The red and green rule

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Early in my career, I produced many data visualizations for a senior executive. Let’s call him Gordon. Gordon is unabashedly a man of strong convictions. One of his most strongly and repeatedly voiced was that, in any data visualization, the color green had to represent good and the color red had to represent bad. And there always had to be good and bad. No exceptions.

I quickly caught on, and for the work I did for him I began abiding by his iron red and green rule. Nevertheless, he reminded me of it several times, asking whether red meant good and green meant bad in the visualizations I produced, despite my answers being uniformly in the affirmative.

At first, I attributed his frequent questions to a lack of trust; in fact, it was one of the only factors contributing to my (slight) perception of a lack of trust in our relationship.

Then, one day, I was sitting in Gordon’s office, while a dashboard brimming with my red and green charts filled his computer screen. He was one of the primary users of this particular dashboard, and was quite familiar with its content. He asked me a question that, for the first time, took me by surprise: “are these charts red and green?”

That’s the moment I realized that the frequent questions were not about trust. Gordon is colorblind.

Why would someone with red-green colorblindness want reports of which he is a primary user in red and green?

It turns out that Gordon picked up this conviction while working for a (colorseeing) CEO who insisted on red and green in his charts. Once acquired, it became a hard and fast rule, part of Gordon’s data visualization grammar.

We all have strong convictions. In the world of data visualization, convictions are often influenced by poor conventions set over decades, such as by lay users of Microsoft Office. The proliferation of 3D pie charts is more about convictions and conventions than about good data visualization.

The next time you’re creating a data visualization, apply your own critical thinking rather than relying on conventions. Consider the best way to surface and communicate the information. Critical thinking, not following conventions, is the path to creating the best data visualizations.


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