One question that I regularly hear in my data visualization talks and workshops goes something like this: “How do I get my boss/manager/colleagues to prioritize better data visualizations?” It’s a common conundrum: you have some interest in data visualization, but your organization is not as motivated as you are. You might hear something equivalent to, “The data is there and that’s good enough.”

In my experience working in and with teams and organizations seeking to improve their data visualization processes, I have found four strategies that help bring managers and colleagues on board to understand and value better data visualizations.

  1. Show comparisons. Simply saying, “I know a better way to visualize these data” isn’t going to convince anyone. You need to show people what a better graph or chart looks like—and why. You might need to demonstrate why a horizontal bar chart is better than a vertical bar chart by showing how the horizontal labels are easier to read. In cases where you want to use a graph that your reader has never seen before, you might need to walk them through it, either verbally or with annotation and labels.
  2. Use real data. If you’ve read my blog or books, you know I like to use real data. I do this for three reasons. First, it’s more effective for both the reader and myself—I often learn something by working with data and visualizing it in new or different ways. Second, real data is messy. It’s too easy to make up data that works perfectly with the chart type I want to use. But with real data, there are outliers, extremes, or groups that don’t quite align. Finally, real data helps people connect with the content. By using real data that they work with in their day-to-day, managers and colleagues can see how their work could be communicated more effectively. Allowing them to see their data in those better visualization types can help them understand the value of better visualizations. Remember, if they think that “the data is there and that’s good enough,” you need to convince them that a new or different graph is a better approach.
  3. Create a style guides. People will often get hung up on colors, fonts, or font sizes in reviewing your work when you want to know whether they actually like the revised presentation of the data. If you and your team or organization can develop a data visualization style guide, you can quickly get by those issues. The blue color in your bar chart is now the blue color that everyone has agreed to, so we can instead focus on the graph itself. By removing branding variables from the equation, you can get people to the core of your question—a new, different, better graph or chart or report layout. If you need help building a data visualization style guide, check out the Data Visualization Style Guide project I’ve been working on with Max Graze, Alan Wilson, and Amy Cesal. 
  4. Don’t over-engineer it. When you’re trying to build a better data (visualization) culture in your organization, starting off by asking for more money or time is not likely to be successful. Don’t try to create some complex, bespoke, interactive data visualization in D3 or ask your managers to some buy expensive software. Don’t over-engineer it. Instead, identify your ultimate user base while keeping your colleague or manager audience in mind. If you’re creating visualizations that your manager doesn’t understand or can’t use, you’re not going to get to the next stage and get that work out the door. In the long run, the interactive data visualization might be the right solution, but you need to take steps to get there—maybe a series of graphs in a tool like Tableau or even a set of slides in PowerPoint.

Not everyone will share your excitement for better charts and graphs at first, or maybe even ever. But I have found that enthusiasm among a small group of people—or even just an individual—can help change how an entire organization thinks about their data and their data visualizations. Changing organizational culture takes time, and I believe these four strategies can help you bring about change to generate better outcomes.

Want to learn more about data visualization? Check out my book, Better Data Visualizations, my Substack newsletter, and my new virtual data visualization course with Skillwave Training, The Art and Science of Data Visualization.