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Eight pitfalls of predictive markets

Predictive markets sound like such a great idea for determining what will work in the market and what won't. But misplaced trust in these markets can spell gloom and doom for many an organization.
Written by Dave Greenfield, Contributor

Predictive markets sound like such a great idea for determining what will work in the market and what won't. But misplaced trust in these markets can spell gloom and doom for many an organization. Here then are eight problems you’ll want to avoid as spelled out by Google and Best Buy and others in a recent roundtable run by McKinsey & Company.

1. Garbage-in-Garbage-Out - Predictive markets aren’t magic. By their very nature it depends on the quality and quantity of participation. Even smart individuals with in sufficient access to the right data will make poor predictions.

2. Lack of participation – Predictive market initiatives require rich involvement on the part of informed, diverse individuals. More important than lacking the number of people are not providing individuals with the access to available information needed for making informed decisions about their investments

3. Watch the optimism – Positive news and feelings tended to drive outcomes higher. Google found that new employees, for example, who were more optimistic about the company or when the stock performed well traders tended to result in people betting that good things would happen to Google, says Bo Cowgill, product manager at Google who has managed the company’s prediction markets for two and a half years.

4. Avoid extreme events. Google noticed that its traders undervalued extreme events, whether they were good or bad. When Google posed contracts with multiple outcomes, such as forecasts about the number of Gmail users, —the highest and the lowest outcome happened more often than the market expected.

5. The water cooler effect. Google found that that beliefs tend to cluster together. Individuals who sat and worked alongside one another, down to feet and meters from one another, tended to bet in similar ways. Geography was more important than work relationships, socializing outside of work, and language.

6. Watch the enemy - Best Buy found that employees tended to underestimate the competition or to think they knew more about them than they actually did. “Our prediction markets have not had a very respectable accuracy on anything related to our main competitor,” says Jeff Severts the vice president and general manager of Geek Squad, the services arm of Besty Buy, the US consumer electronics retailer

7. Air cover is key –Corporations need to be willing that an important initiative may fail. Too often, that’s not the case, which calls for senior executive sponsorship. “Air cover is key or you’ll find yourself trading on what kind of casserole we’re having in the cafeteria on Thursday,” says Severts.

8. Legal Trouble –  Predictive markets deployment broaden the accessibility to sensitive information. How the Security and Exchange Commission (SEC)  will view that matter is anybody’s guess. “Take the employee who sees a prediction market price on her dashboard and realizes, with some degree of confidence, that a certain drug is going to be a success,” says Todd Henderson, an assistant professor at the University of Chicago Law School, ”Is it illegal if she trades on this information in the real stock market? Is she an insider because she now has information that only a few top people had before? What kind of disclosure obligations does that put on a US public company? Gambling laws are another issue. Should prediction markets be viewed as an unregulated form of betting? These are enormous question marks for US public companies."

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