Learning Launch 

 Challenge & Selection 

 I selected the Learning Launch tool , to test our new idea with real stakeholders and   understand if we have a complete solution that works or we need to return to the table   and redesign and improve the model . I never used this tool before , usually we identify   the customer ’s needs , take assumptions , develop the product and deploy the project .   After several months , we return to verify the solutions and often we realize that we   did not get the expected user engagement . More details about Learning Launch tool   could be found in Darden Business Publishing , the technical note Design Learning   Launches ( Angelo Caruso and Anthony Alfaro ) . I used this tool in a   project with the Control Room Operation Team of a Power Plant , we ’re developing   recommender system that identifies and priorize witch electrical load shutdown during   a power instability . The recommender system will be design to works automatically   but can be turned off if the operator identify an abnormal execution . 

 Application 

 We start applying the tool under some stakeholder ’s criteria , test only in systems that   could be shutdown without major implications , all the decisions of the recommender   system need to be confirmed by the operator . This way the recommender system have   the capability to shutdown 5 % of the loads in the power plant . In the first moment we   trained the control room operators to use the recommender system and turned on the   feature , at the shift end we collected a 3 question form with one of the team members :   1 ) How many time of your shift you keep the recommender system in automatic ? 2 )   The recommender system give you some insight ? Why do you trust or not in the   recommender system ? 

 We start to receive in the forms some tips and suggestions from the operators team to   improve the recommender system , and we revised and apply the features as fast as   we could . Initially the recommender system was keep in automatic 10 or 20 % of time   and often turned off in a power instability , after 7 days the operators kept the   recommender system fully operational and suggested to remove the action   confirmation . Therefore , we removed the confirmation function and starts to scale the   Learning Launch to cover 50 % of the power plant loads . 

 Insight & Approach 

 We learn with this tool how to promote the engagement of the team with a new tool   or feature in the control room of the power plant . First we need to train the teams   and before deploy a big idea we runs some tests in non - critical loads / systems to gain   the team trust , other important issue is the forms when the team notice that the tips   and suggestions was being implemented this promotes more engagement and then they   keep the recommender system running automatically for more time . 

 So the Learning Launch tool proves that is a useful tool , and can granted the success   of an new idea because the development team can have an online feedback of the   system and improve , redesign or leave the idea before discredit . 

 After this first contact with the Learning Launch I ’ll try to use the tool in every stage   of project before scale up , because sometimes a successful system that works in one   plant does n’t have the same success in other places . This strategy also provides a fast   a response of the development team , because is easier fix or redesign a small system   then a big system that cover all critical operation in a new plant . 


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: Learning Launch 

 Challenge & Selection 

 I selected the Learning Launch tool , to test our new idea with real stakeholders and   understand if we have a complete solution that works or we need to return to the table   and redesign and improve the model . I never used this tool before , usually we identify   the customer ’s needs , take assumptions , develop the product and deploy the project .   After several months , we return to verify the solutions and often we realize that we   did not get the expected user engagement . More details about Learning Launch tool   could be found in Darden Business Publishing , the technical note Design Learning   Launches ( Angelo Caruso and Anthony Alfaro ) . I used this tool in a   project with the Control Room Operation Team of a Power Plant , we ’re developing   recommender system that identifies and priorize witch electrical load shutdown during   a power instability . The recommender system will be design to works automatically   but can be turned off if the operator identify an abnormal execution . 

 Application 

 We start applying the tool under some stakeholder ’s criteria , test only in systems that   could be shutdown without major implications , all the decisions of the recommender   system need to be confirmed by the operator . This way the recommender system have   the capability to shutdown 5 % of the loads in the power plant . In the first moment we   trained the control room operators to use the recommender system and turned on the   feature , at the shift end we collected a 3 question form with one of the team members :   1 ) How many time of your shift you keep the recommender system in automatic ? 2 )   The recommender system give you some insight ? Why do you trust or not in the   recommender system ? 

 We start to receive in the forms some tips and suggestions from the operators team to   improve the recommender system , and we revised and apply the features as fast as   we could . Initially the recommender system was keep in automatic 10 or 20 % of time   and often turned off in a power instability , after 7 days the operators kept the   recommender system fully operational and suggested to remove the action   confirmation . Therefore , we removed the confirmation function and starts to scale the   Learning Launch to cover 50 % of the power plant loads . 

 Insight & Approach 

 We learn with this tool how to promote the engagement of the team with a new tool   or feature in the control room of the power plant . First we need to train the teams   and before deploy a big idea we runs some tests in non - critical loads / systems to gain   the team trust , other important issue is the forms when the team notice that the tips   and suggestions was being implemented this promotes more engagement and then they   keep the recommender system running automatically for more time . 

 So the Learning Launch tool proves that is a useful tool , and can granted the success   of an new idea because the development team can have an online feedback of the   system and improve , redesign or leave the idea before discredit . 

 After this first contact with the Learning Launch I ’ll try to use the tool in every stage   of project before scale up , because sometimes a successful system that works in one   plant does n’t have the same success in other places . This strategy also provides a fast   a response of the development team , because is easier fix or redesign a small system   then a big system that cover all critical operation in a new plant .
### Output: 