Reflection - Learning Launch 

 New Chemical System Launch owing to Changes in Government Regulation 

 Date : 15.04.2020 

 Challenge 

 I work for a German Multinational in India as an R&D Scientist . The organization manufactures raw   materials which can then be processed by our clients into high - performance plastics . Recently , due to   the changes in government regulations , we had to stop manufacturing the conventional systems and   switch to a more environment friendly system . 

 Additionally , an energy performance regulation was also passed which meant that the new system had   to be more efficient in terms of performance . So in nutshell , we had to come up with a product which   was not only greener but also more efficient . 

 The scope of project included the R&D , Sales , Marketing , Production and Procurement teams . The   timeline is approx . 2 months to ensure readiness before the start of peak season . 

 Selection 

 The tool that we used was Learning Launch . We had a fair idea on the kind of challenge and also a   reasonable alignment amongst the various departments . Moreover , since the product is a critical one ,   prototyping and it subsequent testing is of utmost importance . This will help us retain our customers ’   faith . 

 Application 

 Firstly , we had joint meeting with different teams to understand their perspective , challenges and   strengths . We then compiled the above inputs to get a holistic picture of what is possible and what is   not ! This not only helped in establishing alignment among the various departments but also saved time   as the product development could now take place after the feedback from various departments rather   than incorporating it after reaching a stage in product development . 

 The R&D team conducted many experiments to come up with a few close solutions . These solutions   were then tested at our scale - up simulation lab . The data generated was slightly different from our   expectation and as a result , after continuous iterations , we were able to get some solutions . 

 Finally , we clustered our customers on the probability of success and commercialization . There was   another meeting with the teams to have alignment on our readiness before learning launch process . The   system was finally run in Pilot operations at few of our customers . 

 Insights 

 The assumptions in the form of our trial product were finally tested at customers across different   Geographies . Although , there were few variations against our expected results . The product more or   less fit into the expectations of our customers . This is because of application of smaller learning launch   process at our lab even before a major learning launch at customer ’s end . This had greatly helped us in   testing our assumptions , learning about the possible flaws and then working on rectifying it . The process   in nutshell broadened our perspective on the launch process . 

 The few fine - tunings are being incorporated in the system and we have even got commercial orders   from few of our customers . 

 Approach 

 Although , we had applied the Learning Launch earlier as well , it was not as structured and mostly on an   ad hoc basis due to which there have always been a few glitches in the process / system . Another ,   learning would be to involve all the stakeholders which we earlier missed out somehow . This helps in   bringing the essential elements of diversity on the table and also aligning the various teams . 


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 

 New Chemical System Launch owing to Changes in Government Regulation 

 Date : 15.04.2020 

 Challenge 

 I work for a German Multinational in India as an R&D Scientist . The organization manufactures raw   materials which can then be processed by our clients into high - performance plastics . Recently , due to   the changes in government regulations , we had to stop manufacturing the conventional systems and   switch to a more environment friendly system . 

 Additionally , an energy performance regulation was also passed which meant that the new system had   to be more efficient in terms of performance . So in nutshell , we had to come up with a product which   was not only greener but also more efficient . 

 The scope of project included the R&D , Sales , Marketing , Production and Procurement teams . The   timeline is approx . 2 months to ensure readiness before the start of peak season . 

 Selection 

 The tool that we used was Learning Launch . We had a fair idea on the kind of challenge and also a   reasonable alignment amongst the various departments . Moreover , since the product is a critical one ,   prototyping and it subsequent testing is of utmost importance . This will help us retain our customers ’   faith . 

 Application 

 Firstly , we had joint meeting with different teams to understand their perspective , challenges and   strengths . We then compiled the above inputs to get a holistic picture of what is possible and what is   not ! This not only helped in establishing alignment among the various departments but also saved time   as the product development could now take place after the feedback from various departments rather   than incorporating it after reaching a stage in product development . 

 The R&D team conducted many experiments to come up with a few close solutions . These solutions   were then tested at our scale - up simulation lab . The data generated was slightly different from our   expectation and as a result , after continuous iterations , we were able to get some solutions . 

 Finally , we clustered our customers on the probability of success and commercialization . There was   another meeting with the teams to have alignment on our readiness before learning launch process . The   system was finally run in Pilot operations at few of our customers . 

 Insights 

 The assumptions in the form of our trial product were finally tested at customers across different   Geographies . Although , there were few variations against our expected results . The product more or   less fit into the expectations of our customers . This is because of application of smaller learning launch   process at our lab even before a major learning launch at customer ’s end . This had greatly helped us in   testing our assumptions , learning about the possible flaws and then working on rectifying it . The process   in nutshell broadened our perspective on the launch process . 

 The few fine - tunings are being incorporated in the system and we have even got commercial orders   from few of our customers . 

 Approach 

 Although , we had applied the Learning Launch earlier as well , it was not as structured and mostly on an   ad hoc basis due to which there have always been a few glitches in the process / system . Another ,   learning would be to involve all the stakeholders which we earlier missed out somehow . This helps in   bringing the essential elements of diversity on the table and also aligning the various teams .
### Output: 