At various points in the problem-solving approach you’ll need to be as collectively exhaustive as possible. That means that you must consider big things and small things. But it doesn’t mean that you need to treat them all the same or that you need to treat them in a random sequences. Instead, use the Pareto principle: start and/or focus on the 20% of your causes that amount to the 80% of consequences.

**First, define the 100%…**

We’ve talked about it in a previous post: to look for all the possible root causes for your problem or, indeed, all of its possible solutions, you need to be an optimizer rather than a satisficer; in two words, you need to be collectively exhaustive.

That means that you’ll push yourself out of your comfort zone, looking for new elements that answer your key question. However you can get stuck in your quest for collective exhaustiveness and you’ll never reach conclusions, which is a problem, because analyzing doesn’t solve problems, implementing is what solves problems.

So whether you go by a time limit, a maximum number of factors to consider or any other measure that you see as the optimal one, you need to decide when to stop thinking in a divergence manner so that you can focus your efforts.

**… then decide where to focus**

The Pareto principle—also called the 80/20 rule—states that 80% of the consequences originate from only 20% of causes. Concentrate on these causes and you’ll have the biggest return on investment by avoiding to “boil the ocean”.

Of course, the difficulty is usually to recognize which causes have the larges impact. Here is one way to do it.

Enlist others to decide where to focus. A couple of years ago, at the University of Monterrey, we decided to understand why the quality of our graduate programs wasn’t higher. So we built a why logic tree, identifying all possible factors and then organizing them in a MECE and perspicacious way.

Here is the tree (sorry, it’s in Spanish). With over 70 possible answers to our question, clearly there was value in focusing on the few items that had the largest impact.

So, next we had to identify which ones had the largest impact.

Applying our standard approach, I summarized the possible 70+ possible root causes for our problem in a table, gave the table to each of the six graduate program directors and asked them to evaluate, in percentage points, the impact that each factor had on limiting the overall quality of our programs. They had to do this evaluation on their own, so as to limit the bias they could get from their colleagues. In the end we averaged the scores.

We found that just six factors explained over 80% of our problem. In fact, we thought that a single one explained 38%! Clearly, starting our analysis with these most important factors would help us benefit quickly and profoundly from our problem-solving process.

Of course we could have done this better. For instance, instead of having just program directors ranking the impact of factors, maybe we should have sought the input of professors and students as well. But that would have been longer, so we went for the solution process whose timeline was most compatible with our situation.

The point is that by identifying which factors have the largest influence, you can concentrate your resources where they have the most value; and that is rather powerful.