Reflection – Learning Launch 

 Challenge 

 I am a senior manager of a Global Service Delivery solution team for a fortune 500 MNC and we had an existing product for orchestrating our services via different Centre of Excellence ( CoE ) across the globe . But this product was neither in parity with the era of digital transformation nor was it fulfilling our need to expand services with new engagements and clients . Leading to infuriation bubbling under the surface , different CoE started using their own mechanism and created silos . This existing product was to be used by analysts of all CoE along with stakeholders of different line of services and the service delivery centers . The estimated hours of work was expected to be 400k annually , but it began shrinking around 15 % annually , due to rejection of the tool from all levels . The stakeholders were concerned since it was affecting them from both finance and governance perspective . 

 Selection 

 Since the existing product was based on analytical data set only , I formed a core team that would be influenced by design thinking and their task was to identify all possible solutions . This team started empathizing with users from all levels using journey mapping to understand current situation effectively and later used mind mapping to set the design criteria . We then reached out to Gartner to identify if there is already any off the shelf product in marketplace which could address this design criteria . As Gartner said no such product exists , our team stated using a visualization tool to ideate solutions . Out of 5 prototypes we chose to topmost one for learning launch to co - create with our users and stakeholders . 

 Application 

 We leveraged rapid application development methodology , an iterative process , which uses low code development platform , for learning launches we had . We read several articles regarding learning launch tool for better perspective . Some such articles being - 

 https://www.designthinkingformobility.org/wp- content / uploads/2013/10 / Learning_Launch_principles.pdf 

 https://ideas.darden.virginia.edu/the-learning-launch-how-to-grow-your-business-with-the- scientific - method 

 In our first learning launch we picked up few features from our design specifications like minimum IT involvements , engagement workflow , analytical dashboard and implemented them . We invested an effort of roughly 4 weeks to give it a real feel and create something that matches our expectations . We then released it to some CoE users along with stakeholders for 2 weeks . We started our feedback mechanism by capturing their thoughts and experience on this . The initial feedback was mixed one , some of them were encouraging but 20 % of users stated it does not fit their need as of now . We went back and incorporated them in first product launch and then added all functionalities as per the design criteria like mobility support , resource booking workflow , governance process and time tracking mechanism . It took around another 4 weeks of hard work and we launched our next version involving more CoE users and stakeholders from all line of services . We set 3 weeks of feedback this time and within a week , we started getting positive responses from all corners . The Core success is that they are now able to plan and utilize their hours effectively as our product has shown maturity in achieving service model distribution mechanism . But that ’s not the end . We started our feedback cycle again for another incremental release . 

 And now after 4 launches , we are at a pretty good shape with respect to our business model and to go for a final roll out . 

 Insight 

 Learning launch helped us a lot in the entire process of product development . We were able to transform our key assumptions to reality in an incremental process along with real time feedback from our customers . We prioritize our key requirements and slowly infuse them such that the users are able to map their expectations and identify their needs . This tool helped our product to be stronger in a cognitive way . We encouraged our users for open feedback and addressed them . This has helped us to co - create the product along with our stakeholders and users with minimum cost and time frame . We added different functionalities and made this more scalable product by leveraging this tool . This experiment did not cost much to business and it was tested using market data to realize our ultimate goal for an external market facing product . 

 Approach 

 We will apply the same tool again with same methodology we used in this use case . This tool helped us to quickly gain insights from end users or customers and incorporate them in the next launch . It can also help to examine that your idea or design criteria has performed well in the market or met the expectations of the user . This helps to perform experiment quickly and cost effectively so that we have buy in from finance . Principles of this tool aids team in shaping up a sharp product efficiently . It mitigates the risk of team ’s confirmation biasness with respect to design and provides a good learning curve for team and individuals . 


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: Reflection – Learning Launch 

 Challenge 

 I am a senior manager of a Global Service Delivery solution team for a fortune 500 MNC and we had an existing product for orchestrating our services via different Centre of Excellence ( CoE ) across the globe . But this product was neither in parity with the era of digital transformation nor was it fulfilling our need to expand services with new engagements and clients . Leading to infuriation bubbling under the surface , different CoE started using their own mechanism and created silos . This existing product was to be used by analysts of all CoE along with stakeholders of different line of services and the service delivery centers . The estimated hours of work was expected to be 400k annually , but it began shrinking around 15 % annually , due to rejection of the tool from all levels . The stakeholders were concerned since it was affecting them from both finance and governance perspective . 

 Selection 

 Since the existing product was based on analytical data set only , I formed a core team that would be influenced by design thinking and their task was to identify all possible solutions . This team started empathizing with users from all levels using journey mapping to understand current situation effectively and later used mind mapping to set the design criteria . We then reached out to Gartner to identify if there is already any off the shelf product in marketplace which could address this design criteria . As Gartner said no such product exists , our team stated using a visualization tool to ideate solutions . Out of 5 prototypes we chose to topmost one for learning launch to co - create with our users and stakeholders . 

 Application 

 We leveraged rapid application development methodology , an iterative process , which uses low code development platform , for learning launches we had . We read several articles regarding learning launch tool for better perspective . Some such articles being - 

 https://www.designthinkingformobility.org/wp- content / uploads/2013/10 / Learning_Launch_principles.pdf 

 https://ideas.darden.virginia.edu/the-learning-launch-how-to-grow-your-business-with-the- scientific - method 

 In our first learning launch we picked up few features from our design specifications like minimum IT involvements , engagement workflow , analytical dashboard and implemented them . We invested an effort of roughly 4 weeks to give it a real feel and create something that matches our expectations . We then released it to some CoE users along with stakeholders for 2 weeks . We started our feedback mechanism by capturing their thoughts and experience on this . The initial feedback was mixed one , some of them were encouraging but 20 % of users stated it does not fit their need as of now . We went back and incorporated them in first product launch and then added all functionalities as per the design criteria like mobility support , resource booking workflow , governance process and time tracking mechanism . It took around another 4 weeks of hard work and we launched our next version involving more CoE users and stakeholders from all line of services . We set 3 weeks of feedback this time and within a week , we started getting positive responses from all corners . The Core success is that they are now able to plan and utilize their hours effectively as our product has shown maturity in achieving service model distribution mechanism . But that ’s not the end . We started our feedback cycle again for another incremental release . 

 And now after 4 launches , we are at a pretty good shape with respect to our business model and to go for a final roll out . 

 Insight 

 Learning launch helped us a lot in the entire process of product development . We were able to transform our key assumptions to reality in an incremental process along with real time feedback from our customers . We prioritize our key requirements and slowly infuse them such that the users are able to map their expectations and identify their needs . This tool helped our product to be stronger in a cognitive way . We encouraged our users for open feedback and addressed them . This has helped us to co - create the product along with our stakeholders and users with minimum cost and time frame . We added different functionalities and made this more scalable product by leveraging this tool . This experiment did not cost much to business and it was tested using market data to realize our ultimate goal for an external market facing product . 

 Approach 

 We will apply the same tool again with same methodology we used in this use case . This tool helped us to quickly gain insights from end users or customers and incorporate them in the next launch . It can also help to examine that your idea or design criteria has performed well in the market or met the expectations of the user . This helps to perform experiment quickly and cost effectively so that we have buy in from finance . Principles of this tool aids team in shaping up a sharp product efficiently . It mitigates the risk of team ’s confirmation biasness with respect to design and provides a good learning curve for team and individuals .
### Output: 