On Friday, Prediction Markets Cluster kicks off their Collective Intelligence Summit in Seattle. This year’s theme is “Leading Enterprise Social Media and Prediction Markets.” We attended last year’s summit in Chicago and enjoyed seeing one of our customers present.

This year, Christel Alvarez, our lead Account Executive, will be representing us to discuss prediction markets in the enterprise. Those who attend can expect to hear her discuss strategies for making prediction markets successful in enterprise applications through the rule of three: a combination of consultant, customer, and Foresight.

If you’re interested in the power of collective intelligence for competitive advantage, we hope to see you there!

Ingenix, a Consensus Point partner, recognizes how important the power of collective intelligence can be in healthcare. With the Ingenix Prediction Market, Ingenix is helping employers optimize how healthcare dollars get spent. The end result is more profitable companies with healthier, happier employees.

Ingenix also offers a variety of solutions directly to physicians. We wouldn’t be surprised to see collective intelligence solutions from Consensus Point helping Ingenix empower doctors as well as employers.

Last week, Jonathan Bush, CEO of Athenahealth, a physician billing and practice management firm, was interviewed in the Wall Street Journal. In a wide-ranging interview covering various dimensions of healthcare policy and the ramifications from technology and innovation, this stood out to us:

Mr. Bush thinks the main benefit is the “collective intelligence” that he is starting to weave together from the 87% of American physicians who practice solo or in groups of five doctors or fewer.

Time and again the wisdom of crowds has proven valuable and most times more accurate than a single SME. Applying prediction markets in healthcare can yield benefits for policy and delivery of services.

For more on the Ingenix Prediction Market and Ingenix solutions, go to www.ingenix.com/informationis.

Andrew McAfee shares a “teaching moment” demonstrating the real-life application of prediction markets.  McAfee’s example shows that, even in its simplest form, prediction markets are very accurate and have a wide range of uses. 

Prediction Markets: A Teaching Moment 
cross posted from the Harvard Business blog by Andrew McAfee
2:14 PM Tuesday December 1, 2009 

Nick Bostrom, Director of The Future of Humanity Institute at Oxford University, considers the impact that prediction markets could have on the creation of government policy in the UK. 

Rebooting Britain: Make policy using prediction markets

By Nick Bostrom | 01 December 2009

This article was published in the January issue of Wired UK magazine.

How do we know what to think about the future? Politicians make confident predictions. If we elect them, unemployment will allegedly go down, the economy will grow, crime will be reduced, and terrorist attacks will be prevented. If we elect their opponents, the opposite will happen. These opponents, of course, disagree. Whom should we trust?

We could listen to the media pundits, but pundits are usually given a platform because they are articulate and entertaining, not because they have a track record of being right. We could listen to academic experts, but both sides of a political dispute can usually point to some experts who support their view. Or we could try to form our own opinions; but we may not know very much about the issue at hand, and at any rate, it is unclear why we should believe that our opinions would be any more reliable than the opinions of all those millions of people who have considered the issue and embraced the opposite view.

One way of generating predictions is betting markets. If people are allowed to buy and sell bets that some hypothesis is true, then the fluctuating price of those bets can be interpreted as a probability estimate of that hypothesis. The hypothesis could be that some particular horse will win a race, or it could be that weapons of mass destruction will be found if our forces invade some particular country. The principle is the same in both cases but, as pointed out by the economist Robin Hanson, the information that could be revealed is much more valuable in the second case.

In every known head-to-head field comparison between speculative markets and other forward-looking institutions, the speculative markets have been at least as accurate. More often than not, they prevail. Orange-juice futures improve on National Weather Service forecasts, horse race markets beat horse race experts, Oscar markets beat columnists’ tips, gas demand markets beat gas demand experts, stock markets beat the official NASA panel at identifying the company responsible for the Challenger accident, election markets beat national opinion polls, and corporate sales markets beat official corporate forecasts.

Prediction markets can aggregate many small pieces of information held by large numbers of people from diverse backgrounds. Prediction markets seem to work well because they reward accuracy (rather than the ability to tell a convincing story) and punish error (rather than the voicing of politically inconvenient opinions).

No system for making predictions is going to be perfect, but so far the empirical evidence seems to quite strongly favour prediction markets compared to alternative ways of generating forecasts. Therefore, the traditional ways of forecasting uncertain political futures – pundits, academic experts, debates between leading politicians, and personal gut feelings – should be supplemented by the creation of prediction markets wherever possible. When the issue at hand is sufficiently important, such markets should be subsidised by the state as a relatively inexpensive form of intelligence gathering.

Horse-betting is selfish, but betting on policy-relevant outcomes would be public service. Pundits should be expected to put their money where their mouths are, and everybody who can afford to lose £10 or £20 should be encouraged to participate. Journalists should be asked to include information about prediction market estimates in their coverage of controversial topics. Schoolchildren should be taught applied probability theory in the classroom and given the opportunity to practice their skills in real-world settings.

This way, I think, Britain would make shrewder policy decisions. Moreover, its population would learn to think about uncertainty in a sophisticated and mature manner. In our complex modern world, that would be a winner.

Nick Bostrom is director of the Future of Humanity Institute at Oxford University.

Dawn Keller, formerly with Best Buy, evaluates ROI of prediction markets and how business leaders need to consider the “cost of not doing” and “cost of alternatives” in this equation.

 Excerpt from Dawn Keller’s blog, The Answer is in the Crowd

From what I’ve seen in the marketplace (both first and second hand), Prediction Markets frequently face the same bottom line scrutiny as any other enterprise application, tool, or resource. How much value will it generate and when? Arguably, the business case should be extra tight when evaluating something new and unconventional. And prediction markets fit the bill. They are not yet widely adopted; they stem from newfangled trends such as crowd-sourcing; and most egregiously, they challenge traditional management orthodoxies.

 Here’s what companies often say:
This seems very promising, but I’m not sure it’s worth the cost.  What kind of returns can I expect?  What is the value of this new information?

Here’s the cost-benefit equation those comments imply:
Market value = market benefit - market cost
    or …
ROI = market benefit / market cost
   where …
        cost = price of Prediction Market solution + cost of internal time & resources
        benefit = value of the information (generated by the market)
Not to get hung up on the math, but these simple equations are missing at least three variables:

1. the cost of not doing
2. the cost of alternatives
3. the multiplying factor of the company’s management “skill”

The cost of not doing

Here, I’m simply flipping around one of the original questions.  Instead of only asking what is the cost of doing something, sophisticated leaders also evaluate the cost of not doing something.  In other words, what is the risk of passing on a particular opportunity, or ignoring a particular problem?  Those risks should be considered, and considered as costs.

Read more from Dawn’s blog on the ROI of prediction markets and how prediction markets can address your business needs.

Excerpt from Michael J. Mauboussin’s Think Twice: Harnessing the Power of Counterintuition

Accurately projecting holiday sales is a crucial task for retailers.  A forecast that is too low leaves shelves bare and profits lost, while too much optimism leads to dusty inventory and pressure on profit margins.  So retailers have come up with a precise sales estimate.  To do so, most merchants rely on experts—individuals in the organization who gather information, study trends, and make predictions. 

                The stakes are especially high for consumer electronics firms because they generate so much of their revenue during the gift-giving season and the value of their inventory depreciates rapidly.  The pressure is really on the internal experts at consumer-electronics giant Best Buy, one of a multitude of retailers that rely on specialists.  So you can imagine the reaction when James Surowiecki, author of the best-selling book The Wisdom of Crowds strolled into Best Buy’s headquarters and delivered a startling message: a relatively uninformed crowd could predict better than the firm’s best seers.

                Surowiecki’s message resonated with Jeff Severt’s, an executive then running Best Buy’s gift-card business.  Severts wondered whether the idea would really work in a corporate setting, so he gave a few hundred people in the organization some basic background information and asked them to forecast February 2005 gift-card sales.  When he tallied the results in March, the average of the nearly 200 respondents was 99.5 percent accurate.  His team’s official forecast was off by five percentage points.  The crowd was better, but was it a fluke?

                Later that year, Severts set up a central location for employees to submit and update their estimates of sales from Thanksgiving through year-end.  More than three hundred employees participated and Severts kept track of the crowd’s collective guess.  When the dust settled in early 2006, he revealed that the official forecast of the internal experts was 93 percent accurate, while the presumed amateur crowd was off by only one-tenth of 1 percent. 

                Best Buy subsequently allocated additional resources to its prediction market, called TagTrade.  The market has yielded useful insights for managers through the more than two thousand employees who have made tens of thousands of trades on topics ranging from customer satisfaction scores to store openings to movie sales.  For instance, in Early 2008, TagTrade indicated that sales of a new service package for laptops would be disappointing when compared with the formal forecast.  When early results confirmed the prediction, the company pulled the offering and relaunched it in the fall.  While far from flawless, the prediction market has been more accurate than the experts a majority of the time and has provided management with information it would not have had otherwise.

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.

(Cross posted from Robin Hanson’s blog Overcoming Bias)

In these cases good tools, representations, interfaces, etc. can greatly help people join together in a spirit of constructive camaraderie to build documents, analyses, plans, etc.   People then appreciate the additions and edits of others in building a common product that all will admire.  False or misleading contributions can be quickly detected and eliminated.

The big problems for most collective intelligence tools come when the topics are controversial, and the contributions involve a lot of judgment.  For example, consider folks elaborating a schedule of which projects will be finished when, or designing a budget of which potential projects shall be funded.  Here folks are often justly concerned that many “contributions” will be self-serving attempts to make them or their groups look better or gain more resources.

Prediction markets were designed for exactly these sort of hard problems – contributors know they face a risk of losing as well as gaining from their contributions.  So folks think a little more carefully about what they might say, and choose not to speak when they doubt they have something useful to say.  Prediction markets allow organizations to tap the collective to aggregate info on their most important and controversial topics.  But of course they aren’t the only or best way to support collaboration on all topics.