Mind Mapping in Analytics 

 Challenge & Selection   I am a part of an Enterprise Data Analytics team . My team was engaged to bring in data driven   surveillance in processing to prevent potential fraud . Since there was no precedence of data driven   surveillance in this processing area and our team was not aware of the entire processing lifecycle , we   had to apply a design thinking process to approach this problem . At the initial stages , series of discovery   workshops were conducted with different stakeholders to assess the current state , akin to the " What   Is ? " in this course . The workshops gave us lot of inputs from the stakeholders on current process and   potential gaps and risks across several dimensions which brought about the challenge of designing the   framework of the solution that should be explored . It was a pivotal point for us as the effective synthesis   of all the workshop findings was a key before we could move to the " What If " stage . The design thinking   tool we chose to use was " Mind Mapping " as elaborated by Angela Sanchez in Week 3 of this course .      Application   Step 1 > The first step in the mind mapping tool exercise was to lay down all the findings from the   workshops on a big board . The sticky notes used in the workshops were put on a board for everyone to   see .    Step 2 > During the mind mapping exercise with stakeholders we were able to semi cluster the gaps   ( from the discovery workshops ) on a two - dimensional view - On the top we had the processing lifecycle   stages and on the left we came up with some high - level risk typologies like below – 

 Initiation   Pre - Processing   Processing   Reconciliation   Post Recon 

 Risk Typology 1 

 Risk Typology 2 

 Risk Typology 3 

 All relevant stakeholders played a part to co - create this initial clustering and thereafter further dwell on   how the different gaps are connected to each other .      Step 3 > The stakeholders then helped to combine smaller clusters into broader categories like - Gaps   that can be addressed by Access Control Changes , Gaps that can be addressed by System   enhancements , gaps that can be included in data driven surveillance . This helped the team get the right   focus .     Step 4 > We had to conduct a subsequent mind mapping exercise after a week to come up with a broad   framework since the gaps that can be included for data driven surveillance were also many spanning   across various typologies , involving different processing team and having different considerations from a   data sourcing aspect . This time we invited a smaller focused group of stakeholders . The second   workshop went deep into the focused area and enabled us to come up with design framework to start   the exploratory analysis for data driven surveillance . 

 Insights   The Mind mapping tool used as described above was extremely useful . The evolution of the two- dimensional view to synthesize the workshop findings gave everyone a perfect lens to visualize the   problem . Without that a big bunch of sticky notes made the team think where should we start ? The   clustering into smaller categories was very instrumental in getting the focus right . The output of the   second workshop was the draft framework design that the data analytics team can consider to start the   exploration . Although this was not the final solution , it gave the team the first frame to start   somewhere . This application demystified the myth that many data analytics professionals have that   design thinking does not apply in analytics . Now I am convinced that Design Thinking as a problem-   solving framework is very applicable in analytics .     Approach   With respect to the application of mind mapping tool , I will continue to use it during the latter part of   the discovery or “ what is ” stage . However , at the next application I would like to put some more effort   into the pre - work ( preparation before the mind mapping exercise ) to steer the stakeholders to get more   fruitful contribution . 


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: Mind Mapping in Analytics 

 Challenge & Selection   I am a part of an Enterprise Data Analytics team . My team was engaged to bring in data driven   surveillance in processing to prevent potential fraud . Since there was no precedence of data driven   surveillance in this processing area and our team was not aware of the entire processing lifecycle , we   had to apply a design thinking process to approach this problem . At the initial stages , series of discovery   workshops were conducted with different stakeholders to assess the current state , akin to the " What   Is ? " in this course . The workshops gave us lot of inputs from the stakeholders on current process and   potential gaps and risks across several dimensions which brought about the challenge of designing the   framework of the solution that should be explored . It was a pivotal point for us as the effective synthesis   of all the workshop findings was a key before we could move to the " What If " stage . The design thinking   tool we chose to use was " Mind Mapping " as elaborated by Angela Sanchez in Week 3 of this course .      Application   Step 1 > The first step in the mind mapping tool exercise was to lay down all the findings from the   workshops on a big board . The sticky notes used in the workshops were put on a board for everyone to   see .    Step 2 > During the mind mapping exercise with stakeholders we were able to semi cluster the gaps   ( from the discovery workshops ) on a two - dimensional view - On the top we had the processing lifecycle   stages and on the left we came up with some high - level risk typologies like below – 

 Initiation   Pre - Processing   Processing   Reconciliation   Post Recon 

 Risk Typology 1 

 Risk Typology 2 

 Risk Typology 3 

 All relevant stakeholders played a part to co - create this initial clustering and thereafter further dwell on   how the different gaps are connected to each other .      Step 3 > The stakeholders then helped to combine smaller clusters into broader categories like - Gaps   that can be addressed by Access Control Changes , Gaps that can be addressed by System   enhancements , gaps that can be included in data driven surveillance . This helped the team get the right   focus .     Step 4 > We had to conduct a subsequent mind mapping exercise after a week to come up with a broad   framework since the gaps that can be included for data driven surveillance were also many spanning   across various typologies , involving different processing team and having different considerations from a   data sourcing aspect . This time we invited a smaller focused group of stakeholders . The second   workshop went deep into the focused area and enabled us to come up with design framework to start   the exploratory analysis for data driven surveillance . 

 Insights   The Mind mapping tool used as described above was extremely useful . The evolution of the two- dimensional view to synthesize the workshop findings gave everyone a perfect lens to visualize the   problem . Without that a big bunch of sticky notes made the team think where should we start ? The   clustering into smaller categories was very instrumental in getting the focus right . The output of the   second workshop was the draft framework design that the data analytics team can consider to start the   exploration . Although this was not the final solution , it gave the team the first frame to start   somewhere . This application demystified the myth that many data analytics professionals have that   design thinking does not apply in analytics . Now I am convinced that Design Thinking as a problem-   solving framework is very applicable in analytics .     Approach   With respect to the application of mind mapping tool , I will continue to use it during the latter part of   the discovery or “ what is ” stage . However , at the next application I would like to put some more effort   into the pre - work ( preparation before the mind mapping exercise ) to steer the stakeholders to get more   fruitful contribution .
### Output: 