When I was a young kid my uncle had a stroke.
A middle aged man with a wife and three daughters, it changed his life completely. Not so long after his stroke my uncle came to live with us, becoming part of our family unit for the final 30ish years of his life.
Uncle Jack had a hard time communicating. He would need things repeated sometimes, and occasionally he would become frustrated when the words wouldn’t come to his mouth. For most people, who didn’t know my uncle like I did, they would default to speaking slower and louder. As if he couldn’t understand or follow the most basic conversation.
But looking into his eyes you could see his mind working. A fact that would present itself in an often unexpected quick whit and intelligence that belied his general appearances.
It’s not about simple.
When someone doesn’t understand what we are saying, why is it our default to speak louder and slower?
Now that I’m closing in on a decade in the field of data visualization I find that our pursuit and embrace of simple is often based on that same instinct. Louder and slower.
I hear it every time I get a request for a visual that can be fully understood in a matter of seconds. Visualizations that strip away detail and context in favor of direct simplicity. Big numbers, basic descriptive stats, and simplistic charts. Even when the dataset offers so much more potential.
We are so focused on conveying our point that we so often devalue our audience’s intellect. We treat them like they don’t have the capacity to understand something just a little deeper.
Most audiences don’t have a simple problem.
They have an interesting problem.
Simple data may be easier to digest, but it’s also easier to gloss over and forget. And even when it is interesting, the context that allows for deeper examination gets left out completely.
The “interesting problem” is that your data visuals need to be important, entertaining, catchy, or mysterious for anyone to care enough to explore and remember. They need to be interesting. And interesting is almost always a bit more complicated than it looks at first glance.
Simple is not the solution to the interesting problem. If an audience is interested they’ll push themselves through incredibly complicated tables and charts to find answers. If not, they don’t care, and they’ll move on.
More Data Less Confusing.
This should be the rallying cry of the data visualization specialist.
Just about anyone can reduce data to reduce confusion. And yes, it does take expertise to know what to focus on and what to leave out. The little data that’s required.
But the power in data visualization is in making more data feel like less.
And if you do it effectively, you can provide context in a way that simplifying could never do. You can pull a deeper and wider understanding out of the natural black box created through advanced statistics and data science. You can help an organization drowning in potentially valuable data and information.
You can offer more data AND make it less confusing.