In the Iowa Electronic Market (IEM) people bet on the outcomes of political races. On average, IEM has 23% less error than traditional polling methods.

The Hollywood Stock Exchange (HSX) public market lets people forecast Oscar winners and opening box office receipts. Its 700,000 active traders have predicted 92% of the Oscar winners in the last 3 years.

But, as you all know, Leslie Fine (their Chief Scientist) has decided to ditch the prediction market mechanism in favor of a simpler one.

We all knew that we had to start from scratch, and rebuild a mechanism that was easy to use, expressive both in terms of the question one can ask and the message space in which one can answer, and provided a high level of user engagement. We have abandoned the MSR [Market Scoring Rules] in favor of a new method that users are already finding much simpler and that requires a lower level of participation and sophistication than the usual stock market analogy.

So, CrowdCast is unveiling today their non-market solution:

With Crowdcast you get more accurate forecasts faster:

* Knowledge is dispersed throughout an organization, so you can invite many participants. Or you can be more selective. The Crowdcast market mechanism was designed to support both.

* Knowledge is weighted—participants can vary the level of their bet, depending on their confidence. It is also expressed as a confidence interval, rather than a point, which mirrors how people think and gives you actionable data.

* Accuracy is rewarded. As forecasts are realized, bets are closed out, winners are recognized

* Results are astoundingly accurate

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Here’s a video that explains it all (translating “employee intelligence into enterprise intelligence”):

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CrowdCast outputs both SaaS and consulting:

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CrowdCast is in the New York Times today:

During a pilot period, five large companies, including Warner Brothers and General Motors, have been using Crowdcast to predict revenue, ship dates or new products from competitors. About 4,000 bets that have been placed, and predictions have been about 50 percent more accurate than official forecasts, Ms. Fine said.

At a media company with a new product to ship, 1,200 employees predicted a ship date and sales figures that resulted in 61 percent less error than executives’ previous prediction, according to Crowdcast. A pharmaceutical company asked a panel of scientists and doctors to predict regulatory decisions and new drug sales using Crowdcast and they were more accurate than the company’s original prediction 86 percent of the time.

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CrowdCast’s PR release (boring stuff that Leslie sent me this early morning):

CROWDCAST LAUNCHES PREDICTION MARKETS PLATFORM FOR ENTERPRISE FORECASTING

Crowdcast Shakes Up the Forecasting Game

Redwood City, CA, June 25, 2009

Crowdcast, the leader in innovative corporate forecasting software, today announced the public availability of its prediction markets platform. By giving employees a marketplace where they place bets on important corporate metrics, Crowdcast reveals information that would normally not rise to executive awareness. The resulting forecasts are cleansed of bias and politics, and are significantly more accurate than traditional forecasts.

Forecasting is a multi-million dollar problem. According to the CFO Magazine/Duke University Global Business Outlook Survey of 1,275 finance executives, the most pressing concern for finance professionals is inaccurate forecasting. Crowdcast has helped media, technology, manufacturing and health care companies to improve forecast accuracy by as much as 60 percent, providing actionable data that can save those firms millions of dollars.

Typical Crowdcast Prediction Market Results:
• Media Firm – 1,200 employees predict quality, sales, and ship dates, resulting in61% less error versus management
• Pharmaceutical Company – panel of scientists and doctors predict regulatory decision sand new drug sales; more accurate 86% of the time

“Employees know what’s really going on in a corporation, but that information rarely reaches management’s ears. By tapping employee intelligence, Crowdcast channels this raw knowledge into actionable business intelligence,” said Mat Fogarty, Crowdcast Founder and CEO. “Crowdcast is the first enterprise-ready prediction markets platform that gives executives real-time data about progress toward specific goals so they can take action.”

An effective corporate prediction market offers users a simple interface, requires minimal interaction and allows easy communication of rich information. Crowdcast’s platform is the first prediction market designed specifically for the corporation, utilizing a cutting edge market design that moves far beyond the legacy stock-based trading systems. With Crowdcast, employees place bets on various corporate outcomes, compete with each other, and are rewarded for their accuracy.

“The Crowdcast platform leverages novel algorithms that are grounded in economic theory and experimentation, yet it is usable and engaging. The result is a best-in-class solution for enterprise crowd forecasting,” says Peter Coles, Assistant Professor at Harvard Business School. Crowdcast recently received Series A funding from Alsop Louie Partners.

http://www.crowdcast.com/

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UPDATE: Mat’s post

- CrowdCast on LinkedIn

- CrowdCast on FaceBook

- CrowdCast on Twitter

- VentureBeat

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Next: In most cases, the team (including the best predictors) outshines the best predictor working alone.

CrowdCast’s Leslie Fine:

The claim here is not that the administrator knows more than the executive.  The claim is that the executive’s point-of-view can be enhanced by mingling it with the admin’s. Empirical and experimental evidence show that in most cases the team (including the best predictors) outshines the best predictor working alone. Furthermore, in our implementations we find that our front line managers often have earlier information than the executive suite.  Our mission is not only to provide accurate forecasts, but to do so as early as possible.

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Andrew McAfee on CrowdCast

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UPDATE:

Leslie Fine (CrowdCast Chief Scientist) to me:

Actually, our mechanism is a market, it’s just not a stock market. We use an automated market maker to efficiently price every bet, adjust crowd beliefs, and price an interim sell. In essence, participants trade binary spreads with the market maker.

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UPDATE: Wall Street Journal

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Leslie Fine of CrowdCast:

Chris,

As Emile points out, in 2003 I started experimenting with (and empirically validating) alternatives to the traditional stock-market metaphor that will be more viable in corporate settings. We found the level of confusion and lack of interest in the usual fare led to a death spiral of disuse and inaccuracy. BRAIN was a first stake in the ground in prediction market mechanism design with usability as a fundamental premise.

When I joined Crowdcast (then Xpree) in August of 2008, Mat and the team already recognized the confusion around, and consequent poor adoption of, the MSR mechanism. The number of messages I fielded in my first month here asking me to explain pricing, shorting, how to make money, etc. was astounding. We all knew that we had to start from scratch, and rebuild a mechanism that was easy to use, expressive both in terms of the question one can ask and the message space in which one can answer, and provided a high level of user engagement. We have abandoned the MSR in favor of a new method that users are already finding much simpler and that requires a lower level of participation and sophistication than the usual stock market analogy.

I wish I could go into more detail. However, we need to keep a little bit of a lid on things for our upcoming launch. I can only beg your patience a little while longer, and I hope you will judge our offering worth the wait.

Regards,
Leslie

Nota Bene: IAM = information aggregation mechanism

UPDATE: They are out with their new collective forecasting mechanism.

- or the outcomes are combinatorial.

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- either the market operator acts as an auctioneer; [*]

- or he acts as an automated market maker.

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[*] Jason, does this mean that a pure, real-money betting exchange (by “pure”, I mean without an automated market maker) could organize combinatorial prediction markets?

Sorry for asking, but market design is not my major.

(You’ll notice that David Pennock‘s YooPick is cited. )

A previous combinatorial lecture by the same Hollywood science-fiction consultant.

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Robin Hanson was AWOL.

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UPDATE:

Nigel Eccles:

There was a bug in that chart which is now fixed. However the excess volatility is still there. The problem is that our early markets were created with a liquidity parameter which was too low. That is fixed with more recent markets. However we are also looking at modifying the MSR in some significant ways.

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Previously:

- the latest InTrade predictions

- Emile Servan-Schreiber’s post on market arbitrage

Makes me think of what some IT bloggers said… that they now get more daily referrals from social networking websites (like Twitter, FriendFeed, FaceBook, or LinkedIn) than from Google Web Search.

(That’s not the case with Midas Oracle. For your information, on week days, we receive about 350 daily visits from people using Internet search engines.)

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So, if you could answer my interrogations, please, e-mail me.

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YooPick for FaceBook

YooPick @ FaceBook

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PS: Yet another hit for Robin Hanson‘s MSR. – MSR is only step one in his world domination plan.

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UPDATE: Mystery solved.

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YooPick for FaceBook

YooPick @ FaceBook

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PS: Yet another hit for Robin Hanson‘s MSR.

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Nigel, you f***ed it up. I want your apology letter posted on Midas Oracle no later than Monday morning. I want you full of contrition.

And you need to tell your traders how you’re going to interpret an “exemption”. An “exemption” is in between a “license” (or, more exactly, being subject to the CFTC’s regulation) and an outright “exclusion”. It’s in between.

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