Challenge 

 Like many businesses today , my organization can no longer rely on the historical ideation 

 cycle . We were founded at the horizon of innovative analytical solutions that for years carried   us to substantial profits and helped push the boundaries of what was possible . However , new   solutions , new technologies , and new ways of working have helped competition catch up and ,   in some cases , pass us by . The model we have been using in which , we look for major products   and markets to solve our growth concerns is no longer sustainable . We began as a scientific   company , and in order to make our way back to the front of the pack , we must get back to our   experimental roots . The tool that I have chosen is the Learning Launch tool . 

 Selection 

 The Learning Launch tool is a methodology that organizations can use to apply a scientific 

 approach to the ideation and development of new products , solutions , and value chains . Often   times though , when you put a group of the smartest people in a room together , they can get in   their own way . In the recent past our growth engines were piloted based on assumptions –   assumptions on what customers may want , what the market will be five years from now , and   even the assumption that the assumptions we are making were correct . In the Learning Launch   tool , you are rigorously and scientifically testing the assumptions , theories , and hypotheses you   are making to validate , and just as importantly , invalidate your decisions . This is iterative , fast ,   and inexpensive compared to the full development and deployment process . As Volker Eichhorn   describes , it allows you peel back the layers like an onion until you get to the heart of the   problem or need that we are wanting to address . 

 Application 

 The way this tool was applied was through the redevelopment of the New Revenue Board 

 and addition of divisional gatekeeping for hypothesis testing and validation before any revenue   projections or market predictions get pitched . We want to add structure and rigor around   taking an idea and letting individuals run with it . When originally implementing the learning   launch , we had to have conversations around encouragement of innovative thinking , and   standardization around methodologies . As a multibillion - dollar company with several operating   organizations , when we are making decisions around resource allocation , we need to have a   standardized approach around judgement of proposals . 

 We addressed this issue in two ways . First , we created a standard process companywide 

 that any individual can follow that will take them through the hypothesis generation , testing ,   and adjustment cycle . Once an idea has been iterated through and we have learned and   learned and learned and the idea has been polished enough that there is something substantial   there it can be taken to the New Revenue Board for review . The second change we have made   is to standardize a ‘ rubric ’ that board members use to evaluate proposals . By score carding in   key areas we can easily compare proposals that come from banking and finance to IoT , to   cloud , to supply chain . As part of the scorecard as well , we want to avoid looking for necessarily 

 big wins , and instead focus on potential . If something comes across our desk that is a big win   great , if something else has the potential , we build out an exploratory party to operate   independently to pursue the idea further and keep them from getting bogged down by politics ,   company culture , resource drain , etc . 

 Insight 

 By applying this tool , it was easy to see how often the assumptions we were making were 

 incorrect . As a data driven company at the forefront of analytics , too often we were relying on   gut feeling and intuition to make decisions . This has helped drive the rigorous approach to   innovation that we were founded on . When doing more research into this area , I have also   realized how companies can fall into what Clayton Christensen coined , The Innovator ’s   Dilemma . We have seen great ideas come out of many of our divisions that do n’t fit their   customer base . So , they simply get shelved . However , we need to be thinking more broadly and   avoid falling into the trap of innovation . Not every product is going to help us hit our growth   target in the next six months . Some need time and that is okay . By demonstrating opportunities   and iteratively testing the markets we can better identify early on whether or not a new   product / feature / functionality makes sense for the ‘ projected ’ market and if not , start looking   to identify where it might fit instead of just shelving the innovation until someone else comes   along and beats us to the punch . We ca n’t ignore long - term progress because it does n’t fit our   12 month revenue growth requirements that are arbitrarily set to make stakeholders happy . 

 Approach 

 For this specific situation , Learning Launch makes sense . I think going forward what I 

 would like to see however , is a focus on cross organizational ideation and opportunities to   apply some of the other tools to the process . As discussed , when your organization is siloed it   allows each division to operate in a way that makes sense for their sector . You would n’t sell   retail solutions the same way you would regulatory compliance . However , one issue is   knowledge management and diversity in your thinking . Regulatory Compliance folks think like   regulatory compliance people , not retailer solutions folks . What may be a good policy to adopt   is to develop rotational innovation programs and hackathons in which developers and   marketers and operations people get paired up with individuals from other divisions to work   through interesting solutions and conduct research on addressing meaningful problems . In this   process , using storytelling , mind mapping and visualization would really add an extra layer to   the work being conducted . 


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: Challenge 

 Like many businesses today , my organization can no longer rely on the historical ideation 

 cycle . We were founded at the horizon of innovative analytical solutions that for years carried   us to substantial profits and helped push the boundaries of what was possible . However , new   solutions , new technologies , and new ways of working have helped competition catch up and ,   in some cases , pass us by . The model we have been using in which , we look for major products   and markets to solve our growth concerns is no longer sustainable . We began as a scientific   company , and in order to make our way back to the front of the pack , we must get back to our   experimental roots . The tool that I have chosen is the Learning Launch tool . 

 Selection 

 The Learning Launch tool is a methodology that organizations can use to apply a scientific 

 approach to the ideation and development of new products , solutions , and value chains . Often   times though , when you put a group of the smartest people in a room together , they can get in   their own way . In the recent past our growth engines were piloted based on assumptions –   assumptions on what customers may want , what the market will be five years from now , and   even the assumption that the assumptions we are making were correct . In the Learning Launch   tool , you are rigorously and scientifically testing the assumptions , theories , and hypotheses you   are making to validate , and just as importantly , invalidate your decisions . This is iterative , fast ,   and inexpensive compared to the full development and deployment process . As Volker Eichhorn   describes , it allows you peel back the layers like an onion until you get to the heart of the   problem or need that we are wanting to address . 

 Application 

 The way this tool was applied was through the redevelopment of the New Revenue Board 

 and addition of divisional gatekeeping for hypothesis testing and validation before any revenue   projections or market predictions get pitched . We want to add structure and rigor around   taking an idea and letting individuals run with it . When originally implementing the learning   launch , we had to have conversations around encouragement of innovative thinking , and   standardization around methodologies . As a multibillion - dollar company with several operating   organizations , when we are making decisions around resource allocation , we need to have a   standardized approach around judgement of proposals . 

 We addressed this issue in two ways . First , we created a standard process companywide 

 that any individual can follow that will take them through the hypothesis generation , testing ,   and adjustment cycle . Once an idea has been iterated through and we have learned and   learned and learned and the idea has been polished enough that there is something substantial   there it can be taken to the New Revenue Board for review . The second change we have made   is to standardize a ‘ rubric ’ that board members use to evaluate proposals . By score carding in   key areas we can easily compare proposals that come from banking and finance to IoT , to   cloud , to supply chain . As part of the scorecard as well , we want to avoid looking for necessarily 

 big wins , and instead focus on potential . If something comes across our desk that is a big win   great , if something else has the potential , we build out an exploratory party to operate   independently to pursue the idea further and keep them from getting bogged down by politics ,   company culture , resource drain , etc . 

 Insight 

 By applying this tool , it was easy to see how often the assumptions we were making were 

 incorrect . As a data driven company at the forefront of analytics , too often we were relying on   gut feeling and intuition to make decisions . This has helped drive the rigorous approach to   innovation that we were founded on . When doing more research into this area , I have also   realized how companies can fall into what Clayton Christensen coined , The Innovator ’s   Dilemma . We have seen great ideas come out of many of our divisions that do n’t fit their   customer base . So , they simply get shelved . However , we need to be thinking more broadly and   avoid falling into the trap of innovation . Not every product is going to help us hit our growth   target in the next six months . Some need time and that is okay . By demonstrating opportunities   and iteratively testing the markets we can better identify early on whether or not a new   product / feature / functionality makes sense for the ‘ projected ’ market and if not , start looking   to identify where it might fit instead of just shelving the innovation until someone else comes   along and beats us to the punch . We ca n’t ignore long - term progress because it does n’t fit our   12 month revenue growth requirements that are arbitrarily set to make stakeholders happy . 

 Approach 

 For this specific situation , Learning Launch makes sense . I think going forward what I 

 would like to see however , is a focus on cross organizational ideation and opportunities to   apply some of the other tools to the process . As discussed , when your organization is siloed it   allows each division to operate in a way that makes sense for their sector . You would n’t sell   retail solutions the same way you would regulatory compliance . However , one issue is   knowledge management and diversity in your thinking . Regulatory Compliance folks think like   regulatory compliance people , not retailer solutions folks . What may be a good policy to adopt   is to develop rotational innovation programs and hackathons in which developers and   marketers and operations people get paired up with individuals from other divisions to work   through interesting solutions and conduct research on addressing meaningful problems . In this   process , using storytelling , mind mapping and visualization would really add an extra layer to   the work being conducted .
### Output: 