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Recently, a follower on Twitter reached out to share her frustration over the results of her data storytelling research.
“We’ve been researching the topic like crazy, but I don’t seem to find an agreed upon definition for it.”
I’ve spent my entire career in roles that required a storytelling skillset, so I understand the confusion. To cut through the noise, I’ve found it most useful to find and learn from established experts who have been evangelizing the power of story in a data world. Like my peer Robert Allison. He has a knack for writing about topics that resonate with the SAS user demographic. His most popular being: Marriage and divorce in the US: What do the numbers say?
Robert’s goal is simple: Get users excited about data while educating them on new techniques for designing visualizations using SAS technology. He knows the way to a reader’s attention is through relevant, everyday examples. What’s his secret? A simple 4-step process that starts by locating a trending topic he then turns into an engaging data story.
Step 1: Research Relatable Topics
Robert looks “for trending topics in a variety of places. News sites, Reddit, flowingdata.com, fivethirtyeight.com, nytimes.com, etc.” He knows his target audience, which means he knows what appeals to them. They’re data professionals whose role is to communicate results to the business to drive better, data-driven decisions. Based on the level of engagement his marriage and divorce article amassed, the topic certainly resonated with the data community.
There’s a balance though. The CEO of Frameworks Institute tells us that “Some messages may be highly resonant—they may connect with people in deep and powerful ways—but lead in directions that do not align with our strategic objectives as communicators.” If the trending topic doesn’t align with the predetermined objective, look for one that does.
Step 2: Locate Public Data Sets
If you want an audience to embrace the story, the supportive data needs to be evidence-based. Locating data that’s flawed just to fit within a storyline is misguided.
Here’s the tricky part Robert noted, “You have to find something that’s trending that you can also get data for. Hopefully, the article mentions their data source, or provides a link to it.” In other words, he avoids topics that appear interesting, but offer little in the way of available data to design a companion visualization.
His data research is methodical. He spends time curating data – sometimes from multiple sources – to offer a holistic view of a subject. The marriage piece was triggered by an article in the The New York Times. That led him to sites like prospect.org and the CDC to gain a broader perspective.
Step 3: Design a Supportive Visualization
Our brain needs both story and logic to feel good about the decisions we make. The problem Robert says, “Too often, people create a graph just for the sake of creating a graph.” The visualization should inform the audience, not confuse them.
Because he’s teaching a new skill he’s often looking to create an improved version of someone’s visualization. Sometimes though, he finds interesting data (minus the visualization) and designs something from scratch.
Regardless of the route he chooses, readers are exposed to new ways of thinking about data visualizations. The most important aspect is that “if a graph is trying to communicate too many things, it won’t do a great job of communicating any of those things – keep it simple!”
Step 4: Write the Narrative
For Robert, the narrative and supportive data visualization go together. But he says, “Sometimes it’s a chicken-and-egg thing which means the narrative may come first, other times the visualization does.” For this, he offers a little coaching, “Stay flexible and let the story (and visualization) develop.”
Illustrator, Stacey Williams-Ng says, “Brain research shows us nothing captures our curiosity more than the question, “What happens next?” In the case of Robert’s marriage article, he opened with a personal story. This technique allowed him to piqued the audience’s interest while posing a pondering question: “Based on your keen powers of observation, which wedding do you think ended in divorce?”
He transitions into the meat of his story by sharing a practical application of data visualization. Then, he closes the gap he’d opened at the beginning. Which couple found their happily ever after?
Yes, there are a ton of opinions and excitement around the power of story when it’s married with data. With so many, how do you know whose to subscribe to? My advice is to follow industry leading storytellers. People trust their guidance because they’ve successfully applied the technique in their own practices.
Here are 10 of my favorites to get you started:
Jennifer Aaker: @aaker
Robert Allison: @RobertAllison__
Alberto Cairo: @albertocairo
Andy Cotgreave: @acotgreave
Ted Cuzzillo: @datadoodle
Andy Kirk @visualisingdata
Cole Knaflic: @storywithdata
Robert Kosara: @eagereyes
Ben Wellington: @IQuantNY
Nathan Yau @flowingdata
Who are some of yours? And why?