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Visualizing data in this manner is a surefire way to lose your audience. You're asking them to decipher information and find insights for themselves.
Now imagine if we applied data visualization principles to the above data. The below chart is an excellent example of how to make data easily digestible. I'll explain why...
Beyond clarity: A compelling headline hints at the value the reader will gain. (Example: "The 3-Word Headline That Makes Data Irresistible")
Test options: Come up with 3 to 4 headline variations to see which feels strongest.
Remove extra steps: Direct labeling is when a label is placed next to a data point. It saves viewers the burden of referencing a separate legend, improving understanding.
When legends are needed: Keep them simple and position them close to the corresponding visual elements.
Decluttering: Removing redundant symbols allows more space for the important elements – the data itself.
Consistency is key: Use consistent highlighting to create a visual pattern the audience learns to recognize quickly.
Accessible colors: Blue and orange is a common color combination that's friendly for people who are color blind.
Arrow alternatives: The start of the arrow is 2013 and the end of the arrow is 2022. For smaller changes, a '+' or '-' sign can also indicate direction.
Trustworthiness: Always cite the data source! This builds trust, adds credibility, and allows viewers to investigate further if desired.
Formatting matters: The source should be visible but not distract from the main visualization.
Benchmarks matter: Contextual data anchors the viewer's understanding. Other benchmarks could include averages, historical trends, and/or targets.
Purposeful sorting: Data can be sorted by magnitude, alphabetically, or another logical pattern depending on the story you're telling.
Ranking is optional: Rankings can be useful, but consider if highlighting the top/bottom few items would be more impactful.
Descriptive and concise: Labels should accurately guide the viewer without being wordy.
Consider hierarchy: If one category is the primary focus, make that label slightly more prominent (size or boldness).
Data visualization isn't just about making things pretty. It's about unlocking the insights that drive better decisions.
Effective data storytelling goes beyond individual slides or presentations. In business, it empowers us to cut through complexity, align teams around a shared understanding of the numbers, and make faster, more informed decisions. Whether you're analyzing sales performance, customer trends, or operational metrics, clear visualization is the key to unlocking the insights that truly drive success.
Now, I challenge you to find the stories waiting to be told using your data! Try applying any of the above best practices to your work. Share your before-and-after transformations in the comments below – let's learn and improve together!
For the original chart and analysis, see @ashleywu's article, "The Nation’s Top-Performing Public School System" published in The New York Times. (Oct. 10, 2023).
Brandon Chin is a Creative Director at fassforward. He uses his skills in design, data, and strategy to transform complex ideas into simple ones. He has experience in art, data visualization, and storytelling. Brandon Chin is a lifelong learner.
