Data storytelling is a popular term in the field of data analytics. Storytelling implies looking deeply into the data to find the important messages and communicate those messages in the most effective ways. It’s a powerful concept that is sometimes 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 visualization is an important part of analytics. You can read some of my thoughts on visualization in The Other Side of Data Visualization where I discuss visualization as “the language of images” with visual equivalents of reading and writing. Data storytelling goes well beyond visual presentation of data. Data stories complement visuals with narrative. They combine the language of images and the language of words.

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 change the way that we interact with data, transforming it from a dry collection of “facts” to something that can be entertaining, engaging, thought provoking, and inspirational. Four good reasons to pursue the art of storytelling are:

• Stories are memorable. Most people retain the message of a story longer and with better recall than retention for numbers and statistics.
• Stories are passed on and retold. People love to share a good story, so the reach and social impact of stories is typically greater than for numbers.
• Stories invite personal involvement & engagement. A well told story causes the audience to “see themselves” somewhere in the story bringing a higher level of engagement, communication, conversation, and overall involvement.
•  Stories motivate people to take action. When stories become personal they also become motivating. Stories are more likely to drive action than are statistics and numbers.  Storytelling does much more than just put a pretty face on facts

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 7^th 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, think about the hype around “data-driven” today. Is data-driven the holy grail of analytics? What about narrative-driven or story-driven? Please share your thoughts and comments. I’d like to hear your perspectives on visualization, storytelling, and communicating with data.