Summing Up
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.
Original Article
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?
References:
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)
- Tom Dolembo
- Founder, NewNorth Institute
Good Question, Professor. The MoneyBall Generation has finally put their boots on. Occupy Wall Street has been criticized for lacking proper metrics (demands). The anarchic response is that they don't need them," bring your own list". I know many Greek-Americans and a harder working, more entrepreneurial group I have yet to find, yet Greeks are carelessly typified as irresponsible (what metrics?) by those holding their debts. The WSJ has carefully researched the inequities of executive pensions vs worker pensions in burdening corporate balance sheets. Analytics show strong earnings, the populace claims serious malfeasance by corporations to get them. It's a growing war of metrics. We might soon hear "analytics? We don't need no stinking analytics".Please, yet again, this is not a worldwide recession, it is a worldwide revolution. Disenfranchised, educated, trained and qualified Americans are finally taking to the streets. This is protest without familiar analytics, it is a revolution against cruel analytics that consistently disemploy and disenfranchise.
The MoneyBall Generation is as we speak walking downtown with a purpose, if not traditional demands. If we don't understand their metrics, then we don't understand our customers, our children, or our future. HBS will be swept into the maelstrom. How, then, will we measure that?
- Rahul Kamath
- Student (Industrial Engineering)
Be it setting the temperature of my room or running a binary code through my computer, numbers simplify my life. I try to quantify everything around me. Analysts try to put everything in numbers. Successfully interpret those numbers and you have got yourself a manager.Prof Heskett, I think 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.
True, a lot of time is spent on the analysis of historical data. But history does tend to repeat itself.
- Doug Elliott
- Principal, D. Elliott & Associates
Analytics is a branch of mathematics. It can be wonderous in what it can reveal about about the world around us. In mathematics, the beauty of a number is that it is very exact as a description. But it is also very limited in what it describes. To be as exact as a number, or a function that crunches numbers, of necessity you must crush every non number attribute out of the thing observed. And that makes for a very limited view of things in the world.Everything can be numerically modeled. That is a problem for analytics. Historically you can model stock market performance based on the changing ERA's of a baseball team's pitching staff, but I wouldn't use it to pick a stock, or a pitcher for that matter.
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 of baseball. Analytics will help you refine what you know to apply it to better effect. The is the problem with finance today. Any HBS graduate can read a financial statement. If you notice that sales grow from year to year, great. But you still don't know why. The number isn't the 'thing'- the game is.
We have too many managers of games (and businesses)that have never played a day in their lives. Giving them more analytics won't change their skillset. You have to be a player first.
- Gaurav Goel
- DGM, RCom
I don't have any doubts on the utility of good data and thoughtful analytics for identifying opportunities and to gain comparative advantage over competition. Analytics can help you to position your product as per the latent customer needs, it can help to recognize the most productive employees and profitable business units and it can help to spot the business processes that are resulting in suboptimal resource utilization. Good data put on good use can do wonders.But we do not always have good data. Incomplete data means more assumptions. Incorrect or inappropriate assumptions may create a hallucination of knowing more than what a manager actually knows. The way a manager uses data may also be influenced by the personal context. Things get more complicated in big organizations operating in multiple countries and offering diverse services.
I think that for analytics to be able to contribute significantly in the context of large multinational organizations, we would need prudent processes for data capture that ensure a consistent quality of data. Once good data is available, one needs to define the assumptions and context within which this data is useful. A good analysis within these constraints can help an experienced manager to validate her ideas. A flexible manager may also derive interesting insights that can change the rules of the game in established industries.
Analytics is a powerful weapon but it needs ammunition of good data and right skills / intentions of the operator to be useful for business.
- Pete DeLisi
- President, Organizational Synergies
There is so much emphasis these days on analytics. As you and the others point out, the use of analytics depends vitally on understanding the business and knowing what to measure. We also need to counterbalance analytics with the ability to see the big picture. Recently, I have had the experience of working with a large bank on refinancing my home mortgage loan. I have been a long-standing customer of this bank and was solicited by the bank to refinance my mortgage. In the process, however, underwriting has become so preoccupied with the details of my financial status that they have totally lost the pattern of what's going on. There's another related lesson here. In the case of the bank, analytics are being used to minimize risk, but perhaps, at the expense of the more important goals of growing revenues and keeping satisfied customers. The latter lesson suggests that analytics can't be divorced from an understanding of the respective priorities of our organization.
- Andrew Boer
- President, MovableMedia
I completely agree we are a Moneyball generation-- until your article I didn't realize that we at MovableMedia have created a "MoneyBall" content marketing agency. We generate articles like many other companies, but we actually measure performance and we try to only work with guest bloggers and writers who bring audiences. Never occurred to me that we approach things this way partially due to a generational divide. Love this metaphor.- Anonymous
Joe Morgan: "The guy that wrote Moneyball can't teach me about the game. That is what I meant. If you haven't been on the field, why should I read your book? How can that person teach me about the game? I learn plenty about the game everyday. Every Sunday night I learn something. The game changes almost every day. But I'm still not going to read Moneyball or books written by people who haven't been on the field or really experienced what goes on in the game of baseball."- Ravindra Edirisooriya
- Senior Accounting and Finance Major, Missouri Southern State University
Good Professor Heskett has raised another great question about the predictors of future business performance, which is not quite possible with the traditional analysis of historical financial data. He asked: can "analytic ability and a basic understanding of the business" be useful in predicting the future of business performance? The greater question is what systems do managers have at their disposal to predict future business performance and why analytics now? This may surprise some of you but it is true (documented) that some businesses (under cover) seek future business predictions from renowned and sophisticated crystal ball (anything based on scientifically unsubstantiated practices or methods) readers (fortune tellers). There are expert knowledge based predictive systems for natural phenomenon with a few and far in between events, which can be adapted to forecasting future business performance. Heuristics, a form of adaptive learning can be used in "forgiving" or less competitive (monopolistic or oligopolistic) businesses. Decision trees, neural networks, probabilistic and statistical models, simulation models, combinatorial optimization, linear and nonlinear programming models (see Data Envelopment Analysis and Its Extensions, my thesis) could be applied in the prediction of future business performance. Each and every one of these methods /models should somehow account for (at least) suppliers, consumers, competition, substitutes, and potential new entrants to the businesses. So why could be analytics cutting edge in forecasting future business performance now? It is the exponential growth and availability of cheap computing power which has extended human analytical power and capacity to think in (multi) n dimensional space (local space and time is four dimensional), unthinkable to idol worshippers in the days of Galileo (and before) and after. How would analytics change o
ur society and the future of humanity beyond business? What if dark energy is proved to exist? What if there are parallel universes? Are you ready to find another you watching yourself (toiling to make a living against all odds on this earth) in a "Heavenly" body?
- Kapil Kumar Sopory
- Company Secretary, SMEC(India) Private Limited
One need not ignore the importance of recorded historical data which must be retained at least for the retention period, if any, statutorily laid down. The law of probability says that repetitions would occur and therefore trend observation helps in decision making.Both direct and indirect goals need to be set and targeted. New measures to track down perfomance of the bottomline is also a desirable innovation.
The role of analytics is important and be appreciated. They can be fully involved in suggesting measures for improvement. These might be theoretical at times and many would like to ignore/brush aside these but a truly involved and a well wisher of the organisatin would not do so. Churn what is said and use whatever is worthwhile.
- Yedendra Chouksey
- Professor, International School of Business & Media, India
Sir Isaac Newton was not exaggerating when he called mathematics "the queen and servant of mankind". Analytics coupled with computer technology offers tremendous scope for enhancing problem-solving and decision-making capabilities. However, to the extent that the selection of right data is a material factor and that the same data can be analyzed in different ways by different people to arrive at different conclusions, use of human intelligence and creative thinking plays an important part in getting the results of the kind Oakland Athletics' general manager did. Insights through creative statistical analysis and challenging conventional wisdom with the help of data emphasize the importance of the right side of the brain as well.The answer to the question whether we are into the Moneyball Generation is culturally determined and financially dictated. The rush for analytics may be on the increase in US right now but how long it will be sustained will follow from their financial success rate. In some Asian countries the dwindling interest in the study of science and engineering tells a different story.