Challenge 

 Since 2011 I lead a product team at a Peruvian bank . I have the role of Product Manager , which involves   leading and coaching a team of cross - functional people to develop and evolve a product . The product we   were in charge was called Manyar and it´s a mobile application to look for restaurant information and   menu and also to get dishes recommendations ( we used machine learning for this one ) . 

 However , as COVID-19 stroke in Peru ( we are already in day 60 and restaurants have been closed all this   time ) we needed to change our business model in order to survive . We have a limited budget and could n’t   afford to undertake a big bet and be mistaken . This is where Design Thinking enters . 

 Selection 

 We decided to use the Learning Launch since this would allow us to test small bets and measure the results   in order to get fast and cheap feedback from our users -as explained in the video about Learning Launch .   We would then use this feedback to learn if our ideas would serve to have a business model pivot towards   a new one . 

 Since conducting this pivot in the traditional way would involve time and money ( and both were limited   resources to us ) , Learning Launch became a natural alternative to our challenge , since as the course   stated , it provides a better solution that is based on feedback instead of the traditional way based on   assumptions and tweaks . 

 Application 

 We decided to create small experiments . We had a Business Model Canvas from the previous business   model and we copied it 4 times in order to create 4 pivots we would like to test on the real market with   real customers . 

 Our principal criteria was the find product - market fit , which would allow the new business model to grow   and ideally become profitable . So , we select the 4 most voted ideas from our visual brainstorming session-   conducted with stakeholders and   early adopters from our business model . It was challenging since we   had to conduct this sessions remotely due to social isolation but we managed to get everybody   communicated using the tool Mural which also allows us to use visual tools to facilitate communication   among people . Once in Mural , we managed to rank the 4 most voted pivots : gastronomy social network ,   take - away and delivery solution , restaurant to consumer marketplace and recipes / cook - it - yourself app . 

 We got the usability results from our previous user research and used it to design 4 prototypes using the   Marvel tool in order to have a testable high - fidelity version of the 4 new pivots , presented as mobile   applications . Marvel also allows you to install those prototypes on the phones so we had to distributed   these new versions according to a split test . 

 We selected 100 users who liked or loved us ( had an NPS higher than 8) and also 100 users who hated us   ( NPS lower than 3 ) . We then created 4 random samples of 50 people ( 25 from each segment ) to test the   pivots . We called and emailed the people and got down to 40 people per sample since some of them   never answered . After that , we sent the prototypes via WhatsApp so they could download it directly on 

 their smartphones / iPhones . After the test , we conducted some interviews to get qualitative and   quantitative feedback from users . 

 Insights 

 The learning launch was successful . We managed to get information about the prototypes and learned   our customers did n’t care about the delivery and take - away pivot since they were still fearing the COVID   and believed restaurants could potentially lie about or make mistakes about security measures to prevent   COVID . Even though they idea sounded good , most of the people learned to cook and were improving at   their cooking skills as quarantine continued . This insight was radical to the point only 1 person ( which lived   in upper - class part of Lima city ) mentioned they would consider using this application . 

 This applied to restaurant - user marketplace since it also involved restaurants . It seemed like customers   were really doubting about restaurants implementing and executing security measures correctly . They   also wanted to have more control about the food they and their families ate . 

 On the other side , the prototypes about cook - it - yourself and the gastronomy social network were the one   with better appreciation . Insights about having recipes and cook - it - yourself content inside the social   network were flowing in more than 80 % of users ( 82.5 % ) . For cook - it - yourself prototype , people told they   wanted to have a social usage , to share and get recipes and information with their families and friends ,   who where locked away due to COVID . 67.5 % of the users provided this feedback . 

 Overall , this allowed us to unify both prototypes into a food social network we could them take to a next   iteration of the prototype and also allowed us to create surveys which we would pass to all our users in   order to understand which features they would prefer to have implemented first . 

 Approach 

 The usage of Learning Launch was successful since it has allowed us to launch a business model pivot   which we just launched and got 1000 active users in the first weekend . 

 However , what I would do differently is to couple Mind Mapping as an alternative to traditional   brainstorming since this would avoid getting bias and too much confirmation bias about own ideas and   instead focus the development of ideas around design criteria . It would also allow us to consider the   number of design criteria met as a way to rank ideas instead of conducting a simple voting , which can lead   to some powerful ideas because we resist them for their novelty . 


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 

 Since 2011 I lead a product team at a Peruvian bank . I have the role of Product Manager , which involves   leading and coaching a team of cross - functional people to develop and evolve a product . The product we   were in charge was called Manyar and it´s a mobile application to look for restaurant information and   menu and also to get dishes recommendations ( we used machine learning for this one ) . 

 However , as COVID-19 stroke in Peru ( we are already in day 60 and restaurants have been closed all this   time ) we needed to change our business model in order to survive . We have a limited budget and could n’t   afford to undertake a big bet and be mistaken . This is where Design Thinking enters . 

 Selection 

 We decided to use the Learning Launch since this would allow us to test small bets and measure the results   in order to get fast and cheap feedback from our users -as explained in the video about Learning Launch .   We would then use this feedback to learn if our ideas would serve to have a business model pivot towards   a new one . 

 Since conducting this pivot in the traditional way would involve time and money ( and both were limited   resources to us ) , Learning Launch became a natural alternative to our challenge , since as the course   stated , it provides a better solution that is based on feedback instead of the traditional way based on   assumptions and tweaks . 

 Application 

 We decided to create small experiments . We had a Business Model Canvas from the previous business   model and we copied it 4 times in order to create 4 pivots we would like to test on the real market with   real customers . 

 Our principal criteria was the find product - market fit , which would allow the new business model to grow   and ideally become profitable . So , we select the 4 most voted ideas from our visual brainstorming session-   conducted with stakeholders and   early adopters from our business model . It was challenging since we   had to conduct this sessions remotely due to social isolation but we managed to get everybody   communicated using the tool Mural which also allows us to use visual tools to facilitate communication   among people . Once in Mural , we managed to rank the 4 most voted pivots : gastronomy social network ,   take - away and delivery solution , restaurant to consumer marketplace and recipes / cook - it - yourself app . 

 We got the usability results from our previous user research and used it to design 4 prototypes using the   Marvel tool in order to have a testable high - fidelity version of the 4 new pivots , presented as mobile   applications . Marvel also allows you to install those prototypes on the phones so we had to distributed   these new versions according to a split test . 

 We selected 100 users who liked or loved us ( had an NPS higher than 8) and also 100 users who hated us   ( NPS lower than 3 ) . We then created 4 random samples of 50 people ( 25 from each segment ) to test the   pivots . We called and emailed the people and got down to 40 people per sample since some of them   never answered . After that , we sent the prototypes via WhatsApp so they could download it directly on 

 their smartphones / iPhones . After the test , we conducted some interviews to get qualitative and   quantitative feedback from users . 

 Insights 

 The learning launch was successful . We managed to get information about the prototypes and learned   our customers did n’t care about the delivery and take - away pivot since they were still fearing the COVID   and believed restaurants could potentially lie about or make mistakes about security measures to prevent   COVID . Even though they idea sounded good , most of the people learned to cook and were improving at   their cooking skills as quarantine continued . This insight was radical to the point only 1 person ( which lived   in upper - class part of Lima city ) mentioned they would consider using this application . 

 This applied to restaurant - user marketplace since it also involved restaurants . It seemed like customers   were really doubting about restaurants implementing and executing security measures correctly . They   also wanted to have more control about the food they and their families ate . 

 On the other side , the prototypes about cook - it - yourself and the gastronomy social network were the one   with better appreciation . Insights about having recipes and cook - it - yourself content inside the social   network were flowing in more than 80 % of users ( 82.5 % ) . For cook - it - yourself prototype , people told they   wanted to have a social usage , to share and get recipes and information with their families and friends ,   who where locked away due to COVID . 67.5 % of the users provided this feedback . 

 Overall , this allowed us to unify both prototypes into a food social network we could them take to a next   iteration of the prototype and also allowed us to create surveys which we would pass to all our users in   order to understand which features they would prefer to have implemented first . 

 Approach 

 The usage of Learning Launch was successful since it has allowed us to launch a business model pivot   which we just launched and got 1000 active users in the first weekend . 

 However , what I would do differently is to couple Mind Mapping as an alternative to traditional   brainstorming since this would avoid getting bias and too much confirmation bias about own ideas and   instead focus the development of ideas around design criteria . It would also allow us to consider the   number of design criteria met as a way to rank ideas instead of conducting a simple voting , which can lead   to some powerful ideas because we resist them for their novelty .
### Output: 