Harnessing Quant Power

“Words have become data; the physical states of our machinery have become data; our physical locations have become data; and even our interactions with each other have become data,” writes journalist Alden M. Hayashi. “Indeed, we are awash in information, but what does it all mean?”

In “Thriving in a Big Data World” in the Winter 2014 issue of MIT Sloan Management Review, Hayashi reviews 2013’s Keeping Up with the Quants: Your Guide to Understanding and Using Analytics (Harvard Business School Publishing) to see how a pair of well-known academics are answering that question.

Written by Thomas H. Davenport (Babson College) and Jinho Kim (Korea National Defense University), Keeping Up with the Quants “is geared toward executives who are not themselves analytics experts but whose jobs increasingly require them to understand and deal with those who have such expertise, both inside and outside their organizations,” writes Hayashi.

The book outlines a framework for how to think like a quantitative analyst (“quant” is shorthand for the analysts who use stats to help solve business puzzles). The framework has three steps: “framing the problem,” “solving the problem” and “communicating and acting on results.”

Framing the problem. “This step might at first seem simple and straightforward, but it is often neither,” notes Hayashi. “Take, for example, the company that wants to learn the success rate of its direct mail campaign, so it asks, How many people will buy the product after receiving the mailing? Instead, the question it should ask is this: How many people who wouldn’t have bought the product will now buy it after receiving the mailing?” Framing the problem, say Davenport and Kim, must involve many stakeholders, to get both their input and their buy-in.

Solving the problem. This step involves modeling, data collection and data analysis. One example: the insurance company Progressive, which “gained a competitive edge over rivals by using FICO credit scores and other data to assess the likelihood that a particular person would be involved in a car accident in the future.” Tools help companies take into account both “structured data” (such as a person’s age and income) and “unstructured information” (such as text and images).

Communicating and acting on results. Never underestimate the power of a clear presentation — especially when the topic is one that many people find either confusing or overwhelming to begin with. “The clearer the results presentation, the more likely that the quantitative analysis will lead to decisions and actions — which are, after all, usually the point of doing the analysis in the first place,” write Davenport and Kim. Better still if results are presented in an engaging, user-friendly format.

Hayashi notes that “An important point made in Keeping Up with the Quants is that this new era of computational prowess does not obviate the need for intuition and creativity, and that is especially true in the important first step of framing a problem.” Davenport and Kim write: “Half the battle in problem solving and decision making is framing the problem or decision in a creative way so that it can be addressed effectively.”

For more from Davenport, see our video conversation between Davenport and Erik Brynjolfsson, the Schussel Family Professor of Management at the MIT Sloan School of Management and the Director of the MIT Center for Digital Business. The conversation, recorded in 2012, covers what’s different about today’s analytics, the aspects of analytics that business leaders should be thinking about right now and how achieving the potential of analytics may require change management.

Hayashi’s book review also recommends two other books on the power of big data and quantitative analytics: Big Data: A Revolution That Will Transform How We Live, Work, and Think (Houghton Mifflin Harcourt, 2013) by Viktor Mayer-Schönberger (Oxford University) and Kenneth Cukier (The Economist) and Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (John Wiley & Sons, 2013) by Eric Siegel (founder of the conference Predictive Analytics World). Read about all three books in the full book review.