Another proof that prediction markets don’t put food on the table of their most ardent advocates.

Interesting topic.

- I like Jed a lot, but he often tweets about his private life. I wouldn’t mind, but the problem is that I follow 70 people, and if they all start tweeting about what they had for breakfast, then it becomes Hell on Earth to use Twitter.

- John Delaney is sometimes interesting, but he re-tweets the InTrade RSS feed, which I am already a subscriber to in Google Reader. That is infernal to see 2 times the same info. To add salt to injury, the InTrade RSS feed always re-publishes a second time their feed items. I don’t know why they do that. It is really annoying. So if you subscribe to John Delaney’s Twitter feed, who re-tweets the InTrade feed, then you get the same thing 4 times in a row. It is the craziest thing I have ever seen on the Web. Plus, John Delaney now uses a script to follow every person who follows him —a standard tactic used by the Twitter spammers. It is a bad thing to do.

Addendum:

- Felix Salmon and Tim O’Reilly make a good usage of Twitter. And Felix Salmon is smart enough to poll his people about his Twitter usage.

- A sales leader.

Crowdcast is the leading provider of prediction market solutions created exclusively for the enterprise.

Hummm… The leaders are NewsFutures and Inkling Markets. But maybe CrowdCast will take the lead, later on, that well might be. Jed Christiansen wants to set up some kind of procedure to assess the size of the EPM industry. It might work at the condition that everybody tells the truth. If you have one liar in the set, it will derail the whole process, because the others will get to lie, too. Tricky…

The most urgent task, though, as I have repeated here, is to publish specific business cases that justify the use of our information aggregation mechanisms.

#1. (Public or enterprise) traders mainly bring to the exchange some bits of information they acquired from some official or semi-official sources. The enterprise traders bring in the information they got from second hand, mainly. Few of them are in direct contact with the facts in question, or know the big picture. They also bring their bias, granted.

#2. Enterprise prediction markets are not the only thing “completely different to anything they’ve ever encountered [before]“. If you think of it, the Internet was “completely different”, too. Yet, the companies have all established an Internet presence and are all trying to market thru the Web. If EPMs have not yet been adopted, it is because a) their advocates have greatly exaggerated their benefits b) their advocates have not been specific enough as to when and where exactly EPMs can make a difference.

#3. If the EPMs “do the same thing differently” (I concur), then their advocates should go on the record as to why and when using traders is so beneficial to the forecasting process.

#4. When people hear about the wisdom of crowds in the media, in articles about prediction markets, it is in relation to that damn alleged added accuracy. I didn’t invent that.

#5. Surely. But do those 16 traders remain active after the novelty has worn off?

Jed comes out as a very reasoned and reasonable person. Good point for him.

Number one, I don’t understand why information aggregation would be a “bottom-up” approach (as opposed to “top-down”). Our traders bring bits of information to the market —but these bits of information were originally produced by the traditional sources (news, political polls, political forecasters, opinion leaders, etc.). I don’t understand why this “bottom-up” metaphor would apply to the prediction markets. Generally speaking, I hate metaphors.

Number two, according to Jed, the slow adoption of enterprise prediction markets would be due to the “cognitive dissonance” that they provoke in the (weak) mind of the (freal) business managers. In other words, EPMs are such a novelty, and the corporate forecasters such a bunch of retarded people, that it will take decades before commercial organizations get to adopt the prediction market tool.

The reality is different.

1. As one can plainly see, the Americans love technology very much. For instance, it took less than 2 years for the iPod, the iPhone, FaceBook, or Twitter, to reach mass adoption. When a brand-new technology is truly awesome, the Americans are quick to acquire it. If enterprise prediction markets were such a revolutionary and powerful forecasting tool, it would have found a market already —just like the iPod, the iPhone, FaceBook or Twitter did.
2. The benefits of enterprise prediction markets have been over-hyped by a bunch of Ivory Tower economic canaries who have no experience whatsoever in forecasting and business administration.
3. The added accuracy of the enterprise prediction markets is marginal —and anyway does not fill the gap with omniscience (contrary to people’s expectations). The value of EPMs lays in some specific situations where the competitive forecasting tools have limitations. As of today, to the notable exception of Inkling Markets [deep respect to NewsFutures and CrowdCast, anyway], prediction market consultants have been beaming out generalities about markets that play well with some business media, instead of publishing case studies.
4. The hurdles of running enterprise prediction markets have not been disclosed fully to the public. The main challenge is to find enough active traders. Remember than InTrade (who aims at the Americans) is powered by a few thousands of active traders, and BetFair (who aims at the British), by a few hundreds of thousands. Let’s remember that America is populated by 300 million people, and the United Kingdom, 60 million. In both countries, only a very small part of the population engages in event derivative trading — far less than 1%, and it is closer to 0% than to 1%, actually. In the context of a Fortune-500 company, which is of course much smaller than a country, the pool of potential active participants whose trading activity is sustained over time is quite tiny.
5. The field of enterprise prediction markets does not need to turn every Ivory Tower economic canary into a “chief scientist”. What companies need are Chief Forecasting Officers, who will analyze, impartially, for each specific situation, which tool is appropriate —a traditional forecasting tool (most of the times), or the EPM solution (at times). This analysis should not be done by a prediction market afiscionados, who has a bias, but by a professional and scientific forecaster who can do a benefit/cost analysis of each tool for each specific situation. EPMs will take off when the consultants and managers cease to be mezmerized by the economic canaries and start getting down and dirty with business cases in each industry.

UPDATE: Jed’s reply

UPDATE: My reply

[...] When it comes to the first point, forecasting something that the company already forecasts, prediction markets may or may not be an excellent solution. I’ve seen one set of markets that absolutely blew away the accuracy of current forecasts, and I’ve seen other markets that were consistent with current forecasts with little or no accuracy edge. [...]

Care to say more about what is the determinant of an EPM success?