_group_id is required. Optional – Either product_i d or product_group_id is required. eﬀ_start_date Required eﬀ_end_date Required company_id Optional Required Required Optional Supply Planning 308 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? ss_policy Required – The accepted values for this ﬁeld are Required – The accepted values for this ﬁeld are abs_level, doc_dem, abs_level, doc_dem, doc_fcst, and sl. doc_fcst, and sl. target_in ventory_qty Required – This ﬁeld is required when ss_policy is Required – This ﬁeld is required when ss_policy is set to abs_level. set to abs_level. target_do c_limit target_sl sourcing_rules sourcing_ rule_id Required – This ﬁeld is required when ss_policy is set to doc_dem or doc_fcst. Required – This ﬁeld is required when ss_policy is set to doc_dem or doc_fcst. Required – This ﬁeld is required when ss_policy is Required – This ﬁeld is required when ss_policy is set to sl. Required set to sl. Required company_id Optional Optional product_id Optional – Either product_i d or product_group_id is Optional – Either product_i d or product_group_id is required. required. product_g roup_id from_site_id Optional – Either product_i d or product_group_id is required. Optional – Either product_i d or product_group_id is required. Optional – This ﬁeld is required for sourcing_rule types transfer. Optional – This ﬁeld is required for sourcing_rule types transfer. to_site_id Required Required Supply Planning 309 AWS Supply Chain User Guide Data
supplychain-ug-084	supplychain-ug.pdf	84	– This ﬁeld is required when ss_policy is Required – This ﬁeld is required when ss_policy is set to sl. Required set to sl. Required company_id Optional Optional product_id Optional – Either product_i d or product_group_id is Optional – Either product_i d or product_group_id is required. required. product_g roup_id from_site_id Optional – Either product_i d or product_group_id is required. Optional – Either product_i d or product_group_id is required. Optional – This ﬁeld is required for sourcing_rule types transfer. Optional – This ﬁeld is required for sourcing_rule types transfer. to_site_id Required Required Supply Planning 309 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? sourcing_ rule_type Required – The allowed values for this ﬁeld Required – The allowed values for this ﬁeld are transfer, buy, and are transfer, buy, and manufacture. manufacture. Only lower case is allowed. tpartner_id Optional – This ﬁeld is required for sourcing_rule Optional – This ﬁeld is required for sourcing_rule types buy. types buy. transport ation_lane_id Optional – This ﬁeld is required for sourcing_rule Optional – This ﬁeld is required for sourcing_rule types transfer. types transfer. productio n_process_id Optional – This ﬁeld is required for sourcing_rule Optional – This ﬁeld is required for sourcing_rule types manufacture. types manufacture. sourcing_ priority Optional Optional min_qty Optional max_qty Optional qty_multiple Optional eﬀ_start_date Required eﬀ_end_date Required Optional Optional Optional Required Required Supply Planning 310 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? sourcing_ schedule sourcing_ schedule_id Required Required company_id Optional Optional Note This data entity is optional. tpartner_id Optional – This ﬁeld is required for schedule_type Optional – This ﬁeld is required for schedule_type InboundOrdering. InboundOrdering. status Required Required from_site_id Optional – This ﬁeld is required for schedule_type Optional – This ﬁeld is required for schedule_type OutboundShipping. OutboundShipping. to_site_id Required Required schedule_type Required – The allowed values for this ﬁeld are Required – The allowed values for this ﬁeld are InboundOrdering and InboundOrdering and OutboundShipping. OutboundShipping. eﬀ_start_date Required eﬀ_end_date Required Required Required Supply Planning 311 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? sourcing_ schedule_ details Note This data entity is optional. sourcing_ schedule_ detail_id sourcing_ schedule_id Required Required Required Required company_id Optional Optional product_id Optional – Either product_i d or product_group_id is required. Optional – Either product_i d or product_group_id is required. product_g roup_id Optional – Either product_i d or product_group_id is Optional – Either product_i d or product_group_id is required. day_of_week Optional week_of_m onth Optional time_of_day Optional date Optional product_bom id Not required product_id Not required company_id Optional site_id Not required productio n_process_id Not required required. Optional Optional Optional Optional Required Required Optional Required Required Supply Planning 312 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? component _product_id component _quantity_per Not required Required Not required Required assembly_cost Not required assembly_ cost_uom Not required priority Not required eﬀ_start_date Not required eﬀ_end_date Not required productio n_process productio n_process_id Not required Optional Optional Optional Required Required Required Not required Optional productio n_process _name product_id Not required site_id Not required company_id Optional setup_time Not required Not required setup_tim e_uom operation _time Required Required Optional Optional Optional Not required Optional Supply Planning 313 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? operation _time_uom Not required Optional inv_level snapshot_date Required site_id Required product_id Required company_id Optional Required Required Required Required Optional Required on_hand_i nventory allocated _inventory bound_inv entory lot_number Not required Not required Not required Not required Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 DED. When you upload data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. expiry_date Not required Not required forecast site_id Required Required Supply Planning 314 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? Required Optional Optional Optional Optional Required product_id Required mean Optional Optional Optional Optional Required p10 p50 p90 forecast_ start_dttm forecast_ end_dttm snapshot_date Required Required Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED.
supplychain-ug-085	supplychain-ug.pdf	85	ingestion. expiry_date Not required Not required forecast site_id Required Required Supply Planning 314 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? Required Optional Optional Optional Optional Required product_id Required mean Optional Optional Optional Optional Required p10 p50 p90 forecast_ start_dttm forecast_ end_dttm snapshot_date Required Required Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 315 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? region_id Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. product_g roup_id Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. vendor_pr oduct company_id Optional vendor_tp artner_id Required product_id Required eﬀ_start_date Required eﬀ_end_date Required Optional Required Required Required Required Supply Planning 316 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? vendor_le ad_time company_id Optional vendor_tp artner_id Required product_id Optional site_id Required planned_l ead_time Required eﬀ_start_date Required eﬀ_end_date Required Optional Required Optional Required Required Required Required product_g roup_id Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. Supply Planning 317 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? region_id Required – When you ingest data from SAP or Required – When you ingest data from SAP or EDI, the default value EDI, the default value for string is SCN_RESER for string is SCN_RESER VED_NO_VALUE_PROVI VED_NO_VALUE_PROVI DED. When you upload DED. When you upload data using the Amazon S3 data using the Amazon S3 connector, you must enter connector, you must enter a value or use SCN_RESER a value or use SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for successful ingestion. for successful ingestion. outbound_ order_line id Required – This ﬁeld determines the outbound Required – This ﬁeld determines the outbound shipment id. shipment id. product_id Required – This ﬁeld determines the id of the Required – This ﬁeld determines the id of the product shipped. product shipped. cust_order_id Required – This ﬁeld determines the id of the Required – This ﬁeld determines the id of the outbound order. outbound order. ship_from _site_id Required – This ﬁeld determines the site from where the product units are requested. Required – This ﬁeld determines the site from where the product units are requested. ship_to_site_id Not required Not required init_quan tity_requested Optional – This ﬁeld determines the ﬁnal quantity after any cancellat Optional – This ﬁeld determines the ﬁnal quantity after any cancellat ions and changes. ions and changes. Supply Planning 318 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? quantity_ promised quantity_ delivered ﬁnal_qua ntity_req uested status Optional – This ﬁeld displays the promised quantity. Optional – This ﬁeld displays the promised quantity. Optional – This ﬁeld displays the actual quantity Optional – This ﬁeld displays the actual quantity delivered. delivered. Optional – Final quantity after any cancellations or Optional – Final quantity after any cancellations or changes changes
supplychain-ug-086	supplychain-ug.pdf	86	This ﬁeld determines the ﬁnal quantity after any cancellat ions and changes. ions and changes. Supply Planning 318 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? quantity_ promised quantity_ delivered ﬁnal_qua ntity_req uested status Optional – This ﬁeld displays the promised quantity. Optional – This ﬁeld displays the promised quantity. Optional – This ﬁeld displays the actual quantity Optional – This ﬁeld displays the actual quantity delivered. delivered. Optional – Final quantity after any cancellations or Optional – Final quantity after any cancellations or changes changes Optional – This ﬁeld determines the status of the Optional – This ﬁeld determines the status of the order line, that is, canceled, order line, that is, canceled, open, closed, and so on. open, closed, and so on. requested _delivery_date Required Required promised_ delivery_date actual_de livery_date Optional Optional Optional Optional segmentation segment_id Required creation_date Required company_id Optional site_id Required product_id Required segment_d escription Optional Required Required Optional Required Required Optional Supply Planning 319 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? segment_type Optional segment_value Optional source Optional eﬀ_start_date Required eﬀ_end_date Required company id Required Note This data entity is optional. description Optional address_1 Optional address_2 Optional address_3 Optional city Optional state_prov Optional postal_code Optional country Optional phone_num ber Optional time_zone Optional calendar_id Optional Optional Optional Optional Required Required Required Optional Optional Optional Optional Optional Optional Optional Optional Optional Optional Optional Supply Planning 320 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? supply_pl anning_pa ramters Note This data entity is optional. product_id Required Required product_g roup_id Required. For future Use. Please populate SCN_RESER Required. For future Use. Please populate SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for now. for now. site_id Required. For future Use. Please populate SCN_RESER Required. For future Use. Please populate SCN_RESER VED_NO_VALUE_PROVIDED VED_NO_VALUE_PROVIDED for now. planner_name Optional for now. Optional Optional.For future use Optional.For future use Optional.For future use Optional.For future use Optional.For future use Optional.For future use demand_ti me_fence_ days forecast_ consumpti on_backwa rd_days forecast_ consumpti on_forwar d_days eﬀ_start_date Required eﬀ_end_date Required shipment id Required ship_to_site_id Required Required Required NA NA Supply Planning 321 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? product_id Required ship_from _site_id Required – Supply Planning can use the value from ship_from_site_id or supplier_tpartner_id. NA NA supplier_ tpartner_id Required – Supply Planning can use the value from NA ship_from_site_id or supplier_tpartner_id. order_type Required units_shipped Required planned_d elivery_date Required – Supply Planning can use the value from actual_de livery_date carrier_e ta_date planned_s hip_date actual_sh ip_date planned_delivery_date, actual_delivery_date, or carrier_eta_date. Required – Supply Planning can use the value from planned_ship_date, or actual_ship_date. creation_date Optional shipment_ status Optional NA NA NA NA NA NA Supply Planning 322 AWS Supply Chain User Guide Data entity Column Is the column used for Auto Replenishment? Is the column used for Manufacturing Plan? NA NA NA NA NA NA order_id order_line_id package_id Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 connector, you must enter a value or use SCN_RESER VED_NO_VALUE_PROVIDED for successful ingestion. ??? id Required lot_qty Required expiry_date Optional shipment_id Required product_id tpartner_id order_id order_line_id package_id Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VALUE_PROVI DED. When you upload data using the Amazon S3 connector, you must enter a value or use SCN_RESER VED_NO_VALUE_PROVIDED for successful ingestion. Supply Planning 323 AWS Supply Chain Insights User Guide The table below list the data entities and columns used by Insights for the Inventory Visibility, Network Map, Inventory Insights, and Rebalance Recommendations features. See the table below on how each feature in Insights uses the data entities. Note How to read the table: • Required – The column name is mandatory in your dataset and you must populate the column name with values. • Optional – The column name is optional. For enhanced feature output, it is recommended to add the column name with values. • Not required – Data entity not required. Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? site id Required Required Required Required Required description Required Required Required Required Optional geo_id Insights Required Required – This ﬁeld is required for ﬁlters to group sites by geographi Required – This ﬁeld is required for ﬁlters to group sites by geographi Required –
supplychain-ug-087	supplychain-ug.pdf	87	recommended to add the column name with values. • Not required – Data entity not required. Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? site id Required Required Required Required Required description Required Required Required Required Optional geo_id Insights Required Required – This ﬁeld is required for ﬁlters to group sites by geographi Required – This ﬁeld is required for ﬁlters to group sites by geographi Required – This ﬁeld is required for ﬁlters to group sites by geographi cal groups cal groups cal groups such as such as such as Required – This ﬁeld is required for ﬁlters to group sites by geographi cal groups such as 324 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? region/co region/co region/co untry/sta te and so untry/sta te and so untry/sta te and so on. on. on. region/co untry/sta te and so on. Optional Optional Optional Optional site_type Optional – Populatin g this column will display the site type on the inventory visibilit y page such as RDC, CDC, manufactu ring site and so on. Insights 325 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? company_id Optional Optional Optional Optional Column name company_i d should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 326 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? latitude Optional ations? Optional Optional Required – This ﬁeld is used to view the site on the Network Map page. Column name latitude should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 327 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? longitude Optional ations? Optional Optional Required – This ﬁeld is used to view the site on the Network Map page. Column name longitude should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 328 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column is_active used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? Required – Identiﬁe Required – Identiﬁe Required – Identiﬁe Required – Identiﬁe Required – Identiﬁe s if the s if the s if the s if the s if the site needs site needs site needs site needs site needs to be to be to be to be to be considered considered considered considered considered for Insights for Insights for Insights for Insights for Insights computati on. Note: If you want computati on. Note: If you want computati on. Note: If you want computati on. Note: If you want computati on. Note: If you want a site to be a site to be a site to be a site to be a site to be excluded excluded excluded excluded excluded from the from the from the from the from the Insights computati Insights computati Insights computati Insights computati Insights computati on, make on, make on, make on, make on, make sure you sure you sure you sure you sure you set the column value to False. If set the column value to False. If set the column value to False. If set the column value to False. If set the column value to False. If the column the column the column the column the column is blank or null, is blank or null, is blank or null, is blank or null, is blank or null, the site is the site is the site is the site is the site is considered considered considered considered considered active. active. active. active. active. Insights 329 AWS Supply Chain User Guide Column Data entity Is the
supplychain-ug-088	supplychain-ug.pdf	88	column value to False. If set the column value to False. If set the column value to False. If set the column value to False. If set the column value to False. If the column the column the column the column the column is blank or null, is blank or null, is blank or null, is blank or null, is blank or null, the site is the site is the site is the site is the site is considered considered considered considered considered active. active. active. active. active. Insights 329 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? open_date Optional Optional Optional Optional Column name open_date should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 330 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? end_date Optional Optional Optional Optional Column name end_date should be available in your dataset. Value for the column name is not required for Lead Time Insights. id transport ation_lan e Not required Not required Not required Required Required Insights 331 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? from_site_id Not required Not required Not required ations? Required Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VA LUE_PROVI DED. When you upload data using the Amazon S3 connector , you must enter a value or use SCN_RESER VED_NO_VA LUE_PROVI DED for successful ingestion. Insights 332 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? to_site_id Not required Not required Not required ations? Required Required. When you ingest data from SAP or EDI, the default value for string is SCN_RESER VED_NO_VA LUE_PROVI DED. When you upload data using the Amazon S3 connector , you must enter a value or use SCN_RESER VED_NO_VA LUE_PROVI DED for successful ingestion. Insights 333 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? product_group_id Not required Not required Not required ations? Required Column name product_g roup_id should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 334 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? transit_time Not required Not required Not required ations? Required Column name transit_t ime should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 335 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? time_uom Not required Not required Not required Required – Supports Column name day or days time_uom as units. should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 336 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? distance Not required Not required Not required ations? Required Column name distance should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 337 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend
supplychain-ug-089	supplychain-ug.pdf	89	column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? distance Not required Not required Not required ations? Required Column name distance should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 337 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? distance_uom Not required Not required Not required Required – Supports Column name mile(s), distance_ km(s), or uom Kilometer should be (s) as units. available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 338 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? eﬀ_start_date Not required Not required Not required ations? Optional Column name eﬀ_start _date should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 339 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? eﬀ_end_date Not required Not required Not required ations? Optional Column name eﬀ_end_d ate should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 340 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? product_id Not required Not required Not required Optional – Either Column name product_id product_id or product- should be group-id is available required. in your When the dataset. lane is Value for linked with the column a product, name this ﬁeld is is not mandatory required . for Lead Time Insights. Insights 341 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? emissions _per_unit Not required Not required Not required ations? Optional Column name emissions _per_unit should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 342 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? emissions _per_weight Not required Not required Not required ations? Optional Column name emissions _per_unit should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 343 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? company_id Not required Not required Not required ations? Optional Column name company_i d should be available in your dataset. Value for the column name is not required for Lead Time Insights. Insights 344 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? from_geo_id Not required Not required Not required Required. When you Required. When you ingest data ingest data from SAP from SAP or EDI, the or EDI, the default default value for value for string is string is SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED. When DED. When you upload you upload data using the data using the Amazon S3 Amazon S3 connector connector , you must , you must enter a value or use enter a value or use SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED for DED for successful successful ingestion. ingestion. Insights 345 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for
supplychain-ug-090	supplychain-ug.pdf	90	default value for value for string is string is SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED. When DED. When you upload you upload data using the data using the Amazon S3 Amazon S3 connector connector , you must , you must enter a value or use enter a value or use SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED for DED for successful successful ingestion. ingestion. Insights 345 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? to_geo_id Not required Not required Not required Required. When you Required. When you ingest data ingest data from SAP from SAP or EDI, the or EDI, the default default value for value for string is string is SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED. When DED. When you upload you upload data using the data using the Amazon S3 Amazon S3 connector connector , you must , you must enter a value or use enter a value or use SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED for DED for successful successful ingestion. ingestion. Insights 346 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? carrier_tpartner_i d Not required Not required Not required Required. When you Required. When you ingest data ingest data from SAP from SAP or EDI, the or EDI, the default default value for value for string is string is SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED. When DED. When you upload you upload data using the data using the Amazon S3 Amazon S3 connector connector , you must , you must enter a value or use enter a value or use SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED for DED for successful successful ingestion. ingestion. Insights 347 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? service_type Not required Not required Not required Required. When you Required. When you ingest data ingest data from SAP from SAP or EDI, the or EDI, the default default value for value for string is string is SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED. When DED. When you upload you upload data using the data using the Amazon S3 Amazon S3 connector connector , you must , you must enter a value or use enter a value or use SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED for DED for successful successful ingestion. ingestion. Insights 348 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? trans_mode Not required Not required Not required Required. When you Required. When you ingest data ingest data from SAP from SAP or EDI, the or EDI, the default default value for value for string is string is SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED. When DED. When you upload you upload data using the data using the Amazon S3 Amazon S3 connector connector , you must , you must enter a value or use enter a value or use SCN_RESER SCN_RESER VED_NO_VA VED_NO_VA LUE_PROVI LUE_PROVI DED for DED for successful successful ingestion. ingestion. Insights 349 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? cost_per_unit Not required Not required Not required ations? Optional – You can view the shipping cost unit by lane during Column name cost_per_ unit should be available in your rebalance dataset. recommend Value for ations. the column name is not required for Lead Time Insights. Insights 350 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? cost_currency Not required Not required Not required ations? Optional – You can view the shipping cost unit by lane during Column name cost_curr ency should be available in your rebalance dataset. recommend Value for ations. the column
supplychain-ug-091	supplychain-ug.pdf	91	your rebalance dataset. recommend Value for ations. the column name is not required for Lead Time Insights. Insights 350 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? cost_currency Not required Not required Not required ations? Optional – You can view the shipping cost unit by lane during Column name cost_curr ency should be available in your rebalance dataset. recommend Value for ations. the column name is not required for Lead Time Insights. product id Required Required Required Required Required description Required Required Required Required Required Insights 351 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? product_group_id Required – Using this Required – Using this Required – Using this ﬁeld, you ﬁeld, you ﬁeld, you can group can group can group products products products by product by product by product category category category such dairy, such dairy, such dairy, clothes, clothes, clothes, and so on. and so on. and so on. ations? Required Required – Using this ﬁeld, you can group products by product category such dairy, clothes, and so on. Insights 352 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? is_deleted Required – Identiﬁe Required – Identiﬁe Required – Identiﬁe Required – Identiﬁe Required – Identiﬁe s if the product needs to be s if the product needs to be s if the product needs to be s if the product needs to be s if the product needs to be considered considered considered considered considered for Insights for Insights for Insights for Insights for Insights computati on. Note: If you computati on. Note: If you computati on. Note: If you computati on. Note: If you computati on. Note: If you want the want the want the want the want the product product product product product to be excluded to be excluded to be excluded to be excluded to be excluded from the from the from the from the from the Insights Insights Insights Insights Insights computati computati computati computati computati on, make on, make on, make on, make on, make sure you sure you sure you sure you sure you set the column value to set the column value to set the column value to set the column value to set the column value to True and True and True and True and True and set to False set to False set to False set to False set to False to include to include to include to include to include this this this this this product product product product product for Insights for Insights for Insights for Insights for Insights Insights 353 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column product_type used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? computati computati computati computati computati on. If the column is on. If the column is on. If the column is on. If the column is on. If the column is left blank left blank left blank left blank left blank or null, or null, or null, or null, or null, the system the system the system the system the system considers considers considers considers considers the default the default the default the default the default value of value of value of value of value of True. True. True. True. True. Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Column name is required is required is required is required product_t to support to support to support to support ype multiple product levels such as multiple product levels such as multiple product levels such as multiple product levels such as should be available in your dataset. planning planning planning planning Value for and and and and the column fulﬁllment fulﬁllment fulﬁllment fulﬁllment name product. product. product. product. is not required for Lead Time Insights. Insights 354 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility?
supplychain-ug-092	supplychain-ug.pdf	92	support to support ype multiple product levels such as multiple product levels such as multiple product levels such as multiple product levels such as should be available in your dataset. planning planning planning planning Value for and and and and the column fulﬁllment fulﬁllment fulﬁllment fulﬁllment name product. product. product. product. is not required for Lead Time Insights. Insights 354 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? parent_pr oduct_id Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Column name is required is required is required is required parent_pr to support to support to support to support oduct_id multiple product levels such as multiple product levels such as multiple product levels such as multiple product levels such as should be available in your dataset. planning planning planning planning Value for and and and and the column fulﬁllment fulﬁllment fulﬁllment fulﬁllment name product. product. product. product. is not required for Lead Time Insights. Insights 355 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column base_uom used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Column name is required is required is required is required base_uom for for for for should be Insights to Insights to Insights to Insights to available calculate calculate calculate calculate in your the default the default the default the default dataset. base uom base uom base uom base uom Value for for a given for a given for a given for a given the column product. product. product. product. name is not required for Lead Time Insights. product_h id ierarchy description Required Required Required Required Required Required – Using this Required – Using this Required – Using this Required – Using this Required – Using this ﬁeld, you can ﬁlter groups by product category ﬁeld, you can ﬁlter groups by product category ﬁeld, you can ﬁlter groups by product category ﬁeld, you can ﬁlter groups by product category ﬁeld, you can ﬁlter groups by product category such dairy, such dairy, such dairy, such dairy, such dairy, clothes, clothes, clothes, clothes, clothes, and so on. and so on. and so on. and so on. and so on. Insights 356 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? parent_pr oduct_group_id Optional – This ﬁeld Optional – This ﬁeld Optional – This ﬁeld Column name Optional – This ﬁeld is used by is used by is used by parent_pr is used by ﬁlters to support multiple product ﬁlters to support multiple product ﬁlters to support multiple product oduct_gro ﬁlters to up_id support should be multiple available product hierarchy hierarchy hierarchy in your category category category dataset. hierarchy category such as such as such as Value for such as dairy, frozen diary dairy, frozen diary dairy, frozen diary the column dairy, name is not frozen diary products, fresh diary products, fresh diary products, fresh diary required for products, fresh diary and so on. and so on. and so on. Rebalance and so on. Recommend ations. Insights 357 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? product_uom_id product_u om Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required Note This data entity is is required is required is required is required to perform to perform to perform to perform the the the the product product product product uom uom uom uom conversion. conversion. conversion. conversion. optional. product_id Required Required Required Required Not required For product uom uom conversio ns, data is required in description either product- u quantity om, uom_conve rsion, or Insights. Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required is required is required is required is required for for for for conversion conversion conversion conversion to units. to units. to units. to units. Optional Optional Optional Optional Required – This ﬁeld contains the conversion factor. Required – This ﬁeld
supplychain-ug-093	supplychain-ug.pdf	93	the the product product product product uom uom uom uom conversion. conversion. conversion. conversion. optional. product_id Required Required Required Required Not required For product uom uom conversio ns, data is required in description either product- u quantity om, uom_conve rsion, or Insights. Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required is required is required is required is required for for for for conversion conversion conversion conversion to units. to units. to units. to units. Optional Optional Optional Optional Required – This ﬁeld contains the conversion factor. Required – This ﬁeld contains the conversion factor. Required – This ﬁeld contains the conversion factor. Required – This ﬁeld contains the conversion factor. Not required Not required Insights 358 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? quantity_uom Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required is required is required is required is required for for for for conversion conversion conversion conversion from units. from units. from units. from units. eﬀ_start_date Optional Optional Optional Optional eﬀ_end_date Optional Optional Optional Optional company_id Optional Optional Optional Optional Not required Not required Not required Insights 359 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? uom_conve uom rsion Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required is required is required is required is required for for for for conversion conversion conversion conversion from units. from units. from units. from units. Optional Optional Optional Optional Not required Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required is required is required is required is required for for for for conversion conversion conversion conversion to units. to units. to units. to units. Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Required – This ﬁeld Not required contains contains contains contains the conversion factor. the conversion factor. the conversion factor. the conversion factor. Note This data entity company_id is optional. For conversio n_uom_id product uom conversio ns, data is conversion_factor required in either product- u om, uom_conve rsion, or Insights. geographyid Required Required Required Required Required Insights 360 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? description Required Required Required Required Required Optional Optional parent_geo_id Optional – This ﬁeld Required – This ﬁeld is used to is used to support multiple location support multiple location hierarchy hierarchy such as such as USA, USA- USA, USA- East, and East, and so on. so on. Required – This ﬁeld is used to support multiple location hierarchy such as USA, USA- East, and so on. id trading_p artner Required Required Required Required Required description Optional Optional Optional Optional Required country Optional Optional Optional Optional Optional Insights 361 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is the column eﬀ_start_date used for used for used for used for used for Inventory Network Inventory Rebalance Lead time visibility? map? Insights? recommend Insights? ations? Required – You must Required – You must Required – You must Required – You must enter a enter a enter a enter a Column name eﬀ_start value for value for value for value for _date eﬀ_start eﬀ_start eﬀ_start eﬀ_start should be _date and _date and _date and _date and available eﬀ_end_d eﬀ_end_d eﬀ_end_d eﬀ_end_d in your ate. If you ate. If you ate. If you ate. If you dataset. don't have don't have don't have don't have Value for a value, a value, a value, a value, the column enter enter enter enter 1900-01-0 1900-01-0 1900-01-0 1900-01-0 1 1 1 1 00:00:00 for 00:00:00 for 00:00:00 for 00:00:00 for eﬀ_start eﬀ_start eﬀ_start eﬀ_start _date, and _date, and _date, and _date, and name is not required for Lead Time Insights. 9999-12-3 9999-12-3 9999-12-3 9999-12-3 1 1 1 1 23:59:59 for 23:59:59 for 23:59:59 for 23:59:59 for eﬀ_end_d eﬀ_end_d eﬀ_end_d eﬀ_end_d ate. ate. ate. ate. Insights 362 AWS Supply Chain User Guide Column Data entity Is the column Is the column Is the column Is the column Is

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