Changing Organizational Culture With Better Data Visualization

Keynote-Stephanie-Evergreen.pngeAIR recently spoke with Stephanie Evergreen, opening keynote speaker for the 2018 AIR Forum in Orlando, Florida. She is best known for using a research-based approach to help researchers better present their data to stakeholders through more effective graphs, slides, and reports. A Fulbright scholar, her dissertation illustrated the extent of graphic design use in written research reporting. Her book, Effective Data Visualization, reached #1 on Amazon's bestsellers list. She authors a popular blog on data presentation at StephanieEvergreen.com.

eAIR: If there was one key idea you would want readers to take away from your book Effective Data Visualization: The Right Chart for the Right Data, what would it be?

We have so many more graphing options than pie charts and bar charts. If you start looking, it might actually seem like we have too many graphing options! My book narrows it down to the graph types that research supports and that will help us tell a clear story.

eAIR: In Effective Data Visualization, chapter 1, you ask “What’s your point?” What are some ways researchers can effectively get to the point to produce data visualizations that stakeholders can use for meaningful decision making? 

Researchers and their stakeholders probably have some burning questions. The data (hopefully) hold the answers. So the burning questions should be our guidepost for the points we need to generate from the data that most researchers have been examining for quite some time.

eAIR: Can you share a few success stories from those who have joined the Evergreen Data Academy? 

I hear from countless readers about how my work has helped them change their organizational cultures and open up new doors for communication, internally and externally. But I’ll never forget when I was at a conference lunch a couple of years back, getting ready to receive an award, when a young man approached me and said he needed to thank me for launching the Academy. He said that joining it gave him so many new data visualization skills and the stuff he was producing at work was getting a lot of attention from his supervisors (and their stakeholders). Most importantly, he said, was that these skills put him ahead of his peers, who otherwise had all been recently hired with the same background and degree and skill set that he had. Now he had a leg up on the competition and was better positioned for the next open promotion.

eAIR: How did you develop the Data Visualization Checklist, and how can researchers use it in their day-to-day work to improve presentation of data?

The ​checklist guides people on how to create clear data visualizations. It prompts us to think about the message, the color, the clutter, and the best graph type for our data. People use the checklist on their works-in-progress to see if there’s anything else they can do to improve the clarity of their visuals. I developed the Data Visualization Checklist based on the research I saw in my dissertation and, where there was no research, what my experience consulting hundreds of clients has taught me. I’ve had to refine it a few times because both research and experience keep teaching us new insights.

eAIR: Without giving too much away, what are a few highlights of your opening keynote?

I’m so excited to join you all on May 30, at 8:00 AM. I plan to suggest that we aim for a sweet spot in our reporting and to show you a lot of examples of what that looks like. I’ll be introducing some new graph types that help us tell better stories and contrasting those with some of the typical ways institutional researchers show their work, thanks to a brave volunteer who let me go at his current university dashboard. How FUN!

 

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