Mindset required to solve muddy problems
Last month, we introduced you to the concept of muddy-fuzzy-clear problem life-cycle. Depending on the life stage of the problem, we argued that analytics practitioners and businesses need to have different mindsets to address these problems. In this post we will focus on the mindset required for addressing muddy problems.
Muddy problems are, well, muddy. The problem in itself requires defining and re-defining several times. In this regard, a muddy problem requires slow cooking. Solving muddy problems also requires an analytics practitioner to follow a discovery-driven approach instead of a hypothesis driven approach.
Muddy problems require multiple iterations. Your efforts might (actually, will) not yield immediate solutions. Failures and stumbling along the way are almost inevitable during the course of addressing a muddy problem. If you have to fail, you might as well fail fast; it will help in minimizing the total effort. Therefore, an analytics practitioner addressing a muddy problem will be required to focus on quick iterations (agile exploration) and learning from these failures.
Muddy problems require relatively more right brained thinking. Creativity is an important aspect required for solving a muddy problem. Don’t rule out the possibility of finding a solution in completely unrelated places/situations. The solution to an online yield management problem might come from the airline industry. So, keep your eyes wide open and mind more open.
Above all, the lack of progress in solving a muddy problem might be very frustrating. Patience is the need of the hour. A long term view is required while measuring the ROI from addressing a muddy problem.
In a future post, we will talk about the mindsets required for fuzzy and clear problems. Meanwhile, drop us a note with the muddy problems in your business and how you are approaching them.