10 Data-Driven Stories

Source: HBR blog, May 2014


  1. Past: reporting story using descriptive analytics to tell what happened
  2. Present: most likely to involve some form of survey—an analysis of what people or objects are currently up to
  3. Future: predictions; they use … predictive analytics. They take data from the past … to create a statistical model, which is then used to predict the future.
    Quants create prediction stories all the time—about what customers are likely to buy, about how likely it is for an event to happen, about future economic conditions. These types of prediction stories always involve assumptions (notably that the future will be like the past in some key respects) and probability


  1. What: What stories are like reporting stories—they simply tell what happened.
  2. Why: Why stories go into the underlying factors that caused the outcome.
  3. How: How to address the issue stories explore various ways to improve the situation identified in the what and the why stories.


  1. CSI projects—relatively small, ad hoc investigations to find out why something suboptimal was happening. 
  2. Eureka stories, which involve long, analytically-driven searches for a solution to a complex problem.


  1. a correlation story—in which the relationships among variables rose or fell at the same time
  2. a causation story, in which you’ll argue that one variable caused the other?

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