Put yourself in the position of the data consumer. This was a key piece of advice from Daniel Bauer, professor of risk and insurance at the Wisconsin School of Business, in the school’s most recent EdgeUp webinar: Storytelling With Data.
On August 2, viewers tuned into Bauer’s presentation to learn more about data tools, visualization techniques, and the key principles of data storytelling. As artificial intelligence and big data gain traction in the business world, Bauer emphasized the importance of keeping data communications simple, understandable, and memorable.
Recommended data tools
While Bauer acknowledges the solid capabilities of Microsoft Excel, he also points out the advantages of other business intelligence tools like Tableau and Power BI. Not only do these tools integrate naturally into the cloud environment, but they expedite and simplify processes like pivoting, allowing users to produce cross-sectional data sets more efficiently.
Your guide to graphs
Graphs make information based on data easier to process and remember—but the type of graph being used can significantly help or hurt your data storytelling abilities. Bauer suggests these quick tips for choosing the right graph:
- Only use a table when a specific number is important
- If you want to compare different items, such as customers, firms, or industries, use a bar graph
- If you want to look at metrics over time, use line graphs
- Avoid pie charts
Most importantly, Bauer recommends keeping your graphs simple, consumable, and easy for the audience to digest. “It’s better to have multiple charts that are simple, rather than one complex chart,” he says.
Dashboards are data visualization tools that provide real-time updates, information at your fingertips, and easily sharable content. However, Bauer warns of the cognitive biases that come into play when using data dashboards, which can cause your audience to come up with reasons why the data contradicts their expectations. To mitigate these biases, Bauer suggests that data consumers look for information and trends that challenge their original thinking, rather than confirm it. A simple exercise: Sketch what you think the graph will look like before you see it. This allows you to be surprised and helps prevent cognitive bias interference.
Telling the story
Bauer also introduced some of the key principles of data storytelling. Because people are more likely to remember a well-told story than cold hard facts, it’s crucial to present data in a way that is meaningful and memorable to your audience. Ask yourself: What story am I trying to tell, and what data will help me tell this story? Choosing the appropriate data to highlight, positioning your main point in the title, and including text annotations are just a few ways to tell a memorable story with data.
Daniel Bauer is the Hickman-Larson Chair in Actuarial Science and current chair of the Department of Risk and Insurance at the Wisconsin School of Business. Bauer teaches classes in actuarial science, quantitative finance, and data analytics, and also serves as co-director of the Master’s in Business Analytics program.