If there’s one tool we overlook more often than not due to overuse, it’s the simple, humble 2×2 matrix. This business strategy tool is badly overused, from publications and speeches to every case study you’ve ever had in business school. Every major consulting firm on the planet has thousands of these laying around. It’s trite. It’s cliche. And yet… the reason why it’s so overused is because it works so remarkably well at doing two things.
In business, we tend to have two core blind spots when we’re trying to solve a problem. The first blind spot is a tendency towards binary thinking. What’s the solution to this problem? What’s the answer to this question? Should I do more of X or more of Y? When’s the best time to post on Instagram? These are all questions that hint at binary thinking, when the answer may not be binary.
The simple 2×2 matrix helps to get you thinking differently by breaking you of the habit of assuming there is just one answer when there may be a spectrum of answers. There may not be a best time to post on Instagram, but a series of them. Your choice may not be X or Y, but a little bit of X and a little bit more of Y.
Here’s a simple, facetious example. Rather than asking yourself or your significant other where to have dinner (and the inevitable “I don’t know, what do you want?” debate), put your choices in a 2×2 matrix based on proximity and price. Now it’s not a binary question, but a question of spectrum:
The second blind spot is a tendency towards one-dimensional thinking. We focus, for example, on website visitors or Twitter followers or Facebook Likes. We focus on ROI or net revenue or daily downloads, and we look at a metric often to the exclusion of other related metrics that can help give additional context.
The simple 2×2 matrix expands your mind a little bit by asking you what related metrics you can examine. What else might impact that metric? Or, how would you categorize those two metrics together to draw meaningful conclusions?
Here’s an example using two related metrics from Google Analytics (or any web analytics). Instead of just wondering about the ratio of new vs. returning visitors, categorize them as low or high:
By laying out these two metrics and the relationships they have to each other, we can suddenly start to glean insights from the data that we have, and even hint at what potential solutions we might pursue to change one or more of the metrics.
Just because a tool is overused doesn’t mean it’s bad at what it does; its overuse may indicate that it should factor prominently in your own work. Keep the humble 2×2 matrix handy, and the next time you’re stuck looking at a problem from one dimension or in a binary way, bring it out and see if it expands your thinking.
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