Bulletproof Problem Solving

Chapter SixBig Guns of Analysis

In Chapter 5 we introduced a set of first‐cut heuristics and root cause thinking to make the initial analysis phase of problem solving simpler and faster. We showed that you can often get good‐enough analytic results quickly for many types of problems with little mathematics or model building. But what should you do when faced with a complex problem that really does require a robustly quantified solution? When is it time to call in the big guns—Bayesian statistics, regression analysis, Monte Carlo simulation, randomized controlled experiments, machine learning, game theory, or crowd‐sourced solutions? This is certainly an arsenal of analytic weaponry that many of us would find daunting to consider employing. Even though your team may not have the expertise to use these more complex problem solving tools, it is important for the workforce of today to have an understanding of how they can be applied to challenging problems. In some cases you may need to draw on outside experts, in other instances you can learn to master these techniques yourself.

The critical first step is to ask this question: Have you adequately framed the problem you face, and the hypothesis you want to test, so that it's clear you do need more firepower? If you decide your problem does fall into the genuinely complex range, you then need to consider other questions. Is there ...