CHALLENGE 

 Industry – Courier / Express delivery 

 Scenario – Pertains to package delivery to consumers living in densely populated geographies where   the parcel volumes are highest and brings unique challenges and complexity to delivery operations 

 Design Tool used in this Scenario – Learning launch 

 Description – Parcel delivery at densely populated localities need a lot of administrative and sorting   work and since the volume of parcels are high , the delivery vehicle needs to make multiple rounds   between the office and the delivery area . The multiple to and fro movement adds to transportation   cost , human cost and also increases the risk of delivery delays . I was the manager for a project which   involved design and delivery of a new operations procedure which was expected to reduce the   delivery time to such localities with minimal incremental cost and higher customer satisfaction . 

 SELECTION 

 The project team had come up with various innovative solutions to tackle this problem , but the   trade - offs between Cost of implementation Vs . Benefits realisation was not attractive for most of   the solutions . One of the solutions seemed practically feasible from all aspects ; the idea was to have   an office mounted inside a customised vehicle ; this would act as a moving office which can cater to   high volumes and also reduce the to and fro movement for the delivery vehicles during peak hours . 

 This concept did not have any predecessors and neither was it tried by any player in the industry .   The team had too many assumptions which needed some real testing to lower down the   uncertainties involved in the suggested solution . The team decided that Learning Launch would be   an ideal tool to test the concept and also gather some data and insights which can approve / disprove   the key assumptions made during the solution planning phase . 

 APPLICATION 

 The team studied different scenarios and came up with the suggestion to test the concept at 3   different metro locations with a Learning launch and had assembled a team to gather the data on   various measurements during the pilot period . Three vehicles were custom modified with office   interiors and equipped with all necessary amenities to back the parcel delivery operations . The   delivery personnel were trained on the new SOP and the pilot was scheduled to happen in parallel at   3 cities for a period of 1 month to gather the learning and decide on the future course of action 

 INSIGHTS 

 The pilot was closely monitored by the execution team and results were analysed based on the   success criteria predefined for the project . The results were impressive ; the service quality metric   increased by 15 % for the geographies that were handled by the Mobile office . Surprisingly the   project team noted that the operations cost was 7 % lesser for the operations as compared to the 

 conventional delivery method ; the team had anticipated 3 % higher cost before the learning launch .   The findings were presented to the senior management and since the numbers were clearly   favourable ; the decision committee sanctioned to roll out 75 additional such facilities across the   nation within the next 3 months ! 

 APPROACH 

 The team had studied the problem and came up with a list of workable solutions and from the list ,   shortlisted one solution which was most promising based on various business parameters . The   learning launch was based on various assumptions and some of the assumptions were pivotal for the   success of the solution . One thing which could have been done differently is that some of the key   assumptions could have been pre tested even before the learning launch which would have helped   avid some setbacks and bottlenecks during the learning launch . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: CHALLENGE 

 Industry – Courier / Express delivery 

 Scenario – Pertains to package delivery to consumers living in densely populated geographies where   the parcel volumes are highest and brings unique challenges and complexity to delivery operations 

 Design Tool used in this Scenario – Learning launch 

 Description – Parcel delivery at densely populated localities need a lot of administrative and sorting   work and since the volume of parcels are high , the delivery vehicle needs to make multiple rounds   between the office and the delivery area . The multiple to and fro movement adds to transportation   cost , human cost and also increases the risk of delivery delays . I was the manager for a project which   involved design and delivery of a new operations procedure which was expected to reduce the   delivery time to such localities with minimal incremental cost and higher customer satisfaction . 

 SELECTION 

 The project team had come up with various innovative solutions to tackle this problem , but the   trade - offs between Cost of implementation Vs . Benefits realisation was not attractive for most of   the solutions . One of the solutions seemed practically feasible from all aspects ; the idea was to have   an office mounted inside a customised vehicle ; this would act as a moving office which can cater to   high volumes and also reduce the to and fro movement for the delivery vehicles during peak hours . 

 This concept did not have any predecessors and neither was it tried by any player in the industry .   The team had too many assumptions which needed some real testing to lower down the   uncertainties involved in the suggested solution . The team decided that Learning Launch would be   an ideal tool to test the concept and also gather some data and insights which can approve / disprove   the key assumptions made during the solution planning phase . 

 APPLICATION 

 The team studied different scenarios and came up with the suggestion to test the concept at 3   different metro locations with a Learning launch and had assembled a team to gather the data on   various measurements during the pilot period . Three vehicles were custom modified with office   interiors and equipped with all necessary amenities to back the parcel delivery operations . The   delivery personnel were trained on the new SOP and the pilot was scheduled to happen in parallel at   3 cities for a period of 1 month to gather the learning and decide on the future course of action 

 INSIGHTS 

 The pilot was closely monitored by the execution team and results were analysed based on the   success criteria predefined for the project . The results were impressive ; the service quality metric   increased by 15 % for the geographies that were handled by the Mobile office . Surprisingly the   project team noted that the operations cost was 7 % lesser for the operations as compared to the 

 conventional delivery method ; the team had anticipated 3 % higher cost before the learning launch .   The findings were presented to the senior management and since the numbers were clearly   favourable ; the decision committee sanctioned to roll out 75 additional such facilities across the   nation within the next 3 months ! 

 APPROACH 

 The team had studied the problem and came up with a list of workable solutions and from the list ,   shortlisted one solution which was most promising based on various business parameters . The   learning launch was based on various assumptions and some of the assumptions were pivotal for the   success of the solution . One thing which could have been done differently is that some of the key   assumptions could have been pre tested even before the learning launch which would have helped   avid some setbacks and bottlenecks during the learning launch .
### Output: 