Archive for September, 2009

Friday, September 25th, 2009
Consensus Point to host prediction market roundtable discussion in Chicago

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.

Thursday, September 17th, 2009
Prediction Markets Summit and Collective Intelligence Cluster on November 6 2009 in Chicago

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.

Thursday, September 10th, 2009
Prediction Markets As Collective Intelligence

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

September 4, 2009 

I talked for seven minutes this Wednesday at “Tap The Collective“, after six other speakers also talked for seven minutes each on various forms of “collective intelligence.”  I tried to put prediction markets (and similar mechanisms) in the context of other approaches by saying that other approaches often work very well when either:       
        1. The info people contribute is verifiable, or
        2. The conclusions people draw are uncontroversial.
 

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.

Friday, September 4th, 2009
Prediction Markets succeed when organizations follow proven best practices of Enterprise-wide projects

Consensus Point and Our Customers, such as Best Buy and Ingenix, follow a proven enterprise methodology to yield maximum return and value from our prediction markets.  The major organizational best practices include:

1)   Define Business Problem that prediction markets solve and articulate value that could be derived with market insights; develop projected outcomes and track progress that prediction markets solve and articulate value that could be derived with market insights; develop projected outcomes and track progress  

2)    Determine Executive Sponsor and Prediction Market Leader – two different roles, Executive Sponsor guides market strategy and decision acceleration and Prediction Market Leader provides day to day leadership; incorporate prediction market reviews into existing steering committee structures

3)    Begin with a subset of participants, internal first, and validate accuracy through comparisons to baselines; run a market for minimum 90 days, then gather proof points and expand further to other employees, partners, and potentially customers

4)    Align incentives with company culture- and provide multiple rewards that include influence and career development incentives

5)    Determine mix of participants from several functional groups, with a minimum of 30-50 participants; the broader the participant base, the more liquidity for the market

6)   Be Transparent: communicate early and often about market success and decisions that are made from market insights; employee engagement will likely increase from hearing the actions being taken as a result of the market predictions

 
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