Tool Selected : Learning Launch 

 Challenge : 

 The question to resolve was “ how to get fast the right information needed to conduct a task in the frame   our working space ” .   This was the initial questions that my team in Training and Knowledge Management   collected from the different users in recent surveys . Since many years , this question has been addressed   from different perspectives and applied different solutions that , in the end , they failed to fully satisfy our   users . There is too much information that in the end , is not productive as they spend too much time to   select the right information source . 

 Selection : 

 We apply in an intuitive way , the four steps of the design thinking process “ what is , what if , what wows ,   what works ” . We collected all the existing ways that we had to provide training/ information to users and   we analyze them in terms of the following criteria : 1 ) accessibility 2 ) speed to get the right information 3 )   accuracy and updated information . When collecting feedback from users , they confirmed that they would   like a centralized system , with visual , voice and preferable examples given and that they can share and   re - use if necessary . 

 As mentioned in the Training video “ Learning Launch Tool ” by Angel Glenn , we decided to experiment rather   than building “ theoretical Business Cases or ROI ” . We decided to apply an Intelligent Fast Failure   approach where we were going to test/ fail/ succeed ( Learning Launch ) . So we defined our hypothesis   and assumptions : 

    in terms of value creation , we considered that users would need to reach the knowledge/   information to conduct their task correctly and fulfill most of their requirements 

    in terms of execution , we wanted a quick and fast access to updated information and execution   ( eg no need to login/ passwords , etc ) 

    in terms of dependability , we wanted to be able to manage by our team and no dependency of   other departments 

    in terms of scalability , we wanted to reach in a short time ( 4 months ) 80 % of our population   ( around 400 users worldwide ) 

 We had different ideas but we retained two to test :    improve the “ lessons learned ” database that we   have with appropriate metadata to facilitate the research , to make it available in a centralized repository   and to update the information . The other idea we tested was to use micro - videos with a new tool that   allow us to tag the video with metadata that allows the research tool to look the inside the video in the   indexed data and that can be shared to other users with two clicks . 

 Application : 

 We tested both ideas for the “ what wow/ what works ” . We prepared communications and sent to the   users both tools explaining the changes and the benefits for them . 

 The Micro - Training video options very quickly showed that users preferred this option and data   confirmed our initial hypothesis/ expectations .   In one month , we passed from 40 connections to 200 

 connections and after 3 months we got more than 1000 connections that represented around 70 % of the   population that at least 1 time connected to consult the micro - training video . 

 The first option , even if it was the improvement of the standard way that they have to use the learning   repository , was quickly replaced by the Micro - Training Videos and after 2 months , practically , abandoned . 

 Insight : 

 This was amazing as it was also recognized by other departments that contacted us to get more   information about our Micro - Training Videos and considered to join to our library and/or to develop a   similar tool . Users ’ feedback was in majority ( > 95 % ) positive / very positive . The most value they found   is that combine voice recording , visual elements and the fact that the tool recognize the reach and brings   the appropriate answer to the search question . 

 In terms of tools , I can say that the fast launch to test was key to move forward , to accept that it can work   or it can fail and that we case that data would not confirm our expectations , we would need to change the   model if possible and eventually to abandon the test . 

 Regarding the first test , that we had to abandon it as the data showed that users did not adhere to the   tool , nevertheless , we did not feel “ bad ” or that we failed ( it was not us who failed , just the idea ) . 

 Approach : 

 Next time , we would not hesitate to test more ideas , and to include users not only as part of a “ voice of   customer ” approach but also to integrate them in the design and selection of the tool . The more we   worked with them , the more they felt involved and the more we improved the service and , in the end ,   the more number of connections we had . 


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: Tool Selected : Learning Launch 

 Challenge : 

 The question to resolve was “ how to get fast the right information needed to conduct a task in the frame   our working space ” .   This was the initial questions that my team in Training and Knowledge Management   collected from the different users in recent surveys . Since many years , this question has been addressed   from different perspectives and applied different solutions that , in the end , they failed to fully satisfy our   users . There is too much information that in the end , is not productive as they spend too much time to   select the right information source . 

 Selection : 

 We apply in an intuitive way , the four steps of the design thinking process “ what is , what if , what wows ,   what works ” . We collected all the existing ways that we had to provide training/ information to users and   we analyze them in terms of the following criteria : 1 ) accessibility 2 ) speed to get the right information 3 )   accuracy and updated information . When collecting feedback from users , they confirmed that they would   like a centralized system , with visual , voice and preferable examples given and that they can share and   re - use if necessary . 

 As mentioned in the Training video “ Learning Launch Tool ” by Angel Glenn , we decided to experiment rather   than building “ theoretical Business Cases or ROI ” . We decided to apply an Intelligent Fast Failure   approach where we were going to test/ fail/ succeed ( Learning Launch ) . So we defined our hypothesis   and assumptions : 

    in terms of value creation , we considered that users would need to reach the knowledge/   information to conduct their task correctly and fulfill most of their requirements 

    in terms of execution , we wanted a quick and fast access to updated information and execution   ( eg no need to login/ passwords , etc ) 

    in terms of dependability , we wanted to be able to manage by our team and no dependency of   other departments 

    in terms of scalability , we wanted to reach in a short time ( 4 months ) 80 % of our population   ( around 400 users worldwide ) 

 We had different ideas but we retained two to test :    improve the “ lessons learned ” database that we   have with appropriate metadata to facilitate the research , to make it available in a centralized repository   and to update the information . The other idea we tested was to use micro - videos with a new tool that   allow us to tag the video with metadata that allows the research tool to look the inside the video in the   indexed data and that can be shared to other users with two clicks . 

 Application : 

 We tested both ideas for the “ what wow/ what works ” . We prepared communications and sent to the   users both tools explaining the changes and the benefits for them . 

 The Micro - Training video options very quickly showed that users preferred this option and data   confirmed our initial hypothesis/ expectations .   In one month , we passed from 40 connections to 200 

 connections and after 3 months we got more than 1000 connections that represented around 70 % of the   population that at least 1 time connected to consult the micro - training video . 

 The first option , even if it was the improvement of the standard way that they have to use the learning   repository , was quickly replaced by the Micro - Training Videos and after 2 months , practically , abandoned . 

 Insight : 

 This was amazing as it was also recognized by other departments that contacted us to get more   information about our Micro - Training Videos and considered to join to our library and/or to develop a   similar tool . Users ’ feedback was in majority ( > 95 % ) positive / very positive . The most value they found   is that combine voice recording , visual elements and the fact that the tool recognize the reach and brings   the appropriate answer to the search question . 

 In terms of tools , I can say that the fast launch to test was key to move forward , to accept that it can work   or it can fail and that we case that data would not confirm our expectations , we would need to change the   model if possible and eventually to abandon the test . 

 Regarding the first test , that we had to abandon it as the data showed that users did not adhere to the   tool , nevertheless , we did not feel “ bad ” or that we failed ( it was not us who failed , just the idea ) . 

 Approach : 

 Next time , we would not hesitate to test more ideas , and to include users not only as part of a “ voice of   customer ” approach but also to integrate them in the design and selection of the tool . The more we   worked with them , the more they felt involved and the more we improved the service and , in the end ,   the more number of connections we had .
### Output: 