Predicting the performance of Prediction Markets

I am fascinated, in this interconnected media, with online Social Capital, Social Capitalism, and therefore all forms of Social Markets. Prediction Markets are one of the most intriguing.

(For those not familiar, here is the Wikipedia definition: Prediction markets are speculative markets created for the purpose of making predictions. Assets are created whose final cash value is tied to a particular event (e.g., will the next US president be a Republican) or parameter (e.g., total sales next quarter). The current market prices can then be interpreted as predictions of the probability of the event or the expected value of the parameter. Prediction markets are thus structured as betting exchanges, without any risk for the bookmaker)

Thus this
McKinsey Quarterly article on Prediction Markets caught my interest, from a panel discussion involving Bo Cowgill, who manages Google’s prediction markets; Todd Henderson, an assistant professor at the University of Chicago Law School; Jeff Severts, general manager of Geek Squad, the services arm of US electronics retailer Best Buy; and James Surowiecki, author of The Wisdom of Crowds, a book about prediction markets and other forms of collective intelligence. Renée Dye, a consultant based in McKinsey’s Atlanta office, moderated the discussion.

Its behind a paywall, but key points were:

Define the variable you are trying to forecast
Express variables in a precise, intuitive unit (such as “2nd-quarter revenue, in euros, for new product X”) to avoid confusion among participants.

Give the market a relatively short time duration to keep it interesting and boost participation.

Decide how comfortable you are sharing the results
Be prepared for management embarrassment (“everyone thinks we should shelve our new product launch”).

Consider legal issues (“nobody in the company thinks we will meet the earnings targets our stock price implies”).

Decide who should participate
Markets involving only internal participants are easiest to organize, though adding external participants can help companies achieve the law of large numbers. Information sharing challenges exist for both internal and external participants. Front-line employees often are the most active and excited participants.

Decide on the nature of the market
Markets with real-time buying and selling of contracts yield rich, continuous results but require large numbers of participants, some of whom may need training.

Simple surveys and other single-point forecast mechanisms are easier to administer. Companies getting started may want to proceed gradually through a series of increasingly sophisticated experiments.

Decide on incentives
Cash prizes boost participation but run the risk of looking like “internal betting pools”—where employees can bet on (or against) the company—which could cause legal problems.

Another option is combining symbolic incentives, such as public recognition of strong forecasters, with prizes such as gift cards.

Decide on the role of experts
Departments dedicated to forecasting will see the establishment of a prediction market as a threat.

A key challenge for companies using prediction markets is shifting the mind-sets of experts about their roles, from “knowing all the answers” to asking the right questions to analyzing the answers in creative ways and using them to guide decision making.

This is an early day science but I can't help but think it will form a key part of a lot of the "Social Commerce" systems now emerging all over the space (other examples being Crowdsourcing, C2B aggregation, VRM etc)

Is there bad news for McKinsey though? - maybe strategic Consultants won't be needed. as one of the participants noted:

We ran a similar experiment later that year, when 350 random people predicted our holiday sales. Once again, the nonexperts, off by just one-tenth of 1 percent, were more accurate than the experts, who were off by 7 percent. The participants were surprised by the outcome when we shared it with them well after the actual results were in and reported.

It will be interesting to watch - Prediction Markets have had a bumpier than expected ride so far - as the above discussion notes, they pose quite a few threats to established corporistas.