Don't Be Left Behind! A Step-by-Step Guide to Data Visualization
Visualizing data in charts, graphs, dashboards and infographics is one of the most powerful strategies for getting your organization’s numbers out of spreadsheets and into real-world conversations. I’ll walk you through the data visualization design process, so you know what to do first, second and third, as you transform your spreadsheets into stories.
Step 1: Analyze Your Audience
I begin every data project with planning conversations. It’s tempting to dive straight into spreadsheets and create some quick graphs, but pausing to talk aloud with your coworkers now about the contextual factors surrounding your project will save a lot of time later.
The most important planning consideration is whether your audience is hoping for a traditional graph or a storytelling graph.
Here are two versions of a fictional graph (below). The image on the left is a traditional graph, which has a topical title and a one-color visualization. The image on the right is a storytelling graph, which has a takeaway title and intentional dark/light contrast to guide viewers’ eyes directly to your takeaway finding of choice.
It’s not that one approach is better or worse than the other. They’re apples and oranges. It’s your job to discuss the pros and cons of each approach with your coworkers ahead of time, and then decide which path you’ll take.
Step 2: Choose the Right Chart
After I think carefully about the audience type(s) that I’m designing visualizations for, I think about what type of chart I’ll use to showcase my takeaway findings.
If you’re doing any state-by-state comparisons, you might even add state shapes to create straightforward visuals like this one (below). There’s research showing that easily-recognizable icons and symbols — like the state shapes and the arrows below — can make our visualizations more memorable, so I use icons whenever possible.
Step 3: Select a Software Program
After I decide which chart type I’ll need to showcase my desired takeaway finding, then I create that graph on the computer. There are plenty of good software programs to choose from.
This Chartmaker Directory (below) is my favorite crosswalk for narrowing down which chart type is possible in which software program. The website’s creator, data journalist Andy Kirk, has listed dozens of chart types down the left side. He also listed dozens of free and low-cost software options along the top of the screen. The circles are links to examples and tutorials, where fellow data visualization designers have shared how-to tips that you can follow.
Step 4: Declutter
After I’ve created my graph on the computer, I roll up my sleeves and make intentional edits.
Decluttering is addition through subtraction — you subtract the unnecessary ink so that the remaining ink is more salient. When it comes to data communication, sometimes less is more.
You need to scrutinize the software program’s default settings and delete a lot of the built-in chart junk. Software programs often come with way too many borders, lines and unnecessary ink.
Here’s a decluttering example (below) so you can see the power of decluttering.
Step 5: Clarify Your Message With Color
After I declutter my visualization, I edit the visualization’s colors.
I recommend using your own agency’s color scheme rather than just choosing colors you like. Using your own agency’s colors will ensure that all staff members’ graphs look streamlined (and therefore professional). Using your own agency’s color scheme also saves major time, because you can share your slides, handouts, dashboards and infographics with each other and have everything instantly match.
Following your agency’s color scheme is easy:
- First, locate your existing style guide. If you don’t have a style guide, or you can’t find it, then you can open your agency’s website and use the eyedropper tool or even Microsoft Paint to figure out your color codes.
- Second, you enter your color codes into your software program. Here are tutorials for entering custom color codes into Microsoft Excel and into Tableau.
Step 6: Clarify Your Message With Text
Finally, after I’ve decluttered the visual and added my agency’s branding colors, I edit the text in my graph.
For traditional graphs, I write topical titles. For storytelling graphs, I write takeaway titles.
I also edit my visualization’s text to ensure that it’s as accessible as possible. For example, I measure the reading grade level of my graph’s titles and see where I can swap out technical terms for everyday language.
Data visualization isn’t supposed to be hard. A series of small, intentional edits can completely transform your visualizations. I hope this article has given you practical tips that you can apply to your projects right away. If you’d like to continue learning, you can check out my mini course or connect with me directly.
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Ann K. Emery is a sought-after speaker who equips organizations around the globe to use their data more effectively. Within the past year, she led more than 60 trainings for more than 2,800 participants.
Her design consultancy also overhauls graphs, publications and slideshows with the goal of making technical information even easier to understand for non-technical audiences. Recent clients include the United Nations, Centers for Disease Control and National Institutes of Health.
She stays in touch with her first love, program evaluation, by heading a multi-year evaluation of a workforce development program for underemployed adults in Virginia. Ann is also the chair of the American Evaluation Association's Data Visualization and Reporting interest group and past Secretary for the Washington Evaluators. Learn more at www.annkemery.com/blog.