Best Practices for Creating Infographics

Best Practices for Creating Infographics

Information graphics (infographics) are ubiquitous. With the incredible amount of data we're accumulating and needing to decipher, the propensity to turn quantitative information into compelling visuals has increased significantly. But for all the many beautiful and captivating infographics I run across, there are just as many that fail to elucidate the subject matter. The point of any type of data visualization is to allow for a universal, unquestionable and immediate understanding of the content. If you hope to accomplish this, the following should serve as a set of guidelines when creating infographics:

Find the story

The most first and most important step is to collect all the relevant raw data and read through it. You are trying to find a complete and credible story here. Very often there will be holes, questions you need answers to. You may need to do additional research. The data and information come first — the design is built around them so it's critical to have a complete understanding of the point trying to be made through presentation of the data.

Within the story one or more a-ha moments will emerge. These are the hooks, the heroes in the story and should be made the most prominent element(s) in the design.

Once you have the basic narrative, you’ll want to sketch out or wireframe the design and determine a format. While there are any number of creative ways you could present the data, some types of infographic approaches are better fits for your data than others.

Simplify but don’t oversimplify

Information graphics are used to present complex concepts or statistics that might otherwise be incomprehensible. While it is always best to err on the side of a clean and limit the use of decorative elements, you don’t want to be so Spartan in your design that meaning is lost or there are holes in the information.

Don’t let wit overrule comprehension

Yes, there are some incredibly clever infographics that amplify the understanding of the concept in delightful ways. But there are nearly as many examples of graphics that are trying so hard to be fancypants or masquerade as legitimate quantitative research that all they do is confound the reader. Over the top use of visuals or overwrought design will become a liability to your message. If you can’t get the story across within a few seconds, you’re probably better off sticking with text.

Arrows

Arrows in infographics should really only be used to signify direction, flow or a dependency. If you’re going to use them, they should also be labeled.

Color

Minimize the number of colors being used; overuse of color can be confusing, distracting and weary on the eye. Be purposeful and consistent with how you’re using color. Consider if color will be used to categorize information in some way. If so, then it might be wise to keep supporting elements in a neutral palette.

Cultural context

Consider the cultural meaning of colors and shapes and take advantage of that. There’s no sense in jeopardizing comprehension or wasting people’s time trying to learn new representations for commonly associated colors or symbols. For example, in a U.S. political infographic you would not want to use blue or a donkey shape to represent Republicans and red or an elephant shape for Democrats. You don't want to create a new visual vocabulary for one that's already well-known.

Sources

Whenever possible, the data in information graphics should be sourced. This should be relatively easy to do if the research has been documented properly.

Use your words

Not every single bit of information in an infographic needs to or even should be pictorialized. Include a legend to explain what the shapes or colors represent. Label axis and arrows. And please don’t forget the title and a caption.

As with all rules, sometimes they’re meant to be broken when there’s a good reason. So you will certainly see successful infographics that do not follow this protocol. Perhaps the most solid source of what works and what doesn’t and why for data visualization is statistician Edward Tufte. We encourage you to become familiar with his work. Other good resources are: Picktochart, Visual Complexity and Cool Infographics.