The Wall Street Journal (New York, NY), October 9, 2015
Tom Davenport, the President’s Distinguished Professor of Information Technology and Management at Babson College, a Fellow of the MIT Center for Digital Business and independent senior advisor to Deloitte Analytics, discusses why storytelling with data is critical to success with analytics programs, and several reason why it doesn’t work well.
“Whenever I speak with successful analytics people—and I do that all the time—it’s usually not long before they mention the phrase “telling a story with data.” It may seem obvious that anyone who is doing data analysis would want to create a narrative of the process and outcome, but to many data analysts it’s not obvious at all. So in this essay I’ll describe five reasons why data and analytics-based stories are important to organizations, and four reasons why so many people and organizations do it badly or not at all.
Here’s why I think people who love data and analytics also need to be people who love stories and tell them well:
- Stories have always been effective tools to transmit human experience.
- No matter how impressive your analysis is, or how high-quality your data are, you’re not going to compel change unless the stakeholders for your work understand what you have done via a story.
- Stories that incorporate data and analytics are more convincing than those based on anecdotes or personal experience.
- Analysts need to find a way to deliver the salient findings from an analysis in a brief, snappy way in a story.
- Couching our analytical activities in stories can help to standardize communications about them and spread results.