Learning Launch - Improvement in 

 bottling lines 

 Challenge : 

 Today I work in the area of beverage packaging , which has long been developing 

 technologically and has a very specific and protocolized problem solution support that 

 normally requires a very specialized workforce in this sector in the industry . 

 Two years ago , we started having a lot of problems related to transportation of bottles . 

 The glass bottles were heavily impacted during shipping and this led to a high index of 

 glass breaking and down time . All our indicators of loss and performance were being 

 impacted by this . 

 Learning Laucnh : 

 In the market , the existing solution requires a labor force specialized in automation to 

 adjust speed and modulation of transport . Every start of the year , we faced the same 

 question : how to increase efficiency , knowing that we can not afford the automation 

 service ? 

 We needed to develop solutions that were really engaged with consumer 

 expectations , testing those solutions in practice . 

 That ’s why we chose the “ Learning Launch ” tool . 

 Application : 

 In these same situations , while trying to explain high investments ( in which top 

 management believed but did not want to invest ) we had a group of operators that 

 had other cheaper solutions but in which the company saw no potential . 

 To finally prove the investment , we made the prototypes of how the production would 

 be with both solutions . 

 We tested the two solutions in small tests , planned in the smallest possible time levels : 

 In the end , we came to the conclusion that the homemade solution , in addition to 

 being cheaper , was most suitable for the expected levels of efficiency and bottle 

 breakage . 

 Insight : 

 Without learning launch methodology , we would continue with the old automation 

 solutions . Arriving at lower solutions than we arrived , with greater investments . 

 Approach : 

 In the next situations where we are faced with this type of problem , we will certainly 

 concentrate on listening to people at the end of the chain and doing more 

 experiments , instead of following patterns of solutions that we simply believe , without 

 experimentation , be the best . 


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 - Improvement in 

 bottling lines 

 Challenge : 

 Today I work in the area of beverage packaging , which has long been developing 

 technologically and has a very specific and protocolized problem solution support that 

 normally requires a very specialized workforce in this sector in the industry . 

 Two years ago , we started having a lot of problems related to transportation of bottles . 

 The glass bottles were heavily impacted during shipping and this led to a high index of 

 glass breaking and down time . All our indicators of loss and performance were being 

 impacted by this . 

 Learning Laucnh : 

 In the market , the existing solution requires a labor force specialized in automation to 

 adjust speed and modulation of transport . Every start of the year , we faced the same 

 question : how to increase efficiency , knowing that we can not afford the automation 

 service ? 

 We needed to develop solutions that were really engaged with consumer 

 expectations , testing those solutions in practice . 

 That ’s why we chose the “ Learning Launch ” tool . 

 Application : 

 In these same situations , while trying to explain high investments ( in which top 

 management believed but did not want to invest ) we had a group of operators that 

 had other cheaper solutions but in which the company saw no potential . 

 To finally prove the investment , we made the prototypes of how the production would 

 be with both solutions . 

 We tested the two solutions in small tests , planned in the smallest possible time levels : 

 In the end , we came to the conclusion that the homemade solution , in addition to 

 being cheaper , was most suitable for the expected levels of efficiency and bottle 

 breakage . 

 Insight : 

 Without learning launch methodology , we would continue with the old automation 

 solutions . Arriving at lower solutions than we arrived , with greater investments . 

 Approach : 

 In the next situations where we are faced with this type of problem , we will certainly 

 concentrate on listening to people at the end of the chain and doing more 

 experiments , instead of following patterns of solutions that we simply believe , without 

 experimentation , be the best .
### Output: 