Example Reflection – Learning Launch 

 Challenge & Selection 

 At the moment I work for a Danish company specialising in food quality analysis at   the global scale . The company is building both hardware- sample analysis   instruments and software . The high rate of instruments utilisation , are crucial to   global food producers . Hence monitoring and preventing any downtime of   instruments can help to avoid big losses in production capacity . 

 The challenge is to find out if we have enough data points to accurately predict   potential instrument downtime in order to give an early warning . The design thinking   methodology can quickly address this issue focusing on customers needs . The   process will follow specific steps that will help us better understand the current   situation and to uncover what are the underlying needs of customers when trying to   solve the problem of instruments downtime predictions . 

 Application 

 After collecting the data to assess “ What is the problem ” from as broad perspective   as possible , we would like to examine what is the “ As - Is ” situation . We could do that   by visiting some customers and observing how they use our instruments and   conducting interviews . The question we could ask could be related to e.g what do   customers do when there is an actual downtime ? How often this occurs ? Are those   incidents reported ? How quickly do we send a technician to fix the issue ? Who is   accountable for the downtime if standard operating procedures ( SOP ) are not   followed ?   We could then combine that empirical data with other data points to   formulate our hypothesis that downtime of our instruments ( or any production critical   instruments ) can have a direct impact on revenue losses , hence following SOP is   critical . 

 By developing mind - mapping in collaboration with customers we could address what   are the SOP for each interviewed company and what each instrument ’s operator is   doing to follow it . That will help us to address if there are any gaps in the process . It   will also help us to generate new ideas on what data points we can collect , either   internally or by asking customers to submit their operating practice . Knowing that will   make is easier for us to find out if those data points are sufficient enough to correctly   predict potential instrument downtime and perhaps also to address the root cause of   it . 

 That is where we ’ll create a testable prototype to address our assumption . This is the   learning launch . The purpose is to learn not to introduce a new product yet . The 

 learning launch is based on an idea which has to be suitable for a specific person / s ,   that has a specific need . The idea should meet that need and provide better solution   than the current alternative . In this case , the idea is to develop a service , e.g an app   or data dashboard that is suitable to our customers who are looking for a quick   notification about potential downtime as an alternative to the current process which is   reactive rather than proactive , resulting in slowed down or event stopped production . 

 Insight 

 Since this is a real project , planned to be tested the next month , I can not yet say   much about the insight that I ’ve gained from applying the learning launch tool .   Needless to say , I ’m very excited about implementing the methods , especially that   the company I work for is very conservative and usually , customer tests are taking   months to complete . To run such a test in a short amount of time and get relevant   insides through this method and this structured approach is something very new to   this company . 

 Approach 

 I believe that regardless of the results from this learning launch I will be positive   continuing with design thinking . Perhaps in order to get even quicker hypothesis   validation I will use google design sprint and then conduct more detailed   anthropological research after the hypothesis will be quickly tested . 


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: Example Reflection – Learning Launch 

 Challenge & Selection 

 At the moment I work for a Danish company specialising in food quality analysis at   the global scale . The company is building both hardware- sample analysis   instruments and software . The high rate of instruments utilisation , are crucial to   global food producers . Hence monitoring and preventing any downtime of   instruments can help to avoid big losses in production capacity . 

 The challenge is to find out if we have enough data points to accurately predict   potential instrument downtime in order to give an early warning . The design thinking   methodology can quickly address this issue focusing on customers needs . The   process will follow specific steps that will help us better understand the current   situation and to uncover what are the underlying needs of customers when trying to   solve the problem of instruments downtime predictions . 

 Application 

 After collecting the data to assess “ What is the problem ” from as broad perspective   as possible , we would like to examine what is the “ As - Is ” situation . We could do that   by visiting some customers and observing how they use our instruments and   conducting interviews . The question we could ask could be related to e.g what do   customers do when there is an actual downtime ? How often this occurs ? Are those   incidents reported ? How quickly do we send a technician to fix the issue ? Who is   accountable for the downtime if standard operating procedures ( SOP ) are not   followed ?   We could then combine that empirical data with other data points to   formulate our hypothesis that downtime of our instruments ( or any production critical   instruments ) can have a direct impact on revenue losses , hence following SOP is   critical . 

 By developing mind - mapping in collaboration with customers we could address what   are the SOP for each interviewed company and what each instrument ’s operator is   doing to follow it . That will help us to address if there are any gaps in the process . It   will also help us to generate new ideas on what data points we can collect , either   internally or by asking customers to submit their operating practice . Knowing that will   make is easier for us to find out if those data points are sufficient enough to correctly   predict potential instrument downtime and perhaps also to address the root cause of   it . 

 That is where we ’ll create a testable prototype to address our assumption . This is the   learning launch . The purpose is to learn not to introduce a new product yet . The 

 learning launch is based on an idea which has to be suitable for a specific person / s ,   that has a specific need . The idea should meet that need and provide better solution   than the current alternative . In this case , the idea is to develop a service , e.g an app   or data dashboard that is suitable to our customers who are looking for a quick   notification about potential downtime as an alternative to the current process which is   reactive rather than proactive , resulting in slowed down or event stopped production . 

 Insight 

 Since this is a real project , planned to be tested the next month , I can not yet say   much about the insight that I ’ve gained from applying the learning launch tool .   Needless to say , I ’m very excited about implementing the methods , especially that   the company I work for is very conservative and usually , customer tests are taking   months to complete . To run such a test in a short amount of time and get relevant   insides through this method and this structured approach is something very new to   this company . 

 Approach 

 I believe that regardless of the results from this learning launch I will be positive   continuing with design thinking . Perhaps in order to get even quicker hypothesis   validation I will use google design sprint and then conduct more detailed   anthropological research after the hypothesis will be quickly tested .
### Output: 