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How to Tell Stories About Data

Short Takes...on Analytics

Posted by Tom Davenport, Independent Senior Advisor, Deloitte Analytics


Ever wonder why books like Nate Silver’s “The Signal and the Noise: Why So Many Predictions Fail-but Some Don't”1 or Michael Lewis’s “Moneyball: The Art of Winning an Unfair Game”2 are so popular? In part it’s because of their ability to “tell a story with data.” They write about content domains—electoral politics, professional sports, and financial services—that are becoming increasingly quantitative. Yet they are able to communicate quantitative issues in straightforward fashion; they don’t let the numbers get in the way of a good story.

Quantitative analysts and data scientists within companies also need to tell stories with data. In the current issue of Deloitte Review, I’ve described some of the ways—including stories—in which “quants” can communicate with non-quants. This skill, which unfortunately isn’t taught much in schools, can be a critical one for  organizations focused on making data-based decisions.

To tell stories about data, quants need to learn about the types of stories to be told (basic “here’s what happened” reporting story, investigative reporting story, prediction story, experiment story, etc.), and what kinds of story arcs should accompany each type. The statistical method story—“first we ran a chi square test, and then we converted the categorical data to ordinal, then we ran a logistic regression, then we lagged the economic data by a year…”—is not an acceptable alternative. It prevents any business-oriented discussion about the results of a quantitative analysis.

Of course, words are not the only way to tell stories, and many big data projects have visual analytics as their primary output. Many managers like seeing visual analytics, and mastering the art and science of visualization is a good idea for analysts. Just remember that visual analytics do not themselves create a story for many observers. They often need to be put into context and explained to some degree. In other words, they often need to be accompanied by words!


1. Silver, Nate, The Signal and the Noise: Why so Many Predictions Fail-but Some Don’t, New York, NY: 2012 

2. Lewis, Michael, Moneyball: The Art of Winning an Unfair Game, New York: 2004

This publication contains general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor.

Deloitte, its affiliates, and related entities shall not be responsible for any loss sustained by any person who relies on this publication.

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