I am a data nerd. I grew up, professionally speaking, designing studies, collecting data, and trying to get people to make use of the analysis and results. Then one day I realized that no one was going to pay attention to my amazing, glorious, wonderful data if my reports and presentations were poorly designed. So I married a graphic designer, and together we snarked at bad restaurant signage and had heated discussions about nuances in shades of purple. I became a design nerd, too.

When data and design successfully bridge, we can change the world.

Data nerds need designers

These days, I teach data nerds how to become better designers and designers how to become better data nerds. I design great graphs. And I study how data are presented. Here are the patterns that I see over and over again:

  • At worst, I see data nerds who have never worked with a designer, and the resulting heap of data is so off-putting that only the most committed will ever read through it to pull out meaningful insights.
  • In a better situation, I see beautifully designed reports with gorgeous, flowing page layouts and eye-catching color schemes — with all of the graphs tucked in an appendix, clearly just plunked into the page template and not even touched by the designer.
  • At best, I see graphs embedded appropriately in a report, story, or webpage, with the right look and feel that matches the rest of the design, but cast in the wrong graph type, like a pie chart with dozens of slices.

Are you cringing with recognition? If you’re a data nerd, you’ve probably witnessed at least one of these scenarios.

Data nerds need designers. Design is how we create engagement and spark action. But designers typically avoid a deeper understanding of data and how to best present it. Why?

The data/design landscape

My colleague, Elissa Schloesser, a graphic designer at My Visual Voice, suggested that traditional chart software, like Microsoft Excel, can feel intimidating (yo, it can feel intimidating to data nerds, too). But it’s not just Microsoft — the graphing tools in Adobe Illustrator and InDesign are mediocre at best, only capable of the simplest of chart types. Anything outside their small set of chart choices requires creating the graph in another software program and importing the image or — and I can think of nothing more tedious — drawing the graph manually with individual lines, text boxes, and circles.

No one teaches designers how to visualize data.

Design programs weren’t set up for easy, quality graphing, likely because designers traditionally aren’t data nerds. Users haven’t demanded great graphing capabilities, so software companies haven’t built that capacity, and the cycle just feeds itself over and over.

In addition to unsupportive software, my design clients often tell me that they see themselves as “art people” not “numbers people.” Schloesser, like many graphic designers, is somewhat self-taught. She didn’t go to school specifically for design. But even those who are more classically trained also shy away from a mastery of data visualization best practices, probably because it isn’t included in a designer’s academic coursework. No one teaches designers how to visualize data.

Another design colleague, Peter Brakeman of Brakeman Design, said that sometimes the trouble is compounded by the initial design request. Clients will ask designers to “make this look pretty” and design something that illustrates the larger storyline. So, Brakeman said, “a bar graph showing the amount of corn shipped to China for each of the last five years has ears of corn stacked up to the desired total for each year.” And that design would satisfy the client’s request of making something that looks pretty, even if it is the wrong graph type and doesn’t communicate the data effectively. It is not that a corn graph is technically bad design, it just has the potential to be so much more.

The business need

For these reasons and surely many others, designers have traditionally felt that data nerdiness is not in their wheelhouse. However, today’s organizations are data-driven. I’m not even talking about companies like Facebook that are collecting big data. I’m talking about the smallest nonprofit in your neighborhood, who is doing its best to use data to improve programs and services and make a bigger impact on the world. Everyone is looking to be more strategic by using data to inform business decisions.

This is an area designers can no longer afford to ignore. Data visualization is the next design challenge.

We have data on customer buying behavior, on customer interactions with our websites, on employee performance, on our competitors — we have so much data that people are up to their eyeballs in spreadsheets and need to figure out how to cut through all of that noise and actually use of all that data to drive critical business conversations. Communicating data effectively is now a core business skill.

The hitch is that communicating data effectively requires creating data visualizations that are well-designed, clear, and efficient, so people can make swift use of them in the workplace. But data nerds are not designers. So this is an area designers can no longer afford to ignore. Data visualization is the next design challenge.

The user need

Our audiences will benefit or suffer based on our ability to communicate data clearly. Remember the General Motors ignition key crisis? A problem with the ignition switch would cause the car to turn off even when someone was actively driving it, and it caused several deaths. The issue had been brought to the attention of the decision makers at GM, but the slides that were used were cluttered with 3D bar charts and failed to convey a clear point. Combined with a culture that lacked a sense of accountability, this failure to communicate the data lead to murky understanding, insufficient action, and ultimately the loss of people’s lives. Bad data presentation is expensive on so many levels.

A client of mine, a Fortune 500 senior vice president, contacted me a few months after participating in one of my data visualization workshops. He was a little upset — in the redesigned graphs we made, he could now see that performance at his company was going down, something that should have been caught and corrected a year earlier. But he also commented on the fact that once employees learned how to present their work clearly, they were seeing a shift in the company culture. People were being braver and more honest about showing their data, and that bravery was resulting in better teamwork, promotions, and business decisions that were efficient and effective.

How to be a data nerd

When the world’s largest independent design company hired a data visualization specialist, Fast Company described the partnership by saying “data visualization is the new branding.” Data visualization may not have historically been a part of the graphic designer’s skill set, but the future is asking for designers to create some room.

Data nerds need designers who can understand the data being presented and know the best chart types to convey the nerd’s point. Nerds need designers who can take what they already know about spot colors and condensed fonts and apply those concepts to graphs so the story shines through.

Learning how to construct clear graphs is not as hard as it might seem. When I show people graph makeovers, they are usually stunned. It can seem like it would take a team of designers and programmers several months to create data visualizations of that caliber. So even if they are convinced that good data visualization is important, they start thinking about how expensive the production will be.

But I’ll let you in on a secret: Most of the hard work is simply stripping out the bad design baked into our default graphs and using familiar design principles like unity and proximity to present the information in a clear way — much like designing a clear and user-friendly interface, for instance. As a designer, you’ll feel at home once you clear the initial intimidating hurdle of just getting started.

I can hear you: “Ok great, Stephanie, but how do I get started?” The beauty of the boom in data visualization’s popularity is that resources are everywhere. My latest book, Effective Data Visualization, helps you choose the right graph type and create it in Excel. You’ll also find loads of data design strategies on my blog and in future articles here on Modus. Really, there are so many blogs about data visualization you could make scouring them a full-time job. You could also take one of the many courses offered by Coursera and other online learning platforms.

I am not necessarily advocating for designers to create the type of data-driven visualizations that look so complex and intricate that they could be trendy art for your living room wall (though there is a place for that in the world). And you don’t necessarily need to learn a programming language in order to make great graphs. We are aiming for a sweet spot, where data are readily understood and where designers and data nerds partner to create compelling visualizations inside broader stories that engage, inform, and inspire.