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While data analytics boosted early adapters such as baseball’s Oakland Athletics, its value levels off once the ‘secret sauce’ is widely available, University of Toronto researcher says

Brad Pitt, centre, stars in Moneyball, a Hollywood film about the Oakland Athletics' unlikely surge using data analytics to evaluate player talent.

The Globe’s bimonthly report on research from business schools.

It’s been 16 years since Moneyball, a best-selling book chronicling the unexpected rise of the Oakland Athletics baseball team, made us sit up and notice the power of data analytics.

Today, the term “moneyball” has become synonymous with a statistics-driven management strategy widely embraced by sports clubs, businesses and governments to improve performance and beat the competition.

But a new study from the University of Toronto’s Rotman School of Management suggests the “moneyball advantage” is no longer a guaranteed home run. Indeed, it weakens the more the technique becomes publicly available.

Study author Ramy Elitzur, the Edward J. Kernaghan Professor of Financial Analysis and an associate professor of accounting, says it all comes down to the “secret sauce.”

“Once the secret sauce is out, the competitive advantage, stemming from unique organizational knowledge, is lost,” he says in an e-mail.

A longtime baseball fan, Dr. Elitzur’s research drew on data from major-league baseball teams between 1985 and 2013. In particular, he studied payrolls, playoff success rates, data analytics use and player contributions – the same data the Oakland A’s mined to identify lower-priced and undervalued players, and, ultimately, drive the team’s success in the 1990s.

Dr. Elitzur sought to answer several questions. What makes a team a moneyball team? Do they actually have a performance advantage over other teams relative to their pay? Is this advantage sustainable once the use of sports analytics by these teams leaks out?

He found that between 1997 and 2001, there were only two “moneyball” teams in the major leagues. But, following the release of the book and a subsequent movie starring Brad Pitt, that number began to rise. By 2013, more than 75 per cent of major-league teams were using the technique. At the same time, the study found moneyball teams had the strongest advantage only up until 2003. By 2008, the comparative advantage was gone.

The research suggests the competitive advantage is available only to companies that are able to keep competitive strategies to themselves. Dr. Elitzur uses another Hollywood movie, also starring Mr. Pitt, to illustrate the point.

“The first rule about Fight Club is you don’t talk about Fight Club. ... The second rule about Fight Club is you don’t talk about Fight Club.”

In other words, he says, “once the secret sauce was outed, which was what happened with the book, everybody could imitate the Oakland A’s.”

Another implication of the study is that using data analytics leads to an informational advantage for the first users and, as a result, it forces other players to adapt and join the revolution, eventually leading to an arms race.

On another front, Dr. Elitzur says the research has important lessons about whom we hire and why we hire them.

“As behavioural economics teaches us, we suffer from biases when we make decisions. Studies show, for example, that we when we interview people we take [hire] people who look like us, though not necessarily physically. Using data as the basis of decision-making would help alleviate this problem,” he says.

The paper is published in The International Journal of Management Science.

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