GUEST BLOGGER
Erik Halvorson
Special Agent, U.S. Department of Energy

If we ever work together on an investigation or an analytics project, you will probably hear me say two things: 1) we are paid to be creative problem solvers, not mindless number crunchers and 2) I love analytics because it is so new in our field that we are really only limited by our creativity and the data we can gather. In the words of my childhood TV hero, Colonel John “Hannibal” Smith, “I love it when a plan comes together.” As a kid watching shows like “The A-Team,” I learned that, of course, plans always come together. As an adult and especially as a young investigator, I learned that this is in fact not always the case.

When we learn a new skill, there is typically a lag between what we learn contextually (i.e. from school) and how we can apply that knowledge to a real-world situation. Data analytics is no different. For me, there is no clearer example of this than the use of analytics in an investigation, especially in a proactive fraud analysis. In that spirit, I want to dig in to the process of idea mapping. Hopefully this will help your plan come together, or identify weaknesses in the plan early so they can be caught and fixed.

Idea mapping is nothing new and certainly nothing I created. The idea originally came from a technique known as mind mapping, which was developed in the 1960s. Some 30 years later, in the early 2000s, mind mapping was updated to idea mapping as an easier and more intuitive process version. This process allows ideas to flow naturally (and nonlinearly) while still allowing us to organize them in a reasonable way. Idea mapping has at least two primary benefits: it is an awesome way to capture ideas and it is an excellent tool to generate ideas.

At its most basic level, idea mapping uses three simple, fundamental skills. These are:

Identifying key words and themes
Creating main branches and links
Using simple icons

These skills allow us to create a graphical, nonlinear, organized idea representation without confining ourselves to rigidity or chronological thinking. The way this looks is our central idea or theme in the middle of the page with branches (or links) connecting sub-ideas to the main theme. Then we can add further sub-branches as we move out. The labels can be single words or short phrases, and can use iconography to help us better understand our own meaning. Sounds simple enough, but how does this work for an analytics-driven fraud analysis?

When I’m idea mapping for a project, I typically place my program — or what I am reviewing — in the middle. From there I branch out with specific requirements or certifications to schemes or types of fraud. Then I further branch out from the schemes with red flags to specific data sets or points. The data are anchors I can use to evaluate those red flags.

Figure 1 above illustrates the general concept of how to map your analysis. In this graphic, notice that “Fraud Scheme 2” and “Fraud Scheme 5” have red flags, but no corresponding data sources. Sometimes this happens. A data source can be found later or it might not have one that is conducive to an analytical review. When this happens, try not to spend too much time forcing an analytics approach to the evaluation. Remember the use of analytics in fraud investigations should be a force multiplier and done at scale as much as possible. As you experiment with this process, try out different mediums. I usually use a whiteboard, sticky notes or just scrap piece of paper initially.

Now, let’s look at a more specific example. Pretend I am conducting an analysis of the Small Business Innovation and Research (SBIR) program. This is a federal program to help develop small business research and development. The first step is to review the program requirements. In this case, I know a specific requirement is that the awardee must be a small business. This requirement would be linked to a node listing the scheme of, “large business or university.” This scheme would be linked by the red flag of “located at large business or university” to a node labeled “Google Map/address check.”

Figure 2 is an example of idea mapping a review of the SBIR program, as mentioned above. Filling in the gaps will help illustrate the idea more clearly. In the purest form of idea mapping, there should be less words and icons that mean something specifically to me, the mapper, but get creative, play around and do what makes the most sense to you.

Ultimately, the point of this process is to organize your thoughts and investigative or analytical plan before you start. This allows you to efficiently brainstorm about both schemes and data sources needed to conduct your investigation or review. For me this was an epiphany and allowed me to transition from my young beliefs that plans just “come together” to the understanding that, as former U.S. National Security Advisor Colin Powell once said, “There are no secrets to success. It is the result of preparation, hard work, and learning from failure.”

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