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Using Prediction Markets in Business

Data aggregation and analysis have become an integral part of business. Decision makers within companies rely on the vast amounts of data that are collected across all aspects of the company to drive growth and profitability. However, because it takes time for the data to be collected and analyzed before it can be acted upon, any decisions made from the analysis are already outdated. In order to overcome this problem, companies are turning to prediction markets to provide accurate forecasts of future events so that decisions can be made before the events even occur.

Google is one company that currently relies on prediction markets to drive its decision making. Employees of Google bid on the likelihood of events that affect the company (product launch dates, office openings, etc.), and Google uses the information gathered from these markets and plans as if the markets are correct. In this process, Google has found prediction markets to be a highly accurate way to forecast events (in other words, the consensus price of the prediction market is close to the probability that the event occurred). The aggregation of knowledge and opinions from across the company into an accurate prediction allows Google to make decisions based on future data.

The BRAIN project at HP is project to use prediction markets to forecast company data (revenue, production numbers, etc.) in a way that removes reporting bias. Unlike Google, HP plans to market the BRAIN project as a tool that companies can purchase and use. Participants in a prediction market run by the BRAIN process can place bets from their finite pool of betting tokens on the possibility that various outcomes might occur. The information is then aggregated to form a consensus. HP currently uses these techniques in several business units.

By using prediction markets, Google and HP are bringing to business a powerful tool already harnessed ubiquitously by sites on the web: the wisdom of crowds. Just as Wikipedia uses the general population to build a complete and accurate encyclopedia, businesses can use stakeholders and prediction markets to build an accurate model of the future of the business. This approach, combined with data mining and experimentation, are part of the current fundamental shift in business from expertise and intuition based decision making to scientific and data driven decision making.


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