It’s that time again, election time. Prediction markets are back in the spotlight as the political arena heats up for Presidential elections. More and more people from pundits to professors are trying to predict what the future will hold.

Robin Hanson, Consensus Point’s Chief Scientist and the “Father of Prediction Markets,” is speaking today at the University of Western Ontario’s Political Economy Research Group Conference on a panel entitled, “Can Social Science Predict Accurately: the Case of Elections.” Robin will be focusing on what social science can actually predict with accuracy and what is beyond its reach. Robin will, of course, put special emphasis on prediction markets and how they can be utilized as a powerful tool for predicting future events.

Over the coming year, as the final election draws closer, we expect to see many more of these types of conferences. Stay tuned!

Yesterday, our Chief Scientist Robin Hanson presented at the Society for Risk Analysis 2010 Annual Meeting. We mention it because risk management is one of the primary domains of problems to which our Foresight platform can be applied.

Robin is known for thinking big and thinking about the future, and his talk yesterday was representative in both regards. Here’s the abstract:

Catastrophic Risk Forecasts from Refuge Entry Futures
Speculative markets have demonstrated powerful abilities to forecast future events, which has inspired a new field of prediction markets to explore such possibilities. Can such power be harnessed to forecast global catastrophic risk?

One problem is that such mechanisms offered weaker incentives to forecast distant future events, yet we want forecasts about distant future catastrophes. But this is a generic problem with all ways to forecast the distant future; it is not specific to this mechanism. Bets also have a problem forecasting the end of the world, as no one is left afterward to collect on bets. So to let speculators advise us about world’s end, we might have them trade an asset available now that remains valuable as close as possible to an end. Imagine a refuge with a good chance of surviving a wide range of disasters. It might be hidden deep in a mine, stocked with years of food and power, and continuously populated with thirty experts and thirty amateurs. Locked down against pandemics, it is opened every month for supplies and new residents. A refuge ticket gives you the right to use an amateur refuge slot for a given time period. To exercise a ticket, you show up at its entrance at the assigned time. Refuge tickets could be auctioned years in advance, broken into conditional parts, and traded in subsidized markets. For example, one might buy a refuge ticket valid on a certain date only in the event that USA and Russia had just broken off diplomatic relations, or in the event a city somewhere is nuked. The price of such resort tickets would rise with the chance of such events. By trading such tickets conditional on a policy that might mitigate a crisis, such as a treaty, prices could reflect conditional chances of such events.

Okay, so that’s not a traditional business problem. But if you’re an executive who’s uncomfortable with uncertainty, you should get in touch with Consensus Point.

Because we hang out with smart people like our Chief Scientist Robin Hanson, we’re sometimes inspired to read scholarly publications relevant to our work. Earlier this year, a Masters Thesis came out of Erasmus School of Economics with an intriguing title: “The Relevancy of Group Expertise for the Accuracy of a Prediction Market.” Danielle Almeida’s prose hooked us from the first page…

First of all, Almeida provides a pithy description of prediction markets:

A prediction market is a futures market in which a large group of people can express their opinion about the out coming of a certain event by buying shares from the answer that – according to the participant – is most likely to be correct. Prediction markets are increasingly implemented in enterprise environments.

The author then makes a list that reminds us of our own list of dos and don’ts:

• Invite as many participants as possible to the company’s prediction market: there is no relevance with regard to the accuracy of the out coming of the prediction market.
• In general, employees that have more knowledge on the subject need less explanation why you want them to participate. Also, more knowledgeable employees are more likely to keep participating when related questions are asked consecutive. This means that non-experts might need an extra stimulation to participate.
• Be aware of the ‘contradictory effect of the prediction market’ that might occur when non-experts are involved. It seems that they have different approaches to come to their decisions. While experts merely buy the shares of the answer they believe is most likely to be right, some non-experts tend to play a more strategic game.

You’ve been hearing us talk about the efficacy of prediction markets for a while, but what we offer is much more than just a platform. We know the platform, and we know how to make it effective in the enterprise. Which is why we offer extensive consultative services, from implementation through monitoring and management.

Finally, we hate spoilers, but we’re going to go ahead and give away the ending because we can’t help it:

Based on this research, we would like to recommend all companies to consider implementing a prediction market to support their decision making process in case predictions are a necessary part of the decision making process. We have proven with this research that – based on several data – a group of experts is not capable of making significant better predictions than non-experts.

Especially companies that have hired expensive experts to make forecasts about future events – such as turnover and product innovation – can save a lot of money, by just asking employees, suppliers and customers to make these forecasts for them. Even on a larger scale than previously researched, experts do not outperform non- experts significantly when using a prediction market to forecast.

If you’re an executive who needs better forecasting guidance, you don’t need an expert; you need experts in implementing prediction markets like Foresight. Our expert advice: call us.

Last week, Robin and I presented to a group of Chicago-based knowledge managers on the topic of enterprise prediction markets. We were focused on efficacy in the enterprise: what makes markets work in a business environment and why. Of course, the first thing that makes them work is selecting the right platform. We also tried to provide some background on market theory, as well as applied lessons.

We think the reasons markets work for forecasting guidance are fascinating, and we’re perpetually fascinated by Robin and his research. We’re continually impressed by customer success, too. We did our best to ensure that the talk included a mix of theory and applied material drawn directly from those customer successes.

Here are a few lessons from the talk on how to operate an enterprise prediction market with ongoing success:

Do:

• Integrate
 into
 enterprise
 processes
• Nurture executive sponsorship
• Make accessible to all
• Customize to your business
• Make it part of your value proposition

Don’t:

• Run a 30-day pilot
• Use a similar group of participants
• Run a market without promoting it
• Assume leaders will act on insights

If you’d like to dig deeper into the why of the do and don’t, we’ve posted the slides from our talk. And if you’d like to engage our services, we hope you’ll contact us.

On November 5 in Chicago, Dr. Robin Hanson, Chief Scientist of Consensus Point, and Rami Levy of Motorola, will be discussing the most effective applications of prediction and idea markets in business and government organizations at a lunch hosted by Consensus Point. Idea and prediction markets will become part of the internal DNA of the best organizations, as these solutions link human capital to organization results by providing leading indicators for the most important initiatives. Rami Levy of Motorola will share the business objectives and specific results of Motorola’s Thinktank Idea Exchange.  Dr. Hanson will share some specific approaches to structuring effective markets.

Robin Hanson, PhD., Associate Professor of Economics, George Mason University and Chief Scientist, Consensus Point

Rami Levy, Technical Lead and Manager, Open Source Technologies team, and distinguished member of Motorola’s technical staff, Motorola, Inc.

For more information, contact Consensus Point at info@consensuspoint.com.

The Prediction Market Clusters in collaboration with Aurora WDC, Consensus Point, University of Chicago Gleacher Executive Center and many others announces the Prediction Markets Summit and Collective Intelligence Cluster Friday 6 November 2009 in Chicago, Illinois, USA.

San Francisco, CA (PRWEB) May 31, 2009 — The Prediction Market Clusters in collaboration with Aurora WDC, Consensus Point, University of Chicago Gleacher Executive Center and many others announces the Prediction Markets Summit and Collective Intelligence Cluster Friday 6 November 2009 in Chicago, Illinois, USA.

Prediction Markets Summit and Collective Intelligence Cluster The venue is the stunning University of Chicago Gleacher Executive Center in Chicago, Illinois, USA. 

Learn how prediction markets, social media and collective intelligence networks are fundamentally altering the enterprise landscape. New forecasting techniques and technologies are driving executive decision making, leading collaborative forecasting and optimizing supply chain management. Engage with experts in knowledge markets that are reshaping all practices of knowledge management (KM), advancing innovation and propelling enterprise knowledge ecologies of the future.

“There is not much that any of us do that is more important than telling the company what we know.” Jeff Severts, EVP, Best Buy

We are thrilled several key scholars and thought leaders will join your cluster including:
Robin Hanson, Professor, Economist, Polymath, George Mason University
George Neumann, George Daly Professor of Economics, University of Iowa

In 2004 James Surowiecki published his now-famous book, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. For many this milestone introduced the era of collective intelligence for people, business, institutions, the environment and civil society.

“Thanks for organizing an extremely useful and informative workshop!” – Professor Tom Malone, MIT Center for Collective Intelligence

Testimonials

New ways to share, trade and aggregate information using Internet-based markets are exploding. These powerful Web 2.0 social media and network knowledge markets help companies, schools, governments and individuals to acquire and master ever-growing bodies of knowledge. These prediction market capabilities achieve mastery knowledge management (KM) and collective intelligence with stunning speed, efficiency and accuracy.

“Prediction markets are brutally honest and uncannily accurate.” – Geoffrey Colvin, Fortune Magazine

New collaborative market mechanisms and social innovations are driving collective intelligence networks. They resolve questions of science, technology, management, strategy, planning and policy far better than experts or management.

Collective intelligence inhabits the ceaseless flurry of self-correcting social exchanges, social networks and collective knowledge markets. They cover everything from politics and business plans to sports and new product features. Enormously potent, these social networks and markets generate new ideas and amass and refine knowledge and collective wisdom with blinding speed, low cost and accuracy.

Collective intelligence networks and knowledge markets have become commonplace in the enterprise. Top firms using prediction markets are Best Buy, Google, Microsoft, Eli Lilly, Abbott Laboratories and Yahoo! to name a few. Major analysts firms declare prediction markets critical to Enterprise 2.0 information and knowledge management portfolios.

“A company that can predict the future is a company that is going to win.” – Bernardo Huberman, PhD, Senior HP Fellow, HP Labs

Cluster sessions are focused, practical and conversational. They are for executives, directors, mangers, users and practitioners having immediate needs to apply collective intelligence networks and market mechanisms to advance enterprise business outcomes through mastery of collective wisdom.

Pricing and Availability

Registration for the Collective Intelligence Cluster is open and available now. All are welcome. The event participant tuition, including full-day experience, meals, refreshments, books, reception and materials is $399.00 Secure online event check-in and registration in advance required. Early-bird registration ($299.00) is open until 30 September 2009.

Prediction Markets Summit and Collective Intelligence Cluster

Collective Intelligence Cluster Sponsors

Sponsors of the Collective Intelligence Cluster are the world’s leading producers of prediction market software, services, exchanges and expertise. They supply continuous innovation in prediction markets and collective intelligence networks. They include Aurora WDC, ConsensusPoint, Mercury-RAC, Prediction Market Clusters and many others.

About Prediction Market Clusters

The Prediction Market Clusters, founded in 2004, are the global industry commons and open community for prediction markets and collective intelligence networks worldwide. The open, agnostic network is a focused collaboration of vendors, academia, traders, users, developers, markets, regulators and stakeholders. The goal is to provide awareness, diffusion, adoption and pull-through for enterprise, institutional and consumer prediction markets. The Prediction Markets Cluster is the worldwide Next Practices leadership network for collective intelligence networks practices, tools and theories. For more information, please visit Prediction Markets Cluster.

For more information, discounts and to sponsor the Collective Intelligence Cluster, please contact Jennifer Hulett, Tel: 714-458-3826 Fax: 714-572-3742, for details.

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.)