Via forecasting expert Mat Fogarty of Xpree (cited but not linked to, alas, in that story), the New York Times (2 pages):

“The potential is that prediction markets may be the thing that enables a big company to act more like a small, nimble company again,” said Jeffrey Severts, a vice president who oversees prediction markets at Best Buy, the electronics retailer. The store chain has experimented with prediction markets on everything from demand for digital set-top boxes to store-opening dates. For example, Mr. Severts said that in the fall of 2006, the prices in a prediction market on whether a new store in Shanghai would open on time — in December 2006 — dropped sharply from $80 a share into the $40 to $50 range. Players made yes-no bets, and the virtual dollar drop reflected increasing doubt that the store would open on time. Indeed, Best Buy’s first store in China opened late, in January 2007, but the warning signs from the prediction market helped prevent further slippage. Mr. Severts noted that prices in a current prediction market — betting whether new offerings from its Geek Squad service will be introduced on time in June — are in the $90 range, an encouraging sign. Best Buy plans to move beyond pilot projects in prediction markets to involve more workers throughout the company, starting next month. “It helps on two fronts, the speed and accuracy of information, so that management can move faster to deal with problems or exploit opportunities,” Mr. Severts said.

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Previously: Do Google’s enterprise prediction markets work?

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[...] Last year, for instance, the aggregate of small bettors who placed wagers on electoral results on TradeSports, a Web-based market, forecasted the outcome of every U.S. Senate race correctly. Companies like Best Buy, the electronics retailer, now maintain in-house markets where employees bet on how products will sell. The results help with pricing and inven­tory decisions. Wolfers says that companies have shifted to pre­diction markets because they work better than the traditional means for gathering data and making forecasts, such as sales meetings. [**] “Think of what a meeting is,” Wolfers says. “It’s some fat, obnoxious guy who talks for three minutes despite the fact that he knows nothing. In the meantime, there’s a woman who sits in the back and says nothing because she may feel her opinion isn’t taken into account. And then there’s the brown-noser, who wants to be senior VP and will say anything the boss wants to hear.” When you set up a prediction market in which employees bet actual cash, you weed out those who don’t know anything. As for the sycophant: if the boss isn’t watching, he’s more likely to bet what he really thinks. With a prediction market, everyone brings a small piece of information to the table, and the consensus [**] proves surprisingly accurate. [...]

[...] Zitzewitz says it was Wolfers’s idea to use an online prediction market to assess the economic impact of the war in Iraq, before the U.S. invaded. Up to that point, academics had only used predic­tion markets for retrospective insight into historical events. But in the Iraq study, which Zitzewitz and Wolfers wrote with Australian economist Andrew Leigh, the authors used markets to evaluate the cost of a policy before it was instituted—an approach that suggests such markets could be used to guide policy. They noted that prices of oil on futures mar­kets implied a belief that an oil price spike caused by war would dissipate after about 18 months, limiting the size of an “oil dividend.” This prediction, as it happens, has not been borne out by events—oil is still well above its pre-war prices. But analysts believe that today’s prices may be due to other factors that were not considered before the Iraq war, includ­ing the disruptions caused by Hurricane Katrina. [...]

[**] I wonder whether the word “consensus” is appropriate.

[...] a general agreement among the members of a given group or community, each of which exercises some discretion in decision making and follow-up action.

[*] As I wrote this morning, firms see their internal prediction markets as a strategic forecasting tool.