Every senior executive knows that business decisions are seldom better than the information behind them. Yet although it is usually lower-level employees who interact directly with the customer, decision makers rarely ask them how, for example, new products will fare. Leaders therefore deprive themselves of information that could enrich their analysis and reduce the risk of ivory tower decision making.
Some executives understand that valuable information lies scattered around the organization but don’t know how to retrieve it. Others don’t even try, perhaps for hierarchical reasons or because they suspect they might get answers colored by the desire to second their real or assumed viewpoint.
Prediction markets might solve these problems. Initially a field of research, true prediction markets in essence are small-scale electronic markets, frequently open to any employee, that tie payoffs to measurable future events, such as sales data for a computer workstation, the number of bugs in an application, or a product’s usage patterns.1 Some companies, particularly in the high-tech sector, have adopted them in earnest, and a few major companies elsewhere are experimenting with them.
These markets yield prices on prediction contracts—prices that can be interpreted as market-aggregated forecasts. Their “collective wisdom” is usually at least as accurate as expert opinion. Proponents say that prediction markets work by rapidly aggregating information dispersed across an organization while freeing participants from constraints: for instance, employees can share unwelcome information about a project’s launch date or a new product’s performance anonymously, without fear their careers might suffer. What’s more, advocates say, competition among colleagues and the prospect of winning a prize create incentives for seeking information and making the best-informed bets.
To assess the potential of prediction markets and the organizational and legal challenges they must surmount to become a more widely used business tool, a roundtable was convened at a recent McKinsey conference in Dubai. The panelists were Bo Cowgill, who manages Google’s prediction markets; Todd Henderson, an assistant professor at the University of Chicago Law School; Jeff Severts, general manager of Geek Squad, the services arm of US electronics retailer Best Buy; and James Surowiecki, author of The Wisdom of Crowds, a book about prediction markets and other forms of collective intelligence. Renée Dye, a consultant based in McKinsey’s Atlanta office, moderated the discussion. What follows is an edited and abridged version of it.


