People who love data and analytics also have to be people who love telling stories and tell them well. That’s according to Tom Davenport, independent senior advisor at Deloitte Analytics. Davenport offers five reasons why data-based and analytics-based stories are so important to organizations, and four reasons why people and organizations don’t do it well, if they do it at all.
5 Reasons Storytelling Is Important
- The way people simplify and make sense of this complex world is through narrative, which supplies context, insight, interpretation—“all the things that make data meaningful and analytics more relevant and interesting,” Davenport says.
- People use analytics to change the way business stakeholders make decisions. But even the most impressive analysis won’t persuade them if they don’t understand the work that that’s been done. “That may require a visual story or a narrative one, but it does require a story,” notes Davenport.
- Stories based on personal experiences and anecdotes may be convincing, but those that incorporate data and analytics are even more persuasive. However, the most compelling stories are those that incorporate data and analytics as well as a real-world examples, according to Davenport.
- It’s critical that an analyst deliver the most important findings from an analysis in a brief, “snappy” way or else it would take too much time and be way too boring to share all the details of a quantitative analysis with stakeholders. “Stories fit the bill,” Davenport says.
- Framing analytical activities in stories can help “standardize communications about them and spread results.” Davenport says he has argued that there are 10 kinds of stories to tell with data. But no matter the number, if an organization is clear on the different types of stories it can tell with data and analytics, it’s more likely that analysts will explore those different types over time. “Most importantly, the story repertoire should go well beyond basic ‘here’s what happened’ reporting stories,” Davenport says.
4 Reasons People and Organizations Aren’t Good at Storytelling with Data
- Most analytics folks just aren’t all that fired up to communicate with other living, breathing individuals—or they’re not successful at it. “Let’s just acknowledge that telling compelling stories to other humans may not come naturally to many analysts,” Davenport notes.
- If storytelling doesn’t come naturally to analysts, they probably didn’t learn about it in school, either. That’s because college professors teaching quantitative courses aren’t all that good at storytelling and they may not want to “waste time” on teaching storytelling. But Davenport points out the error in that way of thinking. “One survey of about 400 recruiters of analytical college graduates, summarized here, found the highest ranked of all desired skills was communication,” he says.
- To some analysts, engaging in storytelling isn’t as valuable an investment in time as more technical pursuits. They may think that the best use of their time and effort is to do quantitative analysis, and leave the storytelling to more capable people. “They may have a point, but relying on others to translate analytical results into stories has some perils of its own, in addition to being more labor-intensive,” Davenport notes.
- Analysts believe it takes too much to think creatively about how to tell a good story with data—time they’re not willing to devote to it, even if it would make them more effective.
“So there are several reasons why storytelling with data is critical to success with analytics programs, and several reasons why it doesn’t work very well,” Davenport says. “I’ve constructed this story so that there are more reasons to tell good stories than there are obstacles to the objective, so the story ends happily.”
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