First, every market price is a prediction. Think of a familiar securities market such as a stock market. The price of a company’s stock is a forecast of the value of future dividend payments. A bond price is a forecast of the value of a defined set of interest payments, based on factors such as likelihood of default and future inflation. Second, markets generate forecasts in a very specific way – by aggregating and consolidating information from many individuals, often widely dispersed, each with access to small, idiosyncratic bits of relevant information.
This informational structure is very common in organizational life. Information within firms is often widely dispersed and undocumented, residing in the minds of employees. Junior level workers, for example, while perhaps knowing little about the overall set of strategic issues affecting their company, often have detailed understandings of isolated aspects of the business.
The fundamental challenges of corporate forecasting are to access and coordinate all relevant bits of information dispersed throughout a company and to consolidate them into a set of quantitative metrics that can be employed as forecasts.
But organizations impose significant constraints on the flow and processing of information. The hierarchy that defines organizational life often restricts the movement of information, from the bottom-up as well as across business units, and sometimes, because of various forms of “politics,” motivates the concealing of information or even the spreading of disinformation. When combined with well-documented effects such as human limitations in expressing complex thoughts and systematic biases in group decision-making, the result is that employees often do not reveal their honest assessments, sometimes because they’re not provided the opportunity and sometimes because they fear reprisal for offering an unpopular opinion. Forecast quality suffers.
Prediction markets offer firms the opportunity to incorporate the information aggregating and predictive power of markets within corporate structures relying primarily on top-down direction. A prediction market is established within a company to generate predictions on issues of interest to managers in a manner that directly addresses the foundational communication constraints within firms.
A “stock” is defined to reflect an issue of interest to managers, perhaps unit sales of a product over a specified future time period. A group of employees – perhaps salespeople and marketing personnel -are selected to participate as traders on the basis of their perceived understanding of future sales prospects. Using software that is commercially available and run as an internet (or intranet) application, the participating employees are provided trading accounts, the stock is assigned an initial value (perhaps reflecting management’s current expectation of sales in the defined period) and a currency is established to provide a medium for exchange.
With the protection of anonymity (eliminating the fear of reprisals for offering unpopular opinions) and a well-defined incentive structure, employees are motivated to acquire relevant information and contribute their best assessments. They buy and sell shares of the security based on their beliefs about future sales prospects and their desire to increase the value of their portfolio. When an employee, for example, observes that the price of the stock is less (or more) than his/her expectation of future sales, he/she will buy (or sell) the stock, thereby driving its price up (or down).
As a result of this dynamic, the stock price serves as an ongoing real-time forecast of future sales. It continuously reflects traders’ aggregated assessment of future sales of the product, in the same way that the trading of a company’s stock on a stock exchange continuously reflects the trading community’s collective assessment of the value of the company.
Several internet-based prediction markets have been functioning for many years, and many companies have implemented prediction markets internally. Performance comparisons reveal that such markets produce forecasts that are more accurate than those from traditional systems.
Prediction markets not only produce forecasts and assessments that are, on average, more accurate than those produced from traditional forecasting approaches at any point in time (because they incorporate more information and less disinformation), but also, because the markets function continuously, will reveal the impacts of new information far faster than any alternative approach. Because the usual disincentives for employees to reveal bad news to managers have been eliminated, this system can in some instances serve as an effective “early warning system.”
The informational content of a prediction market is not limited to the stock price. The underlying bid data can be examined for insights into the knowledge and the beliefs of specific employees and groups within the organization. Analysis of market transactions in prediction markets will identify areas where there is substantial disagreement among employees about future values of key parameters driving the firm’s strategic decisions. Such disagreement, reflecting a collective uncertainty about underlying factual premises and/or interpretations, will highlight areas where the incremental value of additional managerial attention, in the form of information gathering (including perhaps discussion with select employees) and/or analysis, will be particularly high.
There are additional benefits of prediction markets – such as improved decision-making on personnel issues and improved employee morale – that can be realized with the most force when the markets are employed for long time horizons.
Thanks to David Perry of Consensus Point for allowing me to republish this explainer.