Most managers understand the value of data-driven decisionmaking that scholars such as Erik Brynjolfsson at MIT Sloan and others have advocated for several years. We know that entertainment businesses like Caesar’s, logistics firm UPS, and even Gallo Wine use big data and analytics for competitive advantage. It also keeps them ahead of those using old-style, gut instinct and relying on the highest paid person’s opinion (HIPPO). By now, Moneyball is a classic example of analyzing data to win the game, and even political campaigns are adopting these techniques for predicting results and planning strategies, as described here.
Yet these managers, like me, also have a nagging feeling that human decisionmaking has its strengths and its value, too.
Now, Phil Rosenzweig, a professor of strategy and international business at the International Institute for Management Development (IMD), in Lausanne, Switzerland, has articulated some of the flaws to the all-analytics approach. He writes that there are times when executives must do their job and lead — taking action, using decisive judgment and exuding self-confidence to yield immediate results. Rosenzweig offers these insights in a new McKinsey Quarterly article, The Benefits—and Limits—of Decision Models, and in his new book, Left Brain, Right Stuff: How Leaders Make Winning Decisions (Public Affairs, January 2014).
Rosenzweig doesn’t dispute the value of unbiased data to support some decisions– in fact he calls some recent applications of analytics “truly dazzling,” and he writes:
At the same time, he does not see them replacing strong management in every case.
The takeaway for me is that making good decisions isn’t an either/or process where you can analyze the data or go by gut instinct. Rosenzweig correctly states that both analytics and the players contributed to the Oakland A’s winning season. And that blended combination of skills is often the winning answer for business executives as well.
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