What threw “storytelling” with data off the rails?
The S word is barely spoken among the “data driven” yet freely used in law and science
Somewhere, “storytelling” with data went off the rails. Maybe it never had any rails — or maybe it went off the moment it was noticed, named, and memed. It became marketing, just more hype, like the “organic” juice that got cut loose from its provenance several iterations before market.
“Data storytelling” seems to have begun long ago by Tom Davenport of Competing on Analytics fame. He said the data scientist’s most important skill was to “tell stories.” Whatever “stories” he meant, it probably wasn’t mere parades of data, no matter how well sequenced the charts may have been.
Storytelling with data quickly became a thing, and it sold books and courses. Whether the trend derived from Davenport, or his observation derived from an already-extant meme, storytelling took hold like weeds in spring. Every marketing person seemed to advise, “Tell a story.” Today, many recipes for, say, white rice include a “story” that takes longer to read than to cook the rice.
Yet hopeful new shoots have appeared. One appeared in Donald Farmer’s fascinating “Curiosity,” a Domo-sponsored series and a classic worth a visit whenever despair for the data industry sets in. Listen between the lines and you can hear stories lurk, unnamed as such except sparingly by Donald.
One of those stories, for example, is about how an emergency room doctor humanized data for an IT tech. The doctor’s story got the technician to hurry up with a small but meaningful project.
Another notable moment in “Curiosity,” though not a story, came with an observation when eminent analytics consultant and author Jill Dyché observes an errant meme in the data analytics world. She pointed out how much is lost by, for example, assuming users in a truly “data driven” organization can write regressions in Python, as if to use data is to be technical. Such assumptions obscure other skills and knowledge, and valuable “tribal wisdom” goes to waste. Stories, not data, carry that tribal wisdom.
Stories and storytelling get better treatment in law and science — where they’re honored and practiced without embarrassment.
Are lawyers and scientists any less qualified to assess evidence, such as data, than our everyday “data driven” business practitioner? No, they’re probably as qualified or better. If nothing else, many seem to give explicit credit to stories as way-finding tools. That explicit credit helps to socialize or reinforce storytelling’s deployment.
Even with that, I still don’t understand: Why is the S word so little used among the so called “data driven”? Are they so insecure about their skills that they cling to the ostensibly rigorous use of data? Do they rely so much on data technology and the ridiculous notion of “data driven” to assure them and their colleagues of their allegiance to facts?
They should get over it. The pretense is fragile. Sooner or later, the mystique will collapse like a cardboard stage set as a full house looks on.
When storytelling finally gets the acknowledgement it deserves, there will be a new battle: fighting overuse and abuse — the white-rice recipe problem.