The (Unfinished) Data Story
Once there was a data visualization professional who worried that translating data into intuitive visuals wasn’t enough to make him relevant. Too often, the villagers gave him slyly-condescending compliments like: “We love how you make data pretty.”
The Data Visualizer sat on a tree stump deep in the woods and thought, How can I be more than a ‘drawer of pictures’? A picture was worth a thousand words…but the saying offers nothing about how those thousand words change how people think. Dispirited, his gaze wandered to a fallen apple nearby, his mind wandered to the story of Sir Isaac Newton’s discovery of gravity.
“Eureka!” he exclaimed, “when you tell a story, you shape a myth. And when you shape a myth, you transform how people think. I’ll be a storyteller. My charts will be data stories, and my presentations will have powerful narrative arcs.”
The Data Visualizer — reborn a Data Storyteller — leapt off the stump and raced down the wooded path in the direction of his laptop.
And so it was that data visualization became data storytelling, and everything and nothing changed.
Data Storytelling is the newest promised path to influence, impact, and relevance for people who communicate data. I’ve spent most of my career in this camp, and would humbly submit that I helped usher in this concept. As a group, we are driven by the best of intentions: to inject data-informed insights into discussion that may otherwise be guided by deeply-held assumptions, bias, and uninformed reactions. We see ourselves on the front-lines of the fight for rationality. Data Storytelling was our powerful new weapon in this good fight.
But like most new concepts and technologies, Data Storytelling quickly became overrun by expectations and misuse:
Google Trends tracks the growing popularity of “Data Storytelling” starting around 2017
A certain corner of the web became littered with posts like this: “The Power of Data Storytelling: Captivate Your Audience and Close More Deals”. I’m as guilty as any in pushing this concept.
A mentioned of Data Storytelling in r/analytics on Reddit led to this top-voted comment:
Data Storytelling surfaced in the Gartner Hype Cycle in 2022, sitting at the Peak of Inflated Expectations.
Meanwhile, it was built into the marketing language of every data and analytics company. Everyone was telling data stories. …or were they?
But little has changed. We are still awash in bad dashboards, too-long presentations, convoluted reports. It is time to take a more critical look at Data Storytelling to evaluate:
WHY has data storytelling been more sizzling concept than a useful steak?
HOW can we reframe Data Storytelling to make it a tool that more people can use?
I’ll save my thoughts on that for Chapter 2 of our Story, where our Data Storyteller turns “Data Hipster” (thanks, CY) and wonders what hath he wrought. For a preview of the “How”, I touched on topic early this year in a post about “Data Storytelling 2.0”.