Should "Moneyball Analytics" Play a Greater Role in Preparation for Management?
There was general agreement among respondents to this month's column that we will see a growing emphasis on analytics among managers as millennials enter the ranks of management. The question, of course, referred to a type of analytic data that might suggest nontraditional indicators designed to provide a competitive edge in everything from investments to selection of talent.
One such example is the use of puzzles to select employees (who in effect select themselves) at Facebook. Those responding with creative solutions to puzzles posted on the Facebook website are given interviews regardless of what their resume information might contain. Many are hired. Such analytics often represent "deep indicators" of the kind increasingly familiar to readers of books like Freakonomics.
Several respondents suggested that the successful use of such analytics require much more than the data itself. For example, Doug Elliott commented that "The lesson of 'Moneyball' is about knowing what to look for in the first place. You first have to be an expert in the game… Giving (managers) more analytics won't change their skill set. You have to be a player first." Pete DeLisi added, "We also need to counterbalance analytics with the ability to see the big picture… analytics can't be divorced from an understanding of the respective priorities of our organization." Observed Gaurav Goel: "Analytics is a powerful weapon but … we … need prudent processes for data capture that ensure a consistent quality of data."
The tone of responses suggested that there was little question that the analytics of "deep indicators" would be used more extensively by management in the future. Rahul Kamath commented, "… the Moneyball generation is already with us. Here in India, being good in analytics is a kind of pre-requirement for admissions to B-schools."
This raises an interesting set of questions for other highly reputable degree and non-degree programs designed to prepare millennials particularly for future leadership. Should applicants be winnowed out with the use of "deep indicator" analytics like the puzzles used by Facebook? Should curricula place greater emphasis on the design and use of analytics for decision-making? Should Moneyball Analytics play a greater role in preparation for management? If so, what should it replace? What do you think?
Jim Heskett's latest book,The Culture Cycle, was published in September.
In the past we've discussed the importance of adding nonfinancial measures to the management dashboard, "indirect goals" that help predict and explain financial performance beyond the "direct goal" of profit. These might include the speed of aircraft turnaround in the airline industry, the conversion rate of people entering a store who actually purchase something, and employee loyalty in organizations with large numbers of workers in direct contact with customers.
The new movie Moneyball (and the book on which it is based) extol the virtues of employing nontraditional thinking and measurement in major league baseball. The Oakland A's studied player performance data through the lens of "sabermetrics" to compete with much better-funded organizations, achieving success with a relatively small investment.
Writing recently in The New York Times, Cade Massey and Bob Tedeschi speculate on whether the film will rekindle the study of analytics in business schools and peak the interest of what may become a "Moneyball Generation" of managers and analysts who want to divine and track new measures that explain bottom line performance and provide a competitive edge. They ask whether we are on the verge of an ascendancy of those capable of teaching and performing the analytics necessary to supply the talent that the "new management" will need.
While exploring the substantial impact of organizational culture on performance, reported in my recent book The Culture Cycle, I specified 35 items of information needed to complete the proposed analysis. Many of them could be regarded as "indirect" performance measures, presumably of interest to managers and the investment analysts who regularly examine their work. They included such things as the proportion of new business referred by existing customers and the proportion of employees leaving the organization voluntarily. When I attempted to collect the data in several organizations, I was typically told that the data was easy to get for only about a third of the items. The other responses were either "Others have the data; it's difficult to get" or "I don't think the data exists." (In these instances, I came up with estimates and went on with the necessary calculations.) I wasn't surprised. How many of us have sat in on board meetings where the analysis of historical financial data went on far too long with little attention given to the predictors of future performance?
The fascination with analytics is understandable. How better can one achieve competitive advantage in a manner that is hard to replicate? But clearly there is a long way to go to enable managers to practice this kind of data-driven decision making. It will require dedicated talent who combine analytic ability with a basic understanding of the business, as well as increased attention given to analytics (the "new managerial economics?") in business school and traditional economics curricula.
The question then is: To what extent will we begin to see a higher profile for analytics in management ranks? How, if at all, will a Moneyball Generation influence management? What do you think?
Michael Lewis, Moneyball: The Art of Winning an Unfair Game (New York: W. W. Norton & Company, 2003)
Cade Massey and Bob Tedeschi, When Data Guys Triumph, The New York Times, October 2, 2011, p. BU6
James L. Heskett, Is Profit as a "Direct Goal" Overrated? Working Knowledge, July 2, 2010
James L. Heskett, The Culture Cycle: How to Shape the Unseen Force that Transforms Management (New York: The FT Press, 2011)