September 15 2008 / by Alvis Brigis / In association with Future Blogger.net
Category: Economics Year: General Rating: 4
Enterprise prediction markets have been growing in popularity, but face three major hurdles to success: 1) lack of access to all relevant information, 2) regulatory concerns, and 3) adoption / sticky use. As these are resolved, new-age prediction markets will increase in value, diffuse more quickly and make us smarter as a species.
1. Lack of access to relevant information: My big takeaway from Wisdom of the Crowds, the prediction market bible by journalist James Surowiecki, was that a large group of humans can consistently out-predict individuals, but only if all the brains are knowledgable of the given topic area. For example, farmers won’t be great at predicting next year’s fashion colors – that will be left to the those with more direct exposure to the appropriate industry trends.
Prediction market guru Chris Masse points out a similar flaw plaguing most, if not all, enterprise prediction markets: lack of access to ”’experts’ and other ‘business leaders’”. Masse argues that minus this crucial top-level information a company’s internal “prediction markets would be clueless, useless, and worthless.”
Solutions: The obvious but eminently unpalatable solution is for corporations like Google, GE, and Microsoft that already utilize prediction markets to open-up access to more of their top-level data to employees or even the public. This would immediately result in better predictions, but would obviously benefit their numerous cut-throat competitors. It will take some time for big businesses to implement such transparent practices, though I can imagine the right start-ups could successfully implement such an open strategy and then scale.
On the flip side of coin, companies could up the incentives for successful predicting in external but vastly larger markets, essentially throwing more money and brains at the process. They could then make use of the growing # of top rated performers and ideas (would be shocked if they’re not already mining such data). It seems like this will gradually occur as 1) companies increasingly look to the web for ideas, 2) the semantic web and better search makes everyone smarter faster.
Then again, a more immediately plausible middle road could involve bringing on a group of professional predictors, say 40 – 100 diverse individuals, and then give them access to the highest level information. Of course, they would be required to live in a cave and never again communicate with friends or family…