Data storytelling has become a popular term in the field of analytics – looking deep into the data to find its important messages and communicate those messages in the most effective ways. It’s a powerful concept that is unfortunately diminished by those who position it as synonymous with data visualization – data viz vendors who adopt it as a marketing buzzword, pundits who equate it with visualization best practices, and so on. Data storytelling is much more than sophisticated ways to present data visually. Data stories combine data and narrative.
Stories are powerful things. We’ve used them throughout history to capture attention, convey ideas, fire the imagination, and stir the soul. Data can be persuasive, but stories are much more. A well-told story is inspirational narrative that is crafted to engage the audience. Stories have impact that isn’t possible with data alone. They are memorable, they are frequently passed on and retold, they invite personal involvement, and they motivate people to take action.
On the surface, narrative storytelling appears to be the opposite of analytics – anecdotal instead of quantitative. But quantities aren’t the only way, or necessarily the ideal way, to convey information. Not everyone in business is a quant who thinks natively in numbers. Some think in pictures, thus the popularity of data visualization: “Show me the shape of things, not the quantities. …” Visualization is powerful, but even more powerful is the ability to connect visuals, and to tell a story with data.
Narrative is the key. Data is ambiguous and contextually deficient. Visualizations are subject to interpretation (and misinterpretation). Narrative reduces ambiguity, connects data with context, and describes a specific interpretation. To view an interesting example of blended visualization and narrative, check out Split Country: Dunkin’ vs. Starbucks. Be sure to scroll through the page to get the full effect.
Hans Rosling, a Swedish professor, was the master of data storytelling. Rosling passed away on February 7th of this year. He left quite a legacy of data storytelling as well as a passion for social and economic justice. To see Rosling at his very best, watch The Best Stats You’ve Ever Seen – compelling visuals and powerful narrative.
To experiment with interpreting visual data take a look at this graph. Write a brief narrative (a paragraph or two) to describe what the graph says to you. Share the graph with colleagues and ask them to write a narrative. You’re sure to find some differences of interpretation. If you want to share your interpretations and to see mine, send me an email and I’ll be happy to share and to comment.
Finally, I’ll ask you to think about the hype around “data-driven” today. Is data-driven the holy grail of analytics? What about narrative-driven? Or story-driven? I invite you to comment on this blog. It would be great to engage in a lively discussion of these questions.