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.

