Do businesses need enterprise prediction markets?

Competitive advantage can be obtained either by differentiation or by low cost. Enterprise prediction markets certainly don&#8217-t foster the innovation process, and they are surely not the cheapest forecasting tool. EPMs require special software, the hiring of consultant(s), the participation of all, and a budget for the prizes. EPMs are costly, and they take time to deliver. As of today, I can&#8217-t see why any sane CEO should be implementing EPMs as a decision-making support. At the contrary, I would say that any sane CEO should fire any employee who tried to sneak in internal prediction markets, and should dismember any existing corporate prediction exchange. Right now.

It has been suggested that EPMs have helped Best Buy getting it right on the ‘HD-DVD versus Blu-Ray’ issue. It&#8217-s a boatload of bullsh*t. I know a lot about technology intelligence. It should be done by a smart and curious operator. There is no need of enterprise prediction markets to do this task. The tools you need consist of a bunch of IT news aggregators and a good search engine. Consider this:

The Inevitable Move Of iTunes To The Cloud

In the &#8216-cloud&#8217- piece above, there are facts and there are speculations. You&#8217-ve got much more technology intelligence reading the &#8216-cloud&#8217- piece above than you would get from a crude, plain and simple prediction market. Gimme a break with EPMs. Make no sense at all.

Contrast EPMs (which are costly) with public prediction markets (a la InTrade or BetFair), where probabilistic predictions are offered for free. That makes all the difference for the reason that the added accuracy brought by prediction markets is very small. Market-generated odds are handed out for free to journalists &#8212-still, few of them take the bait. The market-powered crystal ball is worth peanuts.

The reason CEOs are paid millions is that only a small percent of the population of business administration managers has the ability to cut through the non-sense and the balls to cut the cost of the non-sense. It is a rare skill. I am calling on CEOs to end EPMs. Right now.

Why CrowdCast ditched Robin Hansons MSR as the engine of its IAM software

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Leslie Fine of CrowdCast:


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.


Nota Bene: IAM = information aggregation mechanism

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

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The truth about (enterprise) prediction markets

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Paul Hewitt:

[…] In virtually every case, the prediction market forecast is closer to the official HP forecast than it is to the actual outcome. Perhaps these markets are better at forecasting the forecast than they are at forecasting the outcome! Looking further into the results, while most of the predictions have a smaller error than the HP official forecasts, the differences are, in most cases, quite small. For example, in Event 3, the HP forecast error was 59.549% vs. 53.333% for the prediction market. They’re both really poor forecasts. To the decision-maker, the difference between these forecasts is not material.

There were eight markets that had HP official forecasts. In four of these (50%), the forecast error was greater than 25%. Even though, only three of the prediction market forecast errors were greater than 25%, this can hardly be a ringing endorsement for the accuracy of prediction markets (at least in this study). […]

To the despair of the Nashville imbecile, Paul&#8217-s analysis is quite similar to mine (circa February 14, 2009):

The prediction market technology is not a disruptive technology, and the social utility of the prediction markets is marginal. Number one, the aggregated information has value only for the totally uninformed people (a group that comprises those who overly obsess with prediction markets and have a narrow cultural universe). Number two, the added accuracy (if any) is minute, and, anyway, doesn’t fill up the gap between expectations and omniscience (which is how people judge forecasters). In our view, the social utility of the prediction markets lays in efficiency, not in accuracy. In complicated situations, the prediction markets integrate expectations (informed by facts and expertise) much faster than the mass media do. Their accuracy/efficiency is their uniqueness. It is their velocity that we should put to work.

Prediction markets are not a disruptive technology, but merely another means of forecasting.

Go reading Paul&#8217-s analysis in full.

I would like to add 2 things to Paul&#8217-s conclusion:

  1. We have been lied to about the real value of the prediction markets. Part of the &#8220-field of prediction markets&#8221- (which is a terminology that encompasses more people and organizations than just the prediction market industry) is made up of liars who live by the hype and will die by the hype.
  2. Prediction markets have value in specific cases where it could be demonstrated that an information aggregation mechanism is the appropriate method that should be put at work in those cases (and not in others). Neither the Ivory Tower economic canaries nor the self-described prediction market &#8220-practitioners&#8221- have done this job.

The worlds #1 resource on enterprise prediction markets

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– Do not waste $400 on a &#8220-prediction market conference&#8221- run by a San Francisco clown and attended by suckers.

– Quit listening to the Ivory Tower economic canaries who are over-hyping the prediction markets &#8212-and have no experience whatsoever in the field of forecasting.

– Instead, do read this Inkling Markets resource, and do grill Adam Siegel on the phone. It is free, and he is the Real McCoy. [I hope that NewsFutures and CrowdCast will soon provide the same kind of EPM dossier on their respective website.]


Enterprise prediction markets… the next big thing -not.

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Niall O&#8217-Connor:

A previous Economist article, that I have archived, spoke of how Napster was revolutionising the music industry. Another one, called Betfair a radical upstart. A recent article on Hulu discussed how it was “online videos new model.” By anybody&#8217-s standards, these technologies have unleashed the forces of disintermediation, and affected a paradigmatic shift in the industries in which they operate.

By way of contrast, the Economist article on Prediction Markets states that Koch, one of the biggest users of Prediction markets, asserted that they are a compliment to other forecasting techniques and not a substitute to them. The article aslo raises the issue of cultural barriers that are inhibiting the take up of said Prediction Markets – not least, inertia (etc..).

One can take from the article that Prediction markets are not ground break, not radical, not revolutionising- they are not unleashing the forces of disintermediation. Accordingly, on the evidence presented (”much remains to be done to convince sceptical managers of their value”) the battle is an uphill one. Moreover, one can ask, if the battle was not won during the good times, what is the real chance that it will be won during a recession, when company’s are always more resistent to change.

You guys are all speaking from a position of being laden down with prediction market baggage. Your views are not objective, and one can only hope that you are not collectively suffering from disaster myopia. […]

Niall O&#8217-Connor&#8217-s website

Enterprise prediction markets: Usability innovation is the answer.

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This past week, The Economist wrote on the yet-unfulfilled promise of prediction markets. At CrowdCast (ex-Xpree), we believe prediction markets are not yet mainstream because the current solutions are built on mechanisms designed for the stock market, not for the enterprise.

The stock trading metaphor works for a large, liquid stock market, but is unsuitable for enterprise forecasting. The concept of shorting and covered calls is far from intuitive for your average employee, and the stock mechanism makes it hard to ask the simplest of questions relevant for corporate forecasters. For example, buying or selling a collection of virtual stocks representing probabilities of sales falling in particular ranges is an incredibly obtuse way of asking for a single sales forecast. Finally, the stock mechanism relies on copious liquidity to ensure meaningful metrics, which is often not available with the limited crowds available in the enterprise.

However, innovation moves on and we question the assumption that prediction markets have to rely on the stock market analogy. At CrowdCast, we have been working on a new mechanism, that takes into account participant behavior and aptitude as much as market efficiency. The product we are launching in April will deliver easy, engaging, and expressive information exchanges, without the limitations of traditional notions of stock markets.

When you get the questions, incentives, and mechanism right, a prediction market can be an incredibly powerful management tool. Employees share insights anonymously and are measured and rewarded for their intelligence. Widely deployed, this has the potential to fundamentally change the nature of the organizational contract, moving from information flow based on hierarchy and silos, to enterprise-wide direct communication.

A whole new take on prediction markets- available from CrowdCast in April 2009.

Mat Fogarty

CrowdCast CEO

Cross-posted from the Xpree blog

Previously: Are collective intelligence solutions being oversold?

Inkling Markets CEO Adam Siegel speaks out on the current state of enterprise prediction markets.

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Adam Siegel:


You are right to question this stuff. There is a lot of bullshit out there and frankly I cringe when I see articles or statements about the “accuracy” of markets because it hurts everyone in the long run. It’s why we’ve written 3 or 4 times on our blog about what “accuracy” in a marketplace really means – that you can’t just look at 5 or 10 markets and say “we nailed it.” Unfortunately it’s something we have to deal with because the application is called a “prediction” market after all so it’s the first question that naturally comes to mind. That said I wish Chris wouldn’t make blanket statements [*] about “the vendors, e.g. Inkling Markets” getting the use cases all wrong in enterprise prediction markets. Because frankly, for quite some time “accuracy” has been a secondary argument to a number of other advantages we discuss about markets (in fact on the page on our website that describes the value proposition to companies, we don’t even list “accuracy” as a key benefit). This is also an expectation we set with our clients right from the beginning.

Anyways, I made the statement about business increasing year over year based on our own experience/numbers and as Jed mentioned, by looking at the activity of some of our competitors who have made hires, added clients, etc. I also base the statement on the types of professional services companies we are working with/hearing from and our discussions about prediction markets and what they are going to try and do in the future. I don’t think so many would be interested in adding markets to their toolset and expending resources putting together offerings if they didn’t see them as a long term, worthwhile business capability. So for those that agree with Chris that 6 years is enough time to evaluate a new business capability, I’d like to politely disagree. I could be wrong but these things haven’t been used beyond the experimental/pilot stage in companies for more than 2 or 3 years. We’re just at the cusp of understanding what benefits they’re going to bring. We’ve seen some promising trends, we’ve also seen people try to use Inkling for something and it failed miserably. This is just standard lifecycle stuff, especially for a capability that is designed, as I said in my blog post, to bring about more transparency and break down organization barriers.

[*] Adam, it was not a &#8220-statement&#8221-, it was a 2-choice hypothesis.


An uncertain future – A novel way of generating forecasts has yet to take off. – by The Economist – 2009-02-26

How vendors are scuttling the field of enterprise prediction markets -and the prediction market industry, as a whole

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The danger of vendor conferences without any editorial line: It backfires against the whole prediction markets industry &#8212-big time.


I warned my readers many times against the vendor conferences organized by the San Francisco man. He is so desperate that he invites anybody who will pronounce the word &#8220-prediction&#8221- and &#8220-markets&#8221- in the same paragraph. Many of the invited speakers haven&#8217-t the slightest knowledge of the field of prediction markets. As for the vendors, they are incapable of producing one single case study featuring a success in the use of enterprise prediction markets. Not a single one. (And I won&#8217-t mention the &#8220-flow of information&#8221- &#8212-the worst research ever published on prediction markets.) Their vendor websites publish lists of clients, which, at first glance, look impressive, but many of those so-called customers are in fact ancient clients who have ended pilot programs years ago. To add insult to injury, this fake conference is sold $400 to gullible attendees. It is not even worth 4 cents.

The Economist reporter who attended the San Francisco conference realized what I [*] realized long ago: The field of enterprise prediction markets is all smokes and mirrors. The more the prediction market vendors will participate in such crappy conferences, the more the media will realize that the prediction market vendors are all hat and no cattle, and the more they will publish news stories bursting the prediction market bubble. And in the end of 2009, we will end up with 10 news articles in major media telling the world that prediction markets were a fad. Live by the hype- die by the hype.

The only way to get out of this debacle is to come back to basics: Do the research right, do discover the real value of enterprise prediction markets (velocity), and, then, only when you have something to show for it, go out in postings and conferences.

[*] I follow the field of prediction markets since 2003. I saw it in all shapes and stripes. You can fool your mother, but you can&#8217-t fool me.


An uncertain future – A novel way of generating forecasts has yet to take off. – by The Economist – 2009-02-26

– But although they have spread beyond early-adopting companies in the technology industry, they have still not become mainstream management tools. Even fervent advocates admit much remains to be done to convince sceptical managers of their value.

– Koch says the results so far have been pretty accurate compared to actual outcomes, but stresses that markets are complementary to other forecasting techniques, not a substitute for them.

– A big hurdle facing managers using prediction markets is getting enough people to keep trading after the novelty has worn off.

– Another reason prediction markets flop is that employees cannot see how the results are used, so they lose interest.

Bosses may also be wary of relying on the judgments of non-experts.

The truth about prediction markets

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Come to the wonderful world of collective intelligence, wisdom of crowds, and prediction markets!&#8230- The sun shines bright, the market-generated predictions are vastly superior to the polls as election predictors, and the track record of the public prediction markets stretches as far as the eye can see. There are opportunities aplenty in the field of prediction markets, and the trading technology is cheap. Every working enterprise can have its own internal prediction exchange, and inside every exchange, a set of enterprise prediction markets that correctly predicts the future of business, which their happy, all-American CEO listens to. Life is good in the magic world of prediction markets&#8230- it&#8217-s paradise on Earth.

Ha! ha! ha! ha!&#8230- That&#8217-s what they tell you, anyway&#8230- &#8212-because they are selling an image (just as Bernie Madoff did). They are selling it thru their vendor websites, vendor conferences, vendor-inspired articles in blogs, newspapers and magazines, and interviews of vendor data-fed professors in the media.

The prediction market technology is not a disruptive technology, and the social utility of the prediction markets is marginal. Number one, the aggregated information has value only for the totally uninformed people (a group that comprises those who overly obsess with prediction markets and have a narrow cultural universe). Number two, the added accuracy (if any) is minute, and, anyway, doesn&#8217-t fill up the gap between expectations and omniscience (which is how people judge forecasters). In our view, the social utility of the prediction markets lays in efficiency, not in accuracy. In complicated situations, the prediction markets integrate expectations (informed by facts and expertise) much faster than the mass media do. Their accuracy/efficiency is their uniqueness. It is their velocity that we should put to work.

Here&#8217-s now our definition of prediction markets:

A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative represents the imputed perceived likelihood of the partially uncertain future outcome (i.e., its aggregated expected probability). A 60% probability means that, in a series of events each with a 60% probability, the favored outcome is expected to occur 60 times out of 100, and the unfavored outcome is expected to occur 40 times out of 100.

Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism &#8212-with or without an automated market maker.

Prediction markets enable us to attain collective intelligence. Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. The event derivative traders are informed by the primary indicators (i.e., the primary sources of information), like the polls, for instance. These informed speculators then execute their transactions based on their anticipations about the future &#8212-anticipations that will be either confirmed or infirmed.

The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other meta predictive mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other meta predictive mechanisms. A highly accurate set of prediction markets has little value if some other meta predictive mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate predictions on its topic.

PS: I am updating a bit the content of this webpage, over time &#8212-so as to finesse the message.

Obstacles to Prediction Market Adoption

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Harrah&#8217-s is setting up a pilot prediction market to forecast customer activity in one of its domestic casino operations. […]

Since the power of prediction markets hinges on effectively tapping into cognitive diversity throughout an organization, Page also argues convincingly that if members of a group do not have enough diversity in their perspectives, prediction markets can actually produce dismal results. […]

Until now, few of the companies sponsoring successful pilots or tests have deployed prediction markets on a broad or sustained basis. Why not? One explanation is that prediction markets are deeply subversive. After all, lots of midlevel executives are consumed with the task of forecasting. If prediction markets do a better job of it, doesn&#8217-t that discredit the efforts (and perhaps even the motives) of these executives? But as prediction markets shift their focus toward new knowledge creation, they may become less threatening within corporations. […]

I don&#8217-t buy this explanation &#8212-nor do I buy that other one.

My view is that we haven&#8217-t yet demonstrated clearly when and how prediction markets can be useful.