Learning Launch Reflection 

 Challenge & Selection 

 I am Sales Analytics Coordinator for zolie ( National Institute   of Coffee ) of a Beauty Direct Selling company   that have almost 415k representatives ( sellers ) in our cluster . Data analytics are very important for   build consistent insights to make certain decisions about product launches or incentives programs   to improve their profits and company itself . These 415k representatives are organized in different   zones or regions in each country depending also of different selling behaviors that segmented the   representatives in different ways . Changing our work methods to an agile method , we star   working different multi skills teams to have different knowledge resources working in the same   “ table ” . We focused in work in projects than lasts between 2 and 4 weeks ( depending in the size of   the project and the impact it will have ) . 

 Application 

 We usually put together work teams that not necessarily already exist . This means that work in   agile teams made of people of different functional areas of the company that have direct relation   with the project itself . We consider that projects tests have to be shorts , good and cheap . That ’s   why these do n’t last less than 2 weeks ( they have to bring real impact and solutions ) but less than   4 weeks ( shorts and cheap ) . Any person of each team bring insight about his knowledge area   before discussing any action . After that we build the business case understanding which   hypothesis we are going to prove ( or test ) and how we are going to measure if that hypothesis had   the results we expected or not . After launching we present the business case to our sponsor ( or   financial planning maybe ) to make the skeptical questions to reinforce the project . 

 Insight & Approach 

 To have quick learning and continuous improvement , we first launch the project ( or program ) in a   controlled zone or region to measure and reduce possible impacts . We identify which will be our   Group of Control ( Representatives of similar characteristics to the ones we are talking to ) to have   fast and simple comparison of the results of the project . 

 Ones we realize that the project brings the result we expected , we scale this project to the rest of   the region or the country or either the cluster . 

 If project does not bring good results , we register what does n’t result and iterate with some   changes after analyzing what we think we have to change with the learnings we take 


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 Reflection 

 Challenge & Selection 

 I am Sales Analytics Coordinator for zolie ( National Institute   of Coffee ) of a Beauty Direct Selling company   that have almost 415k representatives ( sellers ) in our cluster . Data analytics are very important for   build consistent insights to make certain decisions about product launches or incentives programs   to improve their profits and company itself . These 415k representatives are organized in different   zones or regions in each country depending also of different selling behaviors that segmented the   representatives in different ways . Changing our work methods to an agile method , we star   working different multi skills teams to have different knowledge resources working in the same   “ table ” . We focused in work in projects than lasts between 2 and 4 weeks ( depending in the size of   the project and the impact it will have ) . 

 Application 

 We usually put together work teams that not necessarily already exist . This means that work in   agile teams made of people of different functional areas of the company that have direct relation   with the project itself . We consider that projects tests have to be shorts , good and cheap . That ’s   why these do n’t last less than 2 weeks ( they have to bring real impact and solutions ) but less than   4 weeks ( shorts and cheap ) . Any person of each team bring insight about his knowledge area   before discussing any action . After that we build the business case understanding which   hypothesis we are going to prove ( or test ) and how we are going to measure if that hypothesis had   the results we expected or not . After launching we present the business case to our sponsor ( or   financial planning maybe ) to make the skeptical questions to reinforce the project . 

 Insight & Approach 

 To have quick learning and continuous improvement , we first launch the project ( or program ) in a   controlled zone or region to measure and reduce possible impacts . We identify which will be our   Group of Control ( Representatives of similar characteristics to the ones we are talking to ) to have   fast and simple comparison of the results of the project . 

 Ones we realize that the project brings the result we expected , we scale this project to the rest of   the region or the country or either the cluster . 

 If project does not bring good results , we register what does n’t result and iterate with some   changes after analyzing what we think we have to change with the learnings we take
### Output: 