He [Rami Levy, a technologist with the Motorola's mobile devices business] says the combined revenue from product-based ideas and cost savings from internal innovations is “conservatively” 5 to 10 times TIX administration costs, which largely involve two to three dedicated employees. The cost to purchase and implement prediction-market software — called Foresight Server, from Consensus Point — was “under $100,000,” he says.

CFO.com has an extensive write-up of the customer success we’ve had with Motorola, and we are impressed with Mr. Levy’s ability to concisely identify the bottom line value that our Foresight prediction markets platform is capable of delivering to the enterprise.

Further, the article is an elegant case study of the sort of business scenario that is a perfect opportunity for the use of prediction markets, the path to implementation, and the ultimate value.

What we like best about the article, in fact, and consider a true success for Motorola’s implementation of our solution, is that the value goes beyond raw consideration of the bottom line:

But additional, softer benefits were key goals for the program, too. These have been realized through collaboration forums that allow employees to see and comment on others’ ideas, which are thus improved by the crowd’s input. The forums facilitate people from disparate regions and company organizations forming relationships, working together on ideas, and avoiding duplication of effort, Levy says. Motorola actually introduced the forums in 2005 along with the voting mechanism, but participation spiked after TIX was introduced and continues to rise.

The bottom line, says Levy: “TIX has proved to be an excellent conduit for enabling collaborative innovation and creating new value for Motorola in a fun and enjoyable way that encourages participation at a minimal cost.”

When was the last time you implemented something for the enterprise that not only created cost-effective value but was also fun?

You can read the full CFO.com article here, and you can contact us about Foresight here. We predict customer success if you do.

Linda Rebrovick, CEO of Consensus Point, discussed effective uses of prediction markets, based on multiple years of supporting effective enterprise prediction markets in large companies and government organizations.  She explained that effective enterprise markets require 3 key components:  a proven and expert consultant, a solution that targets key business problems, and the right customer environment and implementation plan.  Rebrovick discussed several use cases highlighting customer examples across several industries and business problems. 

Click Here to Download Presentation (PDF)

Rami Levy, Distinguished Member of the Technical Staff, Technical Lead and Manager of Motorola’s Open Source Technologies Team, explained how Motorola added the TIX Market, powered by Consensus Point, in 2007 to address the challenges of increasing idea backlog and missed opportunities. Levy explained the evolution of the TIX Market and how, over time, the prediction market has streamlined the innovation process, yielding benefits of 55% decrease in disposition days and 40% increase in idea pursue rates. 

Click here to Download Presentation (PDF)

Robin Hanson, Chief Scientist of Consensus Point, discussed the advantages of prediction markets and how to develop effective markets to efficiently yield meaningful outcomes. 

Click here to Download Presentation (PDF)

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.

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.

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.

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.

Brian Spears
GE Hitachi Nuclear Energy

Christina LaComb
John Interrante
Janet Barnett
Deniz Senturk-Dogonaksoy
GE Global Research Center

ABSTRACT
We present the outcome of an idea market run for one of GE Energy’s sub-businesses in July and August of 2006. GE Energy used this market to elicit and rank-order technology and product ideas from across the sub-business. In this experiment, we examine the behavior of traders that have submitted the ideas on the market and their influence on the market’s outcome. An idea’s submitter is clearly motivated to have his idea valued highly by the market, both by the funding given to the top idea as well as smaller prizes given to the top three ideas. In general, founders tended to buy their suggested ideas at prices above the volume-weighted-average price (VWAP) in significant volumes. We discuss the implications and mitigation strategies. A survey of market participants yielded mixed results regarding the market’s effectiveness at ranking ideas but very positive results regarding the quality of ideas proposed. 

Click here to read the full paper.

The Journal of Prediction Markets (2009) 3,1 17-39

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.

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.