When executives at electronics retailer Best Buy Co. want to know if a new product or idea is likely to succeed, they can seek the opinion of rank-and-file employees by turning to the company’s “prediction market.”

The market, called TagTrade, allows Best Buy’s workers to trade imaginary stocks based on answers to managers’ questions. The market’s judgment has often proved to be more accurate than the company’s official forecasts.

TagTrade is open to all of Best Buy’s 115,000 U.S. employees. The roughly 2,100 of them who choose to participate get $1 million in fake money to trade for a nine-month period. The top trader in the period wins a $200 gift certificate.

Jeff Severts, a 38-year-old executive who is currently chief of the company’s Geek Squad personal-computer maintenance services, spearheaded development of the market. Mr. Severts says TagTrade helps flag potential problems early.

In January, he asked both his management team and the market to predict sales of a new service package the company was offering for laptop computers. A week before the company began selling the product, the market’s guess was 33% lower than the team’s official sales forecast. It subsequently sank further.

When initial sales figures confirmed the market’s prediction, Mr. Severts ended the offer and began redesigning the service package. He listed a TagTrade stock to gauge the revised package’s chances of starting on time, in mid-September. The stock rose, and Mr. Severts says he took “great comfort from that.” On Sunday, Best Buy started offering the new package.

Best Buy isn’t the only company using prediction markets as a way to tap the knowledge of front-line employees. Web-search giant Google Inc. uses them to solicit forecasts on everything from how many users its Gmail service will attract to whether products will launch on time. Other companies that have experimented with them include General Electric Co., Intel Corp. and Microsoft Corp.

Best Buy’s chief executive, Bradbury Anderson, encourages experiments like TagTrade that seek to drive decision-making down the corporate ladder and information up toward the top.

Last year, two marketing employees, working on their own, created an internal electronic bulletin board called Blue Shirt Nation, a reference to the trademark garb of the retailer’s sales force. The bulletin board’s 24,000 users post questions for co-workers, comments on work policies and personal videos.

Tim Sheehan, a senior vice president, watched the bulletin board closely after Best Buy decided to reduce its employee discount last year. Mr. Sheehan, who had participated in the decision, emailed fellow executives, quoting some of the fiery reactions that were posted on the site; the company reinstated the larger discount within days.

Mr. Sheehan now scans Blue Shirt Nation daily. In November, he helped start another site that lets employees with business ideas seek help and funding from elsewhere in the company, bypassing the normal chain of command.

Mr. Anderson, the CEO, says narrowing the gap between management and workers helps to make his Richfield, Minn.-based company more nimble and responsive to customers, while boosting sales and profits. Monday, Best Buy agreed to buy music service Napster for $121 million in what it said was a bid to reach new business.

To encourage more open lines of communication, Mr. Anderson, who says he remembers how distant corporate headquarters felt when he was a Best Buy clerk in the 1970s, invites management gurus like James Surowiecki, author of “The Wisdom of Crowds,” to address his employees.

Inspired by Mr. Surowiecki’s thesis that a crowd, collectively, can make better decisions than individuals — even experts — Mr. Severts decided three years ago to test whether Best Buy’s workers could outperform its bosses.

At the time, Mr. Severts was a marketing executive looking for ways to improve the accuracy of Best Buy’s sales forecasts. He emailed hundreds of Best Buy employees asking them to guess how many gift cards the electronics retailer would sell in February 2005.

As a group, the employees’ guess was more accurate than Best Buy’s official projection. But, Mr. Severts recalls, the forecasting director for gift-card sales said her team felt humiliated.

As a result, Mr. Severts says he learned to keep his experiments from seeming like personal attacks on the competence of his fellow managers. He explains his work at employee gatherings, using PowerPoint presentations that compare Best Buy to a centrally planned economy like the Soviet Union and feature portraits of Joseph Stalin and Mao Zedong. Those leaders, like many managers in big companies, were prone to bad decisions because they were too far from the front lines, Mr. Severts says.

In 2006, armed with Mr. Anderson’s support, a $50,000 budget and some volunteers, Mr. Severts widened his experiment to include a prediction market.

To spark interest in trading, Mr. Severts listed stocks on political contests and DVD sales; one asked how often Mr. Anderson, the CEO, would use the expression “lifestyle groups” during a conference call.

Mr. Severts moved slowly, wary of ruffling more feathers or forcing his ideas on skeptical managers. Seeking more credibility for his results, he enlisted researchers from the University of Chicago to study how market guesses compared with official forecasts. He hopes to get the results later this year.

Other Best Buy managers have started floating stocks. Earlier this year, Rob Rausch, a senior manager two levels below Mr. Severts, created a stock to gauge the likely reaction to a price increase for PC maintenance services. Managers of Best Buy’s private-label business floated a stock to help predict sales of a new digital-TV converter box.

Despite Mr. Anderson’s encouragement, employees say most of Best Buy’s management innovation still emerges from isolated pockets of the company, and depends on the benevolence of bosses who permit work on pet projects.

Mr. Severts says he is glad Mr. Anderson doesn’t force reluctant managers to change their ways. “Nothing would squeeze the life out of TagTrade faster than putting it at the top of a priority list,” he says.

One of Mr. Severts’s latest stocks asked if Best Buy’s information-technology department would finish a planned systems upgrade by mid-September. The market correctly forecast that the department would miss its deadline, but Mr. Severts noticed a glitch: most of the tech work was done by employees of consulting firm Accenture Ltd., who didn’t have access to TagTrade. He proposed opening the market to them as well; Accenture managers say they are interested in participating.

Copyright 2008 Dow Jones & Company, Inc.

What if your boss, rather than dismissing you off hand when you suggested a different way of doing something, let you bet on the fact that your idea was better. And paid you if you were right.

That is the premise of prediction markets – a tool companies are increasingly using to make better decisions by allowing employees to trade in a mock stock market based on information they have about the business.

They work a little like a futures market. Say a company wants to release a new product but is unsure whether a launch date can be achieved. It creates a market for a prediction that the product will launch in a given month. Employees are then given a fixed amount of a mock currency they then use to trade contracts in that future.

Those who think it is likely the product will launch in that month will buy the future, and the price goes up. Those who don’t, sell, sending the price down.

At the end of the trading period, the value of the contracts that have been bought and sold are tallied, and those traders who have been most successful are given cash prizes or bonuses.

The company benefits since the final ‘price’ reflects a broadly based forecast of the likelihood that a given launch date can be achieved.

Several large American firms – including Google, GE, Hewlett-Packard, and Best Buy – have begun using prediction markets to help make assessments about all kinds of projections, including how customer numbers will grow, what demand will be for a product, and when it will launch.

Companies can also set up more complex trading systems which allow employees not only to trade in a given prediction but also to make their own estimates of when they think a product will launch, say, and trade contracts in that future.

Two recent reports – by McKinsey, the management consultancy, and Forrester, the analyst – have suggested that such markets are likely to grow in importance, particularly as the technology which facilitates them becomes cheaper and more widespread.

The advantages, exponents say, are many: the trading system gives employees an incentive to share information they have that may be valuable: although the currency is artificial, the cash rewards are real.

A market also aggregates knowledge more efficiently, as employees can – in effect – give feedback to their boss by trading more or less aggressively on information they have. The social and cultural issues which may have prevented an employee from sharing information are also, in theory, swept aside, because all trades are anonymous.

Companies that have used prediction markets say they provide more accurate information about aspects of their business than could be learnt by more traditional methods, such as polling employees or consulting outside experts.

In one instance, a malfunction in the furnace of a chip manufacturer led employees at the factory to update their positions on future yield more quickly than could employees elsewhere.

Google, the search giant, has been using such markets since 2005 to estimate – among other things – traffic volumes, and when its international offices will open.

About 1,500 employees will trade at any one time, and each has 10,000 ‘Goobles’ – a mock currency – to play with per quarter. The Goobles are issued weekly, “otherwise people would lock up their positions early and there’d be liquidity issues,” Bo Cowgill, an economic analyst at Google, said.

The markets run for anywhere between two weeks and three months. When they close, successful traders are given cash prizes and specially branded T-shirts which, Mr Cowgill said, end up being a greater incentive than the money.

At GE, the healthcare to aviation and media conglomerate, about 40 to 50 predictions – typically about the types of new technologies the company should invest in – are traded at any one time by up to 10,000 of its 330,000 employees.

“We use them as another point in the decision-making process, alongside asking experts and other business leaders,” said Christina LaComb, a computer scientist in the R&D lab at GE.

The window displaying the live trading system sits on the desktop of the employee’s PC. The employee sees the current asking price for any contract and its trading history, and there are simple buttons for buy and sell.

One problem is the inherent biases of such markets, which can make the information they provide less useful.

“The first is a long-shot bias – people tend to overesimate the likelihood of a long-shot paying off, so they tend to overpay to make that bet; conversely they tend to underpay for a sure thing,” said Jeff Severts, a VP of services at the US electronics giant Best Buy, which has used prediction markets for two years.

“The second bias is a home-team bias: employees have been overpaying for ’stocks’ that are based on outcomes that would be good for Best Buy, but we believe we can mitigate the biases through continued refinement of the market.”

The US Commodity Future Trading Commission is also examining prediction markets from a regulatory point of view, and companies which use them have steered away from running markets which predict financial results.

“If we ended up with an application that did an amazingly good job or predicting our results, there would be a concern that anyone who saw it would be an insider,” said Mr Cowgill.

Todd Henderson, an assistant professor at University of Chicago Law School who has written about prediction markets, said that, assuming prediction markets were approved by regulators, the case for using them was compelling, and that the “real puzzle” was why every firm didn’t.

“Companies are the members of society most comfortable with markets as processors of information, and yet when it comes to decision-making, they display these socialist ‘command and control’-style tactics to make them,” he said. “Twenty years from now, prediction markets will be ubiquitous.”

Companies pay anywhere from $25,000 to upwards of a $1 million to run a market, according to David Perry, president of Consensus Point, a business which implements web-based internal trading systems.