Learning Launch 

 Challenge     I am a process engineer and use to work on industrial equipment improvement for which we have   sensors etc that helps us gather a significant amount of data which we can then analyse and draw   evidence of drift / wear / etc , and best action to be taken .   I have recently move into another division of the company and looking after technical service   improvement & innovation for personal medical devices . Here the challenge is very different , we still   can collect data from the equipment , but we also need to understand how the consumer / patient is   using it , and what are the most important features or functionalities to trouble shoot and to innovate   or create new solution .   Our challenge is to create solutions that can be adaptable to different people needs , so we needed   to come with a solution that has different options to better serve our customers . Going to commercial   manufacturing of new devices implies fully customised new production equipment which come at a   high cost .     Selection   We have initially worked through all the data we had but this was not relevant to our needs ,   analytical data were not the way to go , therefore we engaged into design thinking approach .   After doing ethnological survey / interviews we identified different profile and needs amongst each .   To validate our hypotheses , we decided to go for learning launch using prototype and small number   of testers .     Application     For our first learning launch , we decided to focus on a specific profile , and execute   option / customization of device for self - monitoring of sugar level in blood for diabetic kids .   We had originally identified kids as a gap in our consumers range , and during the surveys we   realised our equipment were not adapted enough for them and came with different possible options   to make them more kids friendly .   We prepared 3 prototypes of each of these options ( from physical change to the device like lighter   weight battery , smartphone application or kids friendly interface and new colours ) .   We then proceed to introduce these options to new panel and gathered their feedbacks     Insight    By applying the learning launch tool , our team identified the most valuable new options / features for   young customers , based on scalability of the most popular options we were able to activate further   development , and refined our feedback via additional prototype testing and then manufacturing and   commercialisation of these . In the meantime , we moved to the other profiles we had identified and   looked first at all the options which could be produced same process equipment which helped us to   move even faster to build the prototype .      Approach    Given the need for real consumer feedback regarding practicality and appeal of the options   ( especially for young kids ) the learning launch using prototype they could use and bring along   seemed the best approach to be able to communicate the options clearly to the young consumers . 


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     I am a process engineer and use to work on industrial equipment improvement for which we have   sensors etc that helps us gather a significant amount of data which we can then analyse and draw   evidence of drift / wear / etc , and best action to be taken .   I have recently move into another division of the company and looking after technical service   improvement & innovation for personal medical devices . Here the challenge is very different , we still   can collect data from the equipment , but we also need to understand how the consumer / patient is   using it , and what are the most important features or functionalities to trouble shoot and to innovate   or create new solution .   Our challenge is to create solutions that can be adaptable to different people needs , so we needed   to come with a solution that has different options to better serve our customers . Going to commercial   manufacturing of new devices implies fully customised new production equipment which come at a   high cost .     Selection   We have initially worked through all the data we had but this was not relevant to our needs ,   analytical data were not the way to go , therefore we engaged into design thinking approach .   After doing ethnological survey / interviews we identified different profile and needs amongst each .   To validate our hypotheses , we decided to go for learning launch using prototype and small number   of testers .     Application     For our first learning launch , we decided to focus on a specific profile , and execute   option / customization of device for self - monitoring of sugar level in blood for diabetic kids .   We had originally identified kids as a gap in our consumers range , and during the surveys we   realised our equipment were not adapted enough for them and came with different possible options   to make them more kids friendly .   We prepared 3 prototypes of each of these options ( from physical change to the device like lighter   weight battery , smartphone application or kids friendly interface and new colours ) .   We then proceed to introduce these options to new panel and gathered their feedbacks     Insight    By applying the learning launch tool , our team identified the most valuable new options / features for   young customers , based on scalability of the most popular options we were able to activate further   development , and refined our feedback via additional prototype testing and then manufacturing and   commercialisation of these . In the meantime , we moved to the other profiles we had identified and   looked first at all the options which could be produced same process equipment which helped us to   move even faster to build the prototype .      Approach    Given the need for real consumer feedback regarding practicality and appeal of the options   ( especially for young kids ) the learning launch using prototype they could use and bring along   seemed the best approach to be able to communicate the options clearly to the young consumers .
### Output: 