Decision Making as part of the problem solving process

Decision making is a critical part of the problem-solving process. But it is also only that: a part. The process has several others, and you shouldn’t overlook some at the expense of others.

First, understand your problem and solution spaces

Picture a person coming to a physician’s practice, complaining of a headache. Before the physician prescribes an aspirin or a round of chemotherapy, she should understand the root causes of the problem: is the headache the result of a bad hangover or a brain tumor (or something else)? In other words, before making decisions, you need to understand your problem and your solution spaces.

Decision Making

While a critical activity, decision making should come rather late in the problem-solving process

Let’s focus on complex, ill-defined, non-immediate (CIDNI) problems. That is, problems that have opaque and/or interdependent components (complex); that don’t have clear characteristics (ill-defined); and that you have at least a few days to solve (non-immediate). Providing clean drinking water to remote locations in Africa is an example of a CIDNI problem. So is curbing the US diabetes epidemic, reversing global warming, or any of the 21st century grand challenges. But so is also deciding your next career move, buying a house, or getting married.

A complete problem-solving process starts with framing the problem: recognizing that one exists, understanding what it is—and what it isn’t—and setting up parameters for its solutions.

Then comes the diagnostic phase. Just as our physician must understand the root causes of his patient’s headache, you need to understand why you are having the problem, or why you haven’t solved it yet. You might want to use a diagnostic issue tree to help you do so.

The third step is to identify the universe of potential solutions, the so-called solution space, which also benefits from building an issue tree (this time, a solution one). It is only at the end of that step that you should decide which one(s) among those you should implement. A weighted decision matrix is one of several great ways to help you understand better the implications of each of those and decide which to select.

Once you’ve made your choice, you’ll conclude the process with implementing the solution(s) that you’ve chosen, and periodically review the effectiveness of your course of action to make corrections if necessary.

So, step back and look at the big picture

I once had a mathematics professor who would describe problems in the upcoming exam by saying, “the solution is trivial, the difficulty is to see that it’s trivial”. While I hated hearing this as a student, I must confess he had a point: when confronting CIDNI problems, if you can focus on the right problem, diagnose it correctly, identify a proper set of potential solutions, understand the implications of each of those, and understand how these implications matter to you, then choosing the right solution is trivial. Or, at least, simpler.

A weighted decision matrix is great because they help you with the last two conditions: understand the implications of each of potential solution, and understand how these implications matter to you. But this is not sufficient. It’s like building a great house on poor foundations: sooner or later, you’ll face consequences. So you need to pay attention to both: the great decision making and all the previous work preparing it.

Arnaud Chevallier works at Rice University, where he lectures in the school of engineering. He researches how to solve complex problems and writes about it at

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