I began talking about finding and then telling the stories that reside in data 13 years ago, several years before “data storytelling” became a common expression and popular pursuit. Mostly, I was speaking of stories metaphorically. In some respects, I regret using this expression because, like many metaphors, its use has become overblown and misleading. I did not mean to suggest that stories literally reside in data, or, if I did, I was mistaken. Rather, facts reside in data from which stories can sometimes be woven. Literally speaking, storytelling involves a narrative presentation that consists of a beginning, middle, and end, along with characters, plots, and often dramatic tension. Data does not tell stories, people do.
Don’t be misled: data storytelling (i.e., the presentation of data in narrative form) makes up a tiny fraction of data visualization. The vast majority of data visualizations that we create present facts without weaving them into stories. Relatively few of the facts that we display in data visualizations lend themselves to storytelling. I’m not diminishing the usefulness of data storytelling, which can be incredibly powerful when appropriate and done well. I’m merely pointing out that data storytelling is not some new endeavor or skillset that dominates data visualization. It is a minor—but nonetheless important and useful—aspect of data visualization. Not everyone who works in the field of data visualization must be a skilled storyteller. In general, it’s more valuable to be skilled in data sensemaking and graphicacy, as well as a clear thinker and communicator, and to possess knowledge of the data domain.
When facts can indeed be woven into a story, however, do so if you know how. We love stories. They can breathe life into data. Just don’t try to impose a story on a set of facts to create life where it doesn’t exist.