It seems as if most of today’s business articles start out something like this: “The business executive faces ever greater challenges when making decisions because uncertainty keeps increasing. The shape of the future becomes less predictable, thanks to accelerating technological change, globalization, and finicky customers.” Given the universal recognition of the challenges posed by uncertainty for forecasting – and the decisions informed by forecasts – it would seem natural for companies to rapidly adopt any method that has proved effective at penetrating the unknown to return with relatively reliable forecasts. Decision markets (or idea futures markets) are just such a method. Yet, as James Suroweicki wrote in The Wisdom of Crowds, “the most mystifying thing about decision markets is how little interest corporate America has shown in them.”

I’ve been following the progress of decision markets for over ten years, ever since one of the original architects of the idea, Robin Hanson, explained his proposal for what he called “idea futures.” The results of numerous experiments and real world implementations have been remarkably promising. The Iowa Electronic Markets have consistently outpredicted polls and political forecasting experts, with an average margin of error of 1.5 percentage points; Hewlett-Packard used decision markets that enabled account executives to trade in sales projections to forecast printer sales – the markets beat the company’s traditional forecasting methods over and over again; and the Hollywood Stock Exchange has excelled at forecasting box-office takes by new movies. Despite these persistent and consistent success stories, hardly any companies are even experimenting with decision markets.

Decision markets work because they create incentives for widely dispersed people to reveal information about which they feel confident; they leverage the knowledge of many diverse and independent minds; they decentralize the forecasting process, balancing out mistakes; they bypass hierarchical restrictions on knowledge flow; and they aggregate all those opinions efficiently.

Not only are decision markets the most reliable forecasting tool available in many situations, they have a wide variety of uses. As Thomas Malone showed in his article, “Bringing the Market Inside”, they can be used for internal selling, trading ideas, allocating assets, and trading knowledge. Eli Lilly’s Innocentive offshoot has even used experimental decision markets for employees to forecast which drug candidates were likely to be approved and which rejected by the FDA. Using realistic profiles and data for six drugs whose fate was known to the company, the market rapidly zeroed in on the winners, pushing up their prices, while the prices of the losers plummeted.

One likely reason for the lack of adoption of information, prediction or decision markets is executives’ fear that decision markets will take away their ability to set strategy and make choices. Even if that were going to happen, boards of directors should be pushing for these markets anyway. Executives need not worry, however, since they can use decisions markets to inform major decisions, rather than to make those decisions for them. Other companies may not have tried this potentially profitable forecasting and decision tool due to lack of knowledge. They will find plenty of information in the articles and books related to this commentary. Ajit Kambil, for instance, suggests three steps for implementing decision markets in “You Can Bet on Idea Markets”, while Malone and others point out the limitations and potential downsides.