A global leader in the branding and distribution of consumer packaged goods undertook a major overhaul of its business processes and information technology. This distributor handles hundreds of thousands of products from thousands of suppliers, and provides inventory to several dozen retail chains. As the Company's senior director of IT put it, "We've had to change quickly to stay ahead of the market and keep up with our growth." Establishing enterprise governance over information and an enterprise-wide master data management (MDM) process were key enablers of the company's technology initiative.
With customer teams in over a dozen countries, this large distributor has a complex business which generates a high volume of customer, product, and transaction data. It receives a wide array of inbound data from diverse sources — which packaged integration or consolidation would not resolve. The company recognized that relying too heavily on data from its trading partners and syndicated data providers could introduce redundancies. It needed to match data from these sources, and eliminate data redundancies across its multiple systems.
There was no standard definition of master data across the company's customers, suppliers and other business partners. In fact, product and supplier information was maintained by hundreds of different employees in offices around the world. Each change had to be reentered directly in every line-of-business application. The company identified a key obstacle to reducing the likelihood of data errors and inconsistencies across the enterprise: historically, there was little ownership of data management by the business side.
The overall plan was to re-architect and re-deploy new technologies, solutions and services in an enterprise-wide effort. They planned to achieve their governance objectives by focusing on the lifecycle of master data and treating master data management as an enterprise process rather than a data organization project.
It was evident that the company would need to tightly integrate the maintenance and use of master data and data quality within its key line-of-business applications: supply chain, financial, and portal. The IT group wanted to provide a solid MDM/data quality foundation and contain it in a central hub for managing all master data entities.
Getting the business engaged was seen as a critical enabler of success. "We needed to enhance our ability to involve the business in the ownership and maintenance of MDM and data quality," said a senior IT executive.
As the business expands and changes shape, information complexities are an inevitable consequence. The company, which is enabled by information, identified three data-driven focal points to anchor continuous improvement of its data foundation.
These three business priorities were enabled by a fourth element, a business-and-IT shared recognition that information quality underpins any effort at delivering the business benefits.
A key guideline for the IT group was to build an MDM solution only if it could not find an available package that met its needs. It wanted a single-vendor solution for managing all its item, customer and supplier entities and item-level benchmarking.
After investigating which vendors to short-list, the IT group concluded that implementing Magnitude MDM would set the stage for significantly improved reporting, and deliver the high usability and straightforward integration with operational systems required to run the business. The Magnitude Dynamic Information Warehouse (DIW) delivers a fully automated, model driven solution that rapidly adapts to changing business needs. Magnitude was chosen over six competitors, including two global megavendors.
The company established guidelines to follow in its MDM initiative. First, the IT group defined architectures for core technology and for data, across the enterprise. These frameworks would cascade down, to dictate the design of any subordinate system. Second, data quality requirements included the implementation and maintenance of MDM. Third, data loaded into the new system was thoroughly cleansed, to further data quality and accuracy.
The company prioritized its MDM implementation to focus on the highest-payback domains — product and supplier — in order to lower costs in the near term. The Magnitude DIW was configured to map and manage a dataset containing more than 500,000 product names and SKUs from 5,000-plus suppliers and more than 100 major retail customers. After implementing these two areas, the focus shifted to customer and employee data. This phased approach enabled project payback breakthroughs at shorter intervals.
The Magnitude DIW now enables the rapid creation and management of rich data definitions. Overall information quality has improved, with validation and correction of errors when new items are set up. Redundancy has been largely eliminated and data management across heterogeneous systems has improved. Employees share knowledge more effectively. Overall, master data management supports higher consistency in both data and deliverables, and it is easier to maintain the focus on selling high-priority items with an established single source of master data for all enterprise systems. Across its multi-country operations, this distributor can point to faster "speed to shelf" for new products. Employees have greater confidence in the accuracy of data, a critical benefit for a business that deals with an ever-changing line of hundreds of thousands of products.
Today the company has a ready answer for invalid or incomplete data. Configurable workflows automatically route the problem to the right individual who can correct it to maintain a high level of data quality for downstream applications.
This global CPG distributor has established a clear foundation to manage MDM processes for governing information through its life cycle. Its multiple-domain MDM is now an enterprise-wide reality with ongoing challenges and benefits.
Finding the right balance between operational and analytical entities and hierarchies was another key to success. The company elected to impose an enterprise data architecture on downstream systems, and this became more than a best practice; it was set as a requirement.
Magnitude Dynamic Information Warehouse's easy-to-use design tools, dynamic warehouse capabilities, and automated integration increase productivity and foster collaboration between the Company's business and IT stakeholders. Now, when a new product is introduced or new packaging is requested, the change is a simple business exercise that can be accomplished without touching operational systems. The cost of managing supplier information has decreased, and the company is now positioned to implement advanced analytics to help capitalize on future growth opportunities.