Data Visualization, or DataViz is a hot topic! Recently, the Nonprofit Technology Network (NTEN) shared our recent series reviewing 6 DataViz tools we like, and its popularity made me realize how much of a hunger there is to make good sense what makes for effective data visualization. More than ever, brands are relying on data to tell their stories. Each has to create clarity around their data to better connect with their audiences. And each does so in different ways.
Over the years that we’ve spent helping a lot of different clients put data at the heart of their brands, and there are 3 key things we’ve learned that I believe are essential to doing so effectively. Here they are:
1. Focus on the Why, Then the How
Seems pretty simple, but when you see how many DataViz tools there are to choose from: Google Charts, Highcharts,InfoVis Toolkit, Mapbox and everything in-between—you quickly realize the potential for DataViz disasters that throw every bell and whistle at you. But the “how” of bringing DataViz to life is actually the easiest choice.
Like any design challenge, what’s important in data visualization is to focus first on the why: really understanding what’s meaningful to audiences in the data, how it’s meaningful to the brand, then focusing exclusively on just that. It’s formally known as eliminating the Chartjunk. By first boiling things down to what’s really essential, you’re in a much better position to start thinking about which tool will be the best fit to bring it to life.
2. Avoid Unnecessary Illustration
As Edward Tufte says, “Kill the Frills and Get to the Point.” But with today’s infographic overload, it’s gotten to the point where any illustration with icons and numbers is called an “infographic”—when more often than not it’s something really stupid. Others get so deep in the weeds, it’s hard to understand what they’re trying to say. What’s worse, pretty straightforward data design has become so overwrought with illustration, it gets in the way of understanding the data. Take the example below, touted in this article that I find to be mostly off the mark.
We should be able to understand the answer to this very simple question in seconds. Instead, I’m distracted by a poor attempt at meaningless decoration and beautification. Good data visualization should simplify things to speed understanding. Too often, decoration and beautification get in the way by emphasizing style over substance. Focus on the essential and strip away the fluff like these excellent examples do, the goal isn’t to get your inner Picasso on.
3. Make Data Design Part of Your Brand.
For financial services companies and policy & advocacy nonprofits in particular, clear data is essential to effectively communicating with the audience. And for these brands, it usually involves lots of analysts or research experts plugging away in Excel or proprietary software, crunching numbers and turning them into good old-fashioned charts and graphs. Too often however, companies drop their data into critical communications like pitchbooks and policy reports, settling for whatever look the system they’re using spits out.
But if you’re a brand that adds value with financial analysis and research, or by creating clarity around public policy, the data is one of the most important parts of your brand. It’s what convinces audiences of the merit of your insights. Relying on generic system generated data design to make your case is an unquestioned fail. Brand standards exist for a reason, and making data, even if it’s “boring” charts and graphs, a carefully executed part of the brand is essential to reflecting the expertise and value your brand stands for. Doing otherwise just undermines your credibility.
We’re awash in data these days. Design’s job is to make good sense of it. By focusing on what’s essential to your audience and your brand, not only will you more effectively make your case, you’ll also have greater impact.
Projects & Insights
Communications Science & Our Global Climate Change Discourse
Yale’s communication scientists are researching Americans’ attitudes on climate c
Yale Environmental Index
6 Amazing Data Vizualization Tools 2016 (Pt. 1)
When communicating with complex data, clear, compelling visualizations are more impor