This blog is not geared toward the existing Prediction Market intelligentsia. While I would be honored to have fellow enthusiasts read and critique this blog, I’m not writing this for them, specifically.

I’m writing for a general business audience, decision makers in particular. The discussion will be geared toward people who may have never heard of Prediction Markets, may be minimally aware and curious, may be knowledgeable but still skeptical, or who may be interested but need help engaging others within their organization.

Dawn Tevekelian Keller’s goal is to evangelize enterprise prediction markets:

This simple but powerful truth is why Prediction Markets could potentially change the course of events for Boeing and its Dreamliner jet. By enabling the company to swiftly and accurately tap its own collective knowledge, [prediction] markets create an intelligence engine with infinite application and shelf life.

All this is gentle, she capitalizes “Prediction Markets” in her posts to make it more respectable, but where is the scientific evidence? The name of her blog “the answer is in the crowd” suggests that she believes that collective forecasting brings a giant-size added accuracy, which is not the case, in fact. People who evangelizes collective intelligence should make modest and humble claims.

Using Prediction Markets to Support IT Project Management – by Herbert Remidez and Curtis Joslin – 2009-02-XX

Forrester

Prediction Markets: Wisdom Of The Crowd Comes To The Enterprise. – (MO excerpts) – 2008-07-14

Google – (U.S.A.)

Using Prediction Markets to Track Information Flows: Evidence from Google – (PDF file – PDF file) – (MO excerpts) – by Bo Cowgill, Justin Wolfers, and Eric Zitwewitz – 2008-01-06

More on Google Prediction Markets – [internal prediction markets @ Google] – by Patri Friedman – 2005-09-22

• The trickiest problem was how to measure predictiveness. In our system, if an event has a price of ten cents, that means it should be 10% likely. This is because each outcome is worth 1 Gooble (play money dollar) if it comes true, but 0 otherwise. So if an outcome has a 10% chance of happening, its price should be ten cents. But in the end, it will either happen or not – so how to evaluate the accuracy of that 10%? We came up with the idea of taking all the predictions (every average weekly price for each outcome) and bucketing them, ie 0-10%, 10%-20%, etc. Even though a single data point tells us nothing, if we collect 100 data points that we say should happen 10%-20% of the time, on average about 10-20 of them should happen.

Putting crowd wisdom to work – [internal prediction markets @ Google | See also the NYT article.] – by Bo Cowgill – 2005-09-21

• The markets were designed to forecast product launch dates, new office openings, and many other things of strategic importance to Google. So far, more than a thousand Googlers have bid on 146 events in 43 different subject areas (no payment is required to play).
• So our prices really do represent probabilities – very exciting!
• Our search engine works well because it aggregates information dispersed across the web, and our internal predictive markets are based on the same principle: Googlers from across the company contribute knowledge and opinions which are aggregated into a forecast by the market.

McKinsey – (U.S.A.)

The Promise Of Prediction Markets – 2008-04-XX

Intel Corporation – (U.S.A.)

The Spectrum of Risk Management in a Technology Company – Using Forecasting Markets to Manage Demand Risk – (PDF) – (Excerpts on Midas Oracle) – by Intel Corporation’s Jay W. Hopman – 2007-05-16

General Electric – (U.S.A.)

The imagination market – by Christina Ann LaComb, Janet Arlie Barnett and Qimei Pan – 2007-03-10

• Information markets are typically used as prediction tools, aggregating opinions about the likelihood of future events, or as preference indicators, identifying participants’ product preferences. However, the basic information market concept is more widely applicable. In our experiment, we utilized information markets within the domains of idea generation and group decisioning. Participants were allowed to propose ideas regarding potential technology research areas; these ideas were represented as securities on a virtual financial market. Participants were able to trade shares of technology ideas over the course of 3 weeks, resulting in the market identifying the “best” idea as the highest priced security. Our findings suggest that information markets for idea generation result in more ideas and more participants than traditional idea generation techniques; however, using markets to rank ideas may be no better than other methods of idea ranking. Additional benefits include providing immediate feedback, allowing visibility of all ideas to all contributors, and being a fun mechanism for consensus building.

What’s Your Idea Worth? – [internal prediction markets @ GE | See also the WSJ article.] – 2006-06-21

• Last summer, we ran our first “Imagination Market”. We asked the 150 members of the Computing and Decision Sciences group to participate in a market to identify breakthrough technology research areas that we should be investigating. Since we knew that innovative ideas could come from anywhere, we asked lab managers, project leaders, individual contributors, contractors, summer interns, and other support staff to join in.
• The highest price security at the end of the market, based on the volume-weighted average price over the last 5 days of traded, was considered the “best” idea. The individual who proposed the idea was awarded research funding to more fully explore the research topic.
• I can tell you that the idea was in the area of artificial intelligence.

MicroSoft – (U.S.A.)

Case: MicroSoft’s internal prediction markets – 2007-01-23

Corning – (U.S.A.)

Corning’s Predictions – [Corning's LCD TV prediction markets are been discontinued, according to a Chris Hibbert's comment on this blog post.] – by Alex Kirtland – 2006-07-26

Pharmaceutical Industry – (World)

Can the Many forecast better than the Few in the pharmaceutical industry? – (PDF) – by Joseph Miles – 2007-02-XX

The Institute For The Future – (U.S.A.)

The Experience of Prediction Markets – by Jessica Margolin – 2007-09-12

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CFM

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