Consensus Point releases enhancements to the leading Forecast, Strategy and Project
Prediction Market allowing Executives to Accelerate Decisions

Nashville, TN (August 22, 2009) – Consensus Point LLC, a leading provider of prediction market software and services, announces the release of the 6th generation platform of the Foresight On-Demand software as a service (SaaS) Solution.  Based on customer feedback, Release 6 includes many new features to improve the administration and user interfaces, such as additional reports, group and category capabilities, enhanced idea and prediction descriptors, graphic images, and rich text editing.  These enhancements increase the breadth of early warning and leading indicators to improve forecasts, strategic decisions, and critical initiatives. 

Brian Jaedike, manager of prediction markets at Best Buy who participated in requirements and quality assurance testing, said “Version 6 of the Admin tool saves me time and allows me even more flexibility to add and edit stocks and traders.  The participants like the user experience and professional interface of the main site because it makes them feel they are part of an actual exchange.” 

“Our customers now have the most advanced interfaces to efficiently and effectively use and manage their prediction market with the release of the sixth generation of our Foresight Solution”, commented Brad Wilson, VP, Services and Customer Support, Consensus Point.  “Our comprehensive and proven solution, including the Consensus Point Foresight software, services and support, allow organizations to rapidly launch and realize the significant benefits of an idea or prediction market.”

About Consensus Point

Consensus Point, a Nashville, Tennessee company, is the leading provider of enterprise prediction and idea markets serving corporations and government.  With over 15 years of experience providing prediction markets, Consensus Point offers a comprehensive collective intelligence solution, including Software as a Service (SaaS) with on-demand or on-site licenses, consulting services, and support. The company helps customers increase innovation, reduce the risk of uncertainty, improve revenue insight through accurate forecasts of products and services, and manage projects with a dynamic pulse into future completion dates and budgets.

Thesis on the effectiveness of Prediction Markets as a forecasting tool 

by Kai Trepte and Rajaram Narayanaswamy
Graduate students in the Engineering Systems Division at the Massachusetts Institute of Technology

Graduate students in the Engineering Systems Division at the Massachusetts Institute of Technology studied 20 Prediction Markets at General Mills, powered by Consensus Point, in order to determine the accuracy of Prediction Markets as a forecasting tool in a corporate setting.  According to the study, “Our findings clearly show that Prediction Markets are capable of developing very accurate forecasts, effectively aggregate information from multiple participants and may be able to provide improvement for long-range forecasting.”

Click here to read the full thesis.

Paper courtesy of Harvard’s Program for Evolutionary Dynamics

by Johan Almenberg, Ken Kittlitz and Thomas Pfeiffer

Abstract
Prediction markets are powerful forecasting tools. They have the potential to aggregate private information, to generate and disseminate a consensus among the market participants, and to provide incentives for information acquisition. These market functionalities can be very valuable for scientific research. Here, we report an experiment that examines the compatibility of prediction markets with the current practice of scientific publication. We investigated three settings. In the first setting, different pieces of information were disclosed to the public during the experiment. In the second setting, participants received private information. In the third setting, each piece of information was private at first, but was subsequently disclosed to the public. An automated, subsidizing market maker provided additional incentives for trading and mitigated liquidity problems. We find that the third setting combines the advantages of the first and second settings. Market performance was as good as in the setting with public information, and better than in the setting with private information. In contrast to the first setting, participants could benefit from information advantages. Thus the publication of information does not detract from the functionality of prediction markets. We conclude that for integrating prediction markets into the practice of scientific research it is of advantage to use subsidizing market makers, and to keep markets aligned with current publication practice.

Click here to download the full version of the paper.

Prediction Market Reveals Answer Well Ahead of Results

April 28, 2009 – Ingenix.com - Ingenix Thought Leadership – When trying to determine whether a product is priced right, a project will launch on schedule or the impact proposed health reforms will have, health care entities are considering a methodology that relies less on expert opinions and more on the intelligence of hundreds of people with diverse vantage points.

To determine the results of a key question – what will the employee engagement index be? — on an employee survey, Ingenix used the Prediction Market to gauge the outcome well in advance of the survey results being published. Within one day, the Prediction Market accurately forecasted the index.  Prediction markets provides Ingenix’s clients with early and accurate quantitative data points on future events.

This methodology, known as “collective intelligence,” uses a “prediction market” to “unleash the collective wisdom of organizations and helps them gain a more accurate picture of what is going on in their organization and the industry,” according to Ron Hoffner, associate, Ingenix Consulting.

Prediction markets, defined in a recent BusinessWeek article as “bets on ideas,” ask groups of stakeholders the following question: “What do you think something is worth, and more important, what will it be worth tomorrow?”¹ The groups’ answers have proven to be accurate most of the time, the article goes on to say. “When groups of people bet on something, their combined intelligence is often remarkably prescient.”²

Hoffner agrees. “There is an old Japanese proverb that states ‘None of us is as smart as all of us,’ and we are finding more and more that this is true,” he said. Recent academic research has shown that using a market to forecast demand results in a significant improvement in forecast accuracy when compared to traditional methods.³ The result, Ingenix believes, is that health care programs can better predict which programs are the most likely to succeed.

Another area where prediction markets can add significant value is providing quantitative data on the impact proposed health reforms will have on the industry. “What we are doing is asking a variety of people with different perspectives – who traditionally have not been included in the discussion – for their input,” Hoffner said, “For really the first time, we are going to have quantitative data on the impact of these proposed health reforms that participating organizations can use for planning.”  

Prediction markets harness viewpoints, intelligence

One of the flaws of traditional forecasting is that it generally relies on historical data to make predictions about upcoming events and results. Many years ago, a wise man once said, “You can never plan the future by the past.”⁴ Indeed, Hoffner asserted, using historical data to determine the future assumes that the environment stays the same. However, the health care environment is rapidly changing and traditional methods that use historical data do not account for these changes. The result is forecasts with greater uncertainty.

“To illustrate this point,” Hoffner said, “let’s assume historical data shows two variables are related, such as gas prices and sports utility vehicle (SUV) sales. When gas prices go up, the sales of SUVs go down; conversely, when gas prices go down, SUV sales should pick up. However, they haven’t, so the forecast of SUV sales ended up being higher than the actual SUV sales results. It is clear that how variables are related in the future can change.” These changes can come from a variety of sources, such as social changes or government regulations, he explained.

Prediction markets also may be more reliable because they aggregate and consolidate data “from many individuals, often widely dispersed, each with access to small, idiosyncratic bits of relevant information.”⁵ In a prediction market, companies ask stakeholders from across the spectrum to voice their opinions about future events and milestones by buying “stock” or using points to register their “vote,” according to Hoffner.

“Let’s say a company wants to determine how many people will sign up for their four health plans and if a new wellness program will decrease absenteeism. This is their prediction market. They give stakeholders points to assign to the different questions in the market based on their own views,” he said. “If they have a lot of confidence in the issue, they will assign more points to their answer, so instead of just a  ‘yes’ or ‘no’  answer from a survey where everyone has equal influence, people with more confidence in their view have more influence by assigning more points in the market.” 

Another improvement prediction markets offer over traditional surveys is that participants are rewarded for being right. The result of answering a question right is the participant earning points. At the end of a quarter, for example, those with the highest number of points would receive an award. This results in participants seeking information on programs, which leads to increased awareness of them. 

Further, because the information derived from these diverse sources is contributed on an anonymous basis, the data collected also may be more truthful than if solicited in person. A lower-level employee with relevant exposure to an issue being carefully tracked by the company likely would not feel comfortable telling – or even be invited to tell — his or her boss’ boss about existing problems that might affect forecasts. However, that employee likely would honestly report an experience-based lack of confidence in meeting a future target date in the prediction markets setting.

“Prediction market data fills a lot of information holes, especially when there are many unknown variables, because the diversity of ‘players’ leads to different views and different perspectives that can help reduce uncertainty,” Hoffner suggested. “It lets management know how confident people are in a given forecast while still retaining control over the final decision.”

Expanding use, value of prediction markets

Ingenix believes that prediction markets can help health care entities bridge data gaps so they can “see more and do more,” Hoffner said, so it has forged an exclusive partnership with prediction market pioneer Consensus Point to offer prediction market services to Ingenix clients. These clients either pose questions to an Ingenix prediction market or consult with Ingenix experts to build or improve a prediction market of their own.

“Although collective intelligence is not new, today we are taking that intelligence to the next level, where more value can be derived from it,” Hoffner explained. Ingenix Prediction Markets will combine prospective data from employers, brokers, consultants, providers, payers and academics with longitudinal data from Ingenix’s repositories of patient claims and consumer surveys to provide industry-leading market forecasts of how trends, such as health care reform efforts, will impact the health care industry.”

Prediction markets give Ingenix “the ability to let our clients know what’s out there and what’s coming down the road – in a way that is more accurate than any other trends method – so they can better manage their business,” Hoffner concluded. “Our approach to prediction markets is that Ingenix is providing clients with real-time focus groups that we are calling a ‘living leadership forum.’ Any changes in the views of the group and the marketplace are quickly detected, which means businesses are rarely caught off guard.”

¹ Kunz, Ben, “Prediction Markets Meet Wall Street,” BusinessWeek (Oct. 14, 2008)
² Id.
³Consensus Point
⁴ Burke, Edmund (1729-1797).
⁵ Consensus Point, “What is a Prediction Market?” (Web site accessed April 1, 2009). ,” uses a “prediction market” to “unleash the collective wisdom of organizations and helps them gain a more accurate picture of what is going on in their organization and the industry,” according to Ron Hoffner, associate, Ingenix Consulting.

 License Agreement Provides Access to Successful GE Imagination Market, Comprehensive Innovation Management Process 

Nashville, TN – Consensus Point LLC, a leading provider of prediction market software and services announced the addition of Rebecca Whitehead Munn to the leadership team and a license agreement with General Electric (“GE”).   Through the GE relationship, Consensus Point customers can have access to the proven GE Imagination Market process and benefit by identifying the most promising ideas for business growth.  GE’s Imagination Markets help answer tough business questions such as “what new technology ideas should we be investing in” and “what new products should we develop”. Market participants can submit their own ideas for entry into the market, and they can buy and sell shares of any idea in the market based on how well they believe the idea will contribute to the market’s objectives. At the end of the market, the business leader has a rank-ordered list of ideas.

GE has implemented the Consensus Point solution for idea management in over 10 GE businesses since 2006. The GE Imagination Market has uncovered innovative ideas based upon a variety of business-designated criteria. By licensing and integrating the GE “Imagination Market” technology process, Consensus Point provides a proven, comprehensive design and solution leveraging the prediction market expertise of Consensus Point and the business innovation leadership of GE.  In the recent GE-wide Imagination Market, over 1,400 employees from 170 business segments representing 42 countries suggested over 220 business model innovation ideas. GE Imagination Markets provide a fun way to engage people globally in new idea generation and result in an abundance of relevant ideas that can aid in setting future strategic directions.

Rebecca Munn joined the Consensus Point team as Senior Vice President of Sales. She brings over 22 years of proven experience in strategic planning, sales and marketing leadership, business unit operations, and services delivery. At Consensus Point, Ms. Munn is leading sales, sales operations, marketing, and customer relationships. She has held leadership positions with several global service and technology companies, most recently as the Vice President of Sales Operations of Healthways.  Ms. Munn also held several leadership roles at Cisco Systems, including the former Director of the Services Division, Connected Health Vertical, and principal in the Internet Business Solutions Group. She was the co-founder of The Arbora Group, a retail and wholesale operations start-up, in 2001. Ms. Munn is a former board member of the Nashville Technology Council. She earned an executive MBA from the University of Colorado and a BBA in marketing from the University of Texas at Austin.

“Our customers now have access to GE’s global experience in innovation management and proven design for the Imagination Market, commented Linda Rebrovick, CEO, Consensus Point.  “This fully integrated solution, including the Consensus Point Foresight software and GE Imagination Market process, allows organizations to rapidly launch and realize the significant benefits of an idea and innovation market. Some of our customers have cut the time to process ideas in half through using idea markets. In addition to the GE partnership, we are pleased to announce the continued growth of our company with the addition of Rebecca Munn to our leadership team.” 

Employees use prediction markets to vote up product ideas and productivity improvements they think should be selected for development

April 27, 2009 — CIO.com — The project: Deploy a prediction market to aggregate new business ideas suggested by Motorola employees and assess their viability. A prediction market is a system for forecasting the outcome of projects or events based on how willing individuals are to buy “stock” in them. Users buy shares to vote items up. Each item is evaluated based on how much it is “worth”: the higher the value, the more popular the idea.

The business case: Motorola sought to allow any employee the opportunity to propose ideas for new products, upgrades to current products, productivity improvements or cycle-time reductions, says Rami Levy, distinguished member of Motorola’s technical staff and a member of its open-source technology team, which manages the prediction markets for the company. In 2003, Motorola had built a system to collect ideas, called ThinkTank. But when thousands of suggestions poured in, the teams that were supposed to weed through them were overwhelmed.

Using prediction market technology, Motorola could engage employees in the selection process by letting them vote for the ideas they thought had the best business potential. The most popular ideas could then be selected for further study and eventually be developed.

First steps: Levy and his team worked with a variety of director-level managers, including senior VPs, to secure buy-in for the project. “ThinkTank was already being sponsored by an SVP,” he says, but they needed support from others who would have to produce the business-case and user scenarios for new product ideas. That sponsorship was crucial to obtaining cross-organizational participation and funding for the tool.

Once Levy’s team secured management support, they integrated prediction software from Consensus Point (called ThinkTank Idea eXchange, or TIX, internally), with its existing ThinkTank application. In a six-month pilot during 2007, they experimented with market parameters, such as how long to keep ideas in play and how to finance participants’ purchases.

Today, employees submit ideas to ThinkTank, where anyone within Motorola can vote on them. Ideas that receive at least five votes are eligible for TIX, where each idea is initially valued at $10 per share. Anyone who wants to participate gets $100,000 to start with to buy the stock of the ideas they like best. As employees buy or sell shares, the value of the idea rises—or not. After 30 days, an idea review team determines which of the top-valued ideas to pursue. Winners are judged based on their stock performance, and participants who hold stock in winning ideas get a bonus.

It typically takes 18 months to develop a product at Motorola, so the first product ideas vetted through TIX are expected to come to market this year, Levy says.

What to watch out for: Market parameters that work in one circumstance won’t necessarily work in another, says Levy. You have to fine-tune your system to your environment. Motorola decided to limit an idea to a month in TIX to ensure new ideas were always entering the market. Meanwhile, even though employees find participating fun, you need to get them involved and keep them engaged. Levy’s team ran ads on the company’s intranet, conducted user satisfaction surveys and incorporated social media into the system. “Socialize the experience,” he recommends, “by integrating user comments, tagging, recommendations and links to other information.”

By Kristin Burnham © 2008 CXO Media Inc.

Ben Kunz just published a BusinessWeek article with several interesting insights about how the Dow Jones industrial average signaled the recent market turmoil - very much like how a prediction market aggregates intelligence about future events.

How did Wall Street know what would happen? It acted like a prediction market, a pool of intelligence that can foresee the future. Prediction markets are simply bets on ideas: What do you think something is worth, and more important, what will it be worth tomorrow? When groups of people bet on something, their combined intelligence is often remarkably prescient.

As you may know, this is something that James Surowiecki discusses extensively in his book, The Wisdom of Crowds.  Ben also talked with Robin Hanson about why the traditional prediction methodologies fail:

The trouble with humans, it seems, is that even when we’re smart, we have access to imperfect information and follow the groupthink of our peers. Because we often disagree with other groups, we band together and end up agreeing too much with our own teams. No single leader can overcome such biases and data gaps to predict with certainty whether an action will succeed or fail. But Hanson suggests markets can do just that.

(Ben Kunz is director of strategic planning at Mediassociates, a media planning and internet strategy firm. He is author of the advertising strategy blog.)

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.

CORPORATIONS live and die by ideas, and many enterprises have used Web-based technologies, like blogs, wikis and social networks, to gather thoughts and hasten their way into new services, products and cost-saving steps.

Now executives say they are harnessing a new Web tool, called prediction markets, to transform the idea pipelines inside their companies. Companies like the InterContinental Hotels Group, General Electric and Hewlett-Packard are using prediction markets to try to improve forecasting, reduce risk and accelerate innovation by tapping into the collective wisdom of the work force.

Like blogs and wikis, prediction markets can spur communication and collaboration within a company. Yet they add rigorous measurement to business forecasts, like estimating the sales of a new product or the chances that a project will be finished on time.

Corporate prediction markets work like this: Employees, and potentially outsiders, make their wagers over the Internet using virtual currency, betting anonymously. They bet on what they think will actually happen, not what they hope will happen or what the boss wants. The payoff for the most accurate players is typically a modest prize, cash or an iPod.

The early results are encouraging. “The potential is that prediction markets may be the thing that enables a big company to act more like a small, nimble company again,” said Jeffrey Severts, a vice president who oversees prediction markets at Best Buy, the electronics retailer.

The store chain has experimented with prediction markets on everything from demand for digital set-top boxes to store-opening dates. For example, Mr. Severts said that in the fall of 2006, the prices in a prediction market on whether a new store in Shanghai would open on time — in December 2006 — dropped sharply from $80 a share into the $40 to $50 range. Players made yes-no bets, and the virtual dollar drop reflected increasing doubt that the store would open on time.

Indeed, Best Buy’s first store in China opened late, in January 2007, but the warning signs from the prediction market helped prevent further slippage.

Mr. Severts noted that prices in a current prediction market — betting whether new offerings from its Geek Squad service will be introduced on time in June — are in the $90 range, an encouraging sign.

Best Buy plans to move beyond pilot projects in prediction markets to involve more workers throughout the company, starting next month. “It helps on two fronts, the speed and accuracy of information, so that management can move faster to deal with problems or exploit opportunities,” Mr. Severts said.

For years, public prediction markets have been used for politics, like the Iowa Electronic Markets and Intrade, where buyers and sellers bet on which candidate will win a particular race. And there are prediction markets where people place bets on news events (Hubdub, among others), video game sales (simExchange) or movie box-office receipts (Hollywood Stock Exchange).

These markets have often been more accurate than professional pollsters or market researchers. The idea is that the collected knowledge of many people, each with a different perspective, will almost surely be more accurate than an individual or small group or even experts. The concept has been championed by academic economists and was popularized by James Surowiecki’s 2004 book “The Wisdom of Crowds.”

Robin D. Hanson, an economist at George Mason University, proposes a “futarchy,” a form of government enhanced by prediction markets. Voters would decide broad goals of national welfare, but betting in speculative markets would determine the policy steps to achieve those goals.

Few in the corporate world go that far. An important issue is whether prediction markets are mainly an innovative way to gather information from employees or a font of reliable answers. “It’s still an open question whether the wisdom of crowds is really wise,” said John Kao, a consultant and the author of “Innovation Nation.”

So far, most of the companies using prediction markets are doing so in limited ways, in one or two departments, testing the concept to see how it goes. But in the last few years, corporate experimentation has moved beyond high-tech businesses into other industries, including retailing, consumer packaged foods, hotels, health care, steelmaking and telecommunications.

Today, analysts say, there are dozens of major corporations testing these markets. The companies include Google, Cisco Systems, GE Healthcare, General Mills, ArcelorMittal, the world’s largest steelmaker, and Swisscom, a large telecommunications company.

At the same time, a network of software and service suppliers is developing to cater to corporate prediction markets. The vendors include H.P. and smaller specialist firms like Consensus Point and NewsFutures. The field is attracting start-ups as well.

In 2006, for example, Adam Siegel and Nate Kontny left Accenture, the consulting firm, to found Inkling Markets. Mat Fogarty had been director for financial planning at Electronic Arts, where he experimented with prediction markets, before founding Xpree last year.

“Prediction markets are starting to move into the mainstream, and they will really change the way companies are run in the future,” said Emile Servan-Schreiber, the chief executive of NewsFutures.

At InterContinental Hotels, Zubin Dowlaty, vice president for emerging technologies, decided to create an online market last fall to “harvest and prioritize ideas” from within the hotel’s 1,000-person technology staff. “We wanted to tap the creative class that may not be able to voice their ideas,” Mr. Dowlaty said.

With InterContinental’s prediction market, players were asked to submit ideas anonymously, with a description and the benefit to customers and company. The bettors were given virtual tokens, each receiving 10 green ones to be placed on the best ideas and three red for bad ideas.

There were no limits on the number of times bettors could change their wagers as new ideas came to market, and the market was open for four weeks. The five top ideas (most green tokens), five bottom ideas (most red) and the top five bettors (most accurate, according to market consensus) were listed regularly.

The winners got $500, while second- and third-place finishers received $250 each. The winners, Mr. Dowlaty said, were engineers, analysts and contractors, not managers.

More than 200 people participated, submitting 85 ideas. One person proposed bringing back quarter-operated vibrating beds. “That one got beat down really fast,” Mr. Dowlaty said.

The winning ideas were suggestions to improve searching the company’s Web site to find and book hotel rooms. Two projects have been started as a result of the market, Mr. Dowlaty said.

Next, he said, prediction markets may be opened up to InterContinental’s customers, probably beginning with members of its Priority Club loyalty program. They could bet in markets for improving service and offerings, with points redeemed. “It’s the next frontier and the natural progression for this,” Mr. Dowlaty said.

Setting up corporate prediction markets can be tricky. Public markets for presidential candidates will attract thousands of bettors, but a company may want to run a market only for people with expertise in a certain product or project. At Hewlett-Packard, researchers have been working on techniques and software to make even small prediction markets efficient.

“We want to reduce the wisdom of crowds to the wisdom of 12 or 13 people,” said Bernardo A. Huberman, director of the social computing lab at Hewlett-Packard. Among the techniques, he said, are preliminary tests to assess the “behavioral risk characteristics” of participants to shade predictions from people who are inherently risk seekers or risk averse.

Starting a year ago, a group in the purchasing unit at H.P. began prediction markets on the price of computer memory chips three and six months ahead. The prediction markets, Dr. Huberman said, were up to 70 percent more accurate than the company’s traditional forecasting models. The more accurate predictions, he said, can be used to finesse purchasing, marketing and product pricing decisions.

The H.P. research project has become a service offering called Brain, for Behaviorally Robust Aggregation of Information in Networks. The service is now used in pilot projects by H.P. clients that include Swisscom, which is trying it to predict demand for new services like Internet television on cellphones.

At GE Healthcare, Steven Linthicum, manager for advanced prototyping and innovation, has recently managed prediction markets projects that have generated ideas for software products for the hospital and health care market. Based on that work, patents have been filed and projects are under way.

“These markets bring not only ideas, but what your organization thinks of the ideas,” Mr. Linthicum said. “That’s what leadership needs to know.”

G.E. is also evaluating how broadly prediction markets could be used in the health care division, a $17 billion-a-year unit, and elsewhere in the company.

“We’ll know a lot more at the end of the year how much this becomes part of the decision-making process,” Mr. Linthicum said. “We’re at the crossroads right now.”