let's improve this graph!

As we share what we’ve learned—and continue to learn—on how to bring data to life, we recently added a new makeover page, which illustrates concrete tips with real-world examples. On the topic of makeovers, today’s post kicks off a week-long series of five questions to ask yourself when designing a graph for explanatory purposes. Each day will be dedicated to one question. Devoting time holistically to these components will improve your value as a data communicator. 

Before we get to the five questions, let me pose one to you. Have you ever created a graph only to be met with requests for more data? As an example, spend a moment considering the following visual:

I empathize with the plight of this anonymous creator. In previous roles, I frequently created visuals that looked like this, and was left frustrated when requests came back for “more data.” I slowly came to realize that I was assigning my audience the tedious task of figuring out for themselves what the takeaways were. My visuals should have been highlighting the interesting things to those seeing them for the first time. The five questions we’ll be discussing in this series will help us to do just that.

QUESTION 1: What elements can I eliminate?

Our dataviz tools are a frequent source of unnecessary visual clutter. These seemingly minor things—borders, gridlines, excessive data labels, legend, and title positioning can make our visuals appear more complicated than they really are. Take another look at the original chart at the onset of this post—what clutter would you remove?

I’m inclined to eliminate the superfluous borders, gridlines, and numeric labels. I can also move the legend directly next to the data, reducing the mental effort of going back and forth between the category labels and the graph. Finally, I’d advocate left-aligning the chart title so that it’s not hanging out awkwardly in the middle. Making these changes leaves a more approachable, cleaner, and organized visual:

In the spirit of removing elements which don't add value, you may be wondering whether I need the black total line; we’ll discuss this and additional changes soon.

These steps took me less than five minutes in Excel, although it once took longer and became more second nature with repetition. Notice how a few simple changes go a long way towards making the graph feeling less complicated—consider how you might apply the tactics illustrated here in your own work. For additional practice, try the SWD community exercise strip away the non-essential. 

If you’re like me, I still want to make further improvements. We pick up here in the next post with question #2. Hint: it’s arguably the most important decision you make as an information designer!