High Road/Low Road - On the low road, run your numbers and dive deep into the analysis. On the high road, ask about the implications of the analysis and what new insights it provides
- Critical thinking doesn't just apply to the analysis you do, it applies to the way you do analysis, choosing which analyses to do, and how to handle the results that come out. I encourage people to take the high road, and the low road when they're thinking about analysis. On the high road, always step up to the high level problem that you're trying to solve, and ask how does the analysis I'm doing tie to that problem? What am I proving or disproving with the data that I'm analyzing? Estimate the benefit of even doing the analysis before you start pulling data.
Is it going to be beneficial? Will this analysis help me answer the ultimate question that I'm trying to solve? Use the 80/20 principle, and back up the envelope types of calculations to ask, will these numbers have any impact? If they will, continue with the analysis. If they won't, don't do the analysis. You don't have the time. And once you've completed the analysis, stay on that high road. Test your thinking. Ask, does this answer I got from my analysis tie to the recommendation that I'm trying to make? Does it support, or does it refute the recommendation I'm making? When you think about the low road, which is the deep analysis you're going to do, you should still be thoughtful about how you approach it.
First, only run the numbers you need to run. If you think about your scoped problem statement, and you're only going to focus on two business units, and that's what you've said is in scope for your solution, you should only be running analyses related to those two business units. If you find yourself pulling data for five or six different business units, you're wasting your time. Focus on the numbers you need to run. Also, don't stay in the data too long.
It's very easy to lose an entire day, or an entire week doing analysis. The numbers are clear, we can build graphs, and pivot tables, and charts, and we can build formulas, we can analyze data for extensive amounts of time, and when you do that, you may be wasting effort. Pull back up to the high road occasionally. Once you've finished some analysis, ask yourself, what have I learned from this? How does it apply to the recommendation I'm trying to make? I always tell people when they're doing deep analysis, "Don't polish dirt," and what I mean by that is, when you're in there doing rough analysis, and you're not sure what the answer's ultimately going to be, but you're trying to figure out is it hundreds, thousands, or millions? Once you figure out that it's thousands, you don't need to take it out several decimal points.
You know it's 5,000 to 7,000, move on with life. You shouldn't get that refined answer if that refinement isn't going to add value. Focus your attention on the answers that matter. That analytical time is precious. It chews up a lot of your time, and a lot of your team's time, so get back up to that high road regularly, and ask about the implications of your analysis. Critical thought isn't only related to the analysis itself, it's about thinking about the analysis, what analysis should you be doing, and not doing? These critical thought processes should help you question everything you do in terms of solving problems, from defining the problem, to generating recommendations, to doing your analysis, to figuring out if you've actually solved the problem, and if you're more mindful about the way you spend your time when you're doing analysis, you're going to be able to solve more problems more effectively, and more efficiently.
- Breaking big problems into small ones
- Defining the problem statement
- Asking focusing questions
- Finding root causes
- Using critical thinking tools
- Teaching others to think critically