Why don’t more businesses use prediction markets?

Last week in The New York Times (TimesSelect), Joseph Nocera quoted Robin Hanson as saying private businesses had not made a breakthrough with the use of idea futures.  It seems natural to let your employees bet on future business conditions, the success of product lines, or broader questions of corporate strategy.  Microsoft and Google and a few other companies have played with the idea, but it does not (yet?) seem to be taking off.  Why not?

1. Prediction markets threaten the hierarchical control of top managers.  It would become too obvious that most managers are idiots, unable to predict the future.

2. Prediction markets make a big chunk of the bettors into "losers."  Yet within a company morale is all-important.  Businesses proceed by soliciting feedback, and by reshaping their plans to pretend that everyone is on board and has an ego stake in the final outcome.  Prediction markets make this coordination more difficult.  Once people make bets, they start rooting for their bet to win and for the other bet to lose.  They move away from maximizing the value of the firm and develop an oppositional mentality vis-a-vis other employees.  Furthermore it is disruptive to have a running tally on who are the winners and losers each day.

3. No matter what they pretend, businesses are not much interested in forecasting many future variables.  Successful businesses find product markets they can control for long periods of time.  They do a few things really well, and let a surprisingly large number of tasks slide.

4. We already have implicit betting markets in the form of resource prices.  When the information contained in those prices is sufficiently important, institutions will be organized in terms of "markets," rather than "firms."  Or firms can look at resource prices in outside markets for the information they need.

5. Most employees have no rational basis on which to bet.  If someone knows the truth, but is otherwise locked out from credibly signaling that knowledge to management, something is wrong with the organization of the company.  The small prizes from corporate prediction markets won’t be enough to elicit that knowledge from him in any case.

6. The corporate beast is far more constrained than most outsiders imagine.  Interest groups must be courted, coordinated, and sometimes fought every step of the way.  When it comes to choice, there are fewer degrees of freedom than one might think.  The real question is not what to do, but rather having the will and effectiveness to do it.  A bit like international free trade, no?  Prediction markets don’t help much in this regard.

7. When reward systems are created, employees view them as a means to distribute further privileges to insiders and favorites.  Prediction markets would be viewed the same way and in fact this might be true.  Who else is going to win all those bets?  Do corporations really need more insider favoritism?

Your thoughts?  Here are five open questions about prediction markets.


I nominate:
8. Regulations, both from government regulators and from internal ethics policies. Most companies take aggressive steps to prevent anyone from profiting from either inside information, front running, or side deals with outside customers and suppliers. Letting people profit from information via prediction markets goes against the spirit of these ethics rules and could in some case provide an incentive for rule breaking. Even worse, Sarbanes-Oxley and SEC disclosure rules could provide criminal penalties for CEO's who tell the world something different from what the internal prediction markets are saying.

It is no surprise that Microsoft and Google would be interested in prediction markets, as both companies have reputations for playing fast and loose with government regulations (Microsoft for antitrust, Google for copyright and their pre-IPO quiet period interview with Playboy). [Note that I am just summarizing some common opinions of these companies; I am not judging their actions, nor am I alleging any actual violations, nor do I have any nonpublic knowledge of either.]

Old economy companies are more careful. I work at a bank, and I'm just glad they haven't banned visiting or commenting on blogs yet.

To some extent this is present in (2), but perhaps it could be spelled out a bit more. To what extent would such markets introduce bad incentives? For example, suppose I bet (sorry, "predict") that a product I'm working on will have a late release date? or will fail commercially? Someone has to bet against success for these markets to be interesting, and such bets do not encourage whole-hearted commitment to success.

1 (a): Many managers assume they know they know at least as much about the state of the world as any of their employees (after all they are 'in charge') so why ask?
1 (b): Managers think they provide the same function by asking their suboridinates (and recursing through the organization) their beliefs and aggregating the response. The incentives however may be quite different when talking directly to your boss versus logging on to an internal prediction website.

Other reasons:

Size. It takes a 'large enough' business unit for the aggregation benefits to show up. Obviously there are a number of companies large enough but it's usually smaller companies that are willing to attempt innovations like this first.

Cultural norms. If you thought the project was going poorly why didn't you tell management instead of betting against your company's success? Aren't you a team player?

In any non-annonymous market reason 6 is going to be a big factor. Who wants to bet against the boss? If you do is it better to be right or wrong?

Tom Slee's point above about incentives is a good one.

You'd need to cap employee's bets below their bonuses, so that it was always better to increase performance, and the betting market could be used only to "hedge" against a management predicition that is too high or "double down" on a prediction that is too low.

The other danger is that since other aspects of compensation are tied to "meeting targets" employees may systematically climb on the short side of the market as hedgers. You'd need to find a way to account for the risk aversion of everyday people.

Here's an example of a set of *public*, real-money business prediction markets aiming at the release date of the PS3 machine.

So maybe the answer to Tyler Cowen's question is:

10. Business prediction markets already exist, but Tyler Cowen hasn't noticed yet.

[Under my name, link to the InTrade/TradeSports PS3 prediction markets.]

on General Motors prediction markets...this has been around for a long time ,it's called cds [credit default swaps]

JC Kommer,

Fair remark (on the 'credit default swaps'). However, with prediction markets, there's openness and the interpretation is easy. Prices (0--100) can be understood as probabilities. My 4 year-old nephew can understand that. Can you say the same with swaps or with traditional futures markets?????

I go with a variation of (3) and (5). Prediction markets would only work if a large number of people are participating in them, but opening up prediction markets and encouraging an internal workplace culture of using them to the extent that they can be effective, is going to divert employees from more productive tasks. (8) is huge, too -- see Ribstein and Butler on Sarbanes-Oxley at the March 13 AEI event.

In a corporate setting, if everyone above you has a vested interest in a certain outcome, and you correctly predict that the outcome will not happen, you will be punished and possibly fired. In many large organizations, being wrong when everyone above you is wrong too is fine, being right when everyone above you is wrong is dangerous.

On the market makers/uninformed traders issue:

Below are excerpts from "Five open questions about prediction markets" - by Justin Wolfers and Eric Zitzewitz - (2005-01-21) - 2006-02-00

1. How to attract uninformed traders? Counterintuitively, the problem for most prediction markets is attracting sufficient uninformed order flow.

An important implication of the model sketched above is that the success of the prediction market in generating trade depends critically on attracting uninformed traders. --- Risk love or the “thrill of a gamble† provide obvious motives for uninformed traders, and both Tradesports and Betfair have successfully attracted many sports bettors to their markets. --- As the wonkishness of the contract rises, however, volume and liquidity falls rapidly. --- To summarize, three routes to attracting order flow have been successful thus far: offering sports betting, subsidization, and, possibly, exploiting career concerns. Each has their drawbacks, however.

As a supplier of prediction market software, I think more work needs to be done educating the marketplace about this methodology. Articles like this one and books such as "The Wisdom of Crowds" have done *much* to advance the concept but you'd be surprised at how many executives I talk to know nothing of prediction markets and the value that they can bring to the organization.

The existing software options have also impeded wider adoption. While they work well in academic settings, many prediction market platforms have clunky interfaces which are hard for corporate clients to use. From our experience, the markets with the simplest users interfaces have also been the most successful.

James Surowiecki wrote: "In other words, [marginal traders] do not have enough capital to set prices." & "But this does not make them price setters."

From what I read from the IEM papers, I disagree on the ground that the Joe-Six-Pack traders (a.k.a. the typical traders) are more likely to *accept* prices proposed by the market makers (a.k.a. marginal traders). And even though it's true that the market makers "control a small fraction of the amount of capital invested in the market" (as James Surowiecki wrote), since they trade like a machine gun, they very often *propose* prices.

Note the final line, in the paragraph below: "Marginal traders, not average traders, drive market prices and, therefore, predictions."

The excerpt below is from "Results from a Dozen Years of Election Futures Markets Research" - page 6 - by Joyce Berg, Robert Forsythe, Forrest Nelson and Thomas Rietz - 2000-11-00 - [Link to the PDF file under my name.]

"Specifically, the core group of traders that tend to set market prices appears less biased and error prone than typical traders. [T]ypical traders have unrealistically hopeful beliefs for their preferred candidates []. However, 'marginal traders (those who regularly trade or place bids and asks near the top of the queues) are much less prone to this bias. [T]ypical traders often trade at a price that is not the most advantageous price for the trader or that violates arbitrage restrictions. Such 'mistakes' are 'irrational' because they decrease the trader's payoff regardless of expectations or outcomes. However, 'market makers' (those who actually set market prices by placing the best bids and asks) make mistakes much less often. [...] Marginal traders, not average traders, drive market prices and, therefore, predictions."

Surowiecki is right about "marginal traders." Sorry, market makers do not set or control prices, except in conspiracy theories. You can't set prices unless you have a real demand or supply curve. The classic market maker (e.g. on the floor of the NYSE) has no demand for stock, relatively little capital, and usually tries to have zero net stock holdings at the end of each trading day. Instead, the market maker supplies liquidity, by quoting bid and ask prices around the aggregate of other traders' supply and demand curves, which the market maker learns by observing order flows. The price setters are Fidelity and other big stakeholders with their own real views on the market, and supply and demand curves reflecting their views.

Prediction markets work the same way, although since they are smaller than US equity markets, the players are less specialized, and you are more likely to find people who blend market making with committing real capital to specific ideas. As prediction markets get larger, IMHO, you will see increasing specialization into passive market makers and people with views.

What if we viewed predictor markets as a sort of futures market? They both have that predictive quality.

From my basic knowledge of futures markets, the majority is often wrong. It's only a small minority who's walking aay with the cash.

But I guess a predictions market isn't a zero-sum game, is it?

There's no reason that it has to be: a company could give each employee a small pot with which to play to create some liquidity let people add in more if they want: you're right it's zero sum ex-post but not at the ex-ante ztage (though the firm pays something to encourage participation, however if these predictions are worth as much as some of y'all are claiming then it's worth it)?

The question is premature; it's like asking in 1975 why more firms don't use overnight shipping. (Fed ex began in 1973).

How many firms really need overnight shipping?

Wouldn't overnight shipping cause managers to have to work harder, so they oppose it?

Firms don't want overnight shipping because then employees will procrastinate.

See how easy this is? In reality prediction markets are not very old, most managers have never heard of them and yet they have already scored huge successes. Much greater success, I might add than Tyler predicted many years ago when I first handed him a paper by Hanson!

Time will tell but the simplest explanation is that Rome was not built in a day;


(Tyler and I discussed this topic a few weeks ago over lunch. A lot of good comments here; sorry I was away on travel and didn't comment till now.)

Tyler's options 2,4,5, & 7 are not very plausible (on 2, markets can be subsidized so that most everyone wins). Concerns of DK on regulation, Tom Slee on bad incentives, Trevor on retribution, and Ted on time diversion are relevant, but in practice can be overcome (See my paper on foul play).

Tyler's options 1,3, & 6 are more plausible. Management is generally more about theatre and politics than decision theory; while managers cultivate a heroic knowledgeable-decision-maker image, they correctly see their key role as more political and strategic that informational.

The main problem today is, as Emile notes, a lack of actionable topics. Most prediction markets have been weak-incentive play-money markets on cute simple topics of broad appeal. These avoid disruption to existing corporate politics and culture, and let firms join the prediction market fad, but are usually not of great decision-making value. Alas, these fads can end as quickly as they begin, and I fear that if no firm is heard to have made millions in decision-value within two to four years, the story will be that this method was tried and failed.

Nevertheless, many key corporate decisions could benefit greatly from such markets, and as Alex implicitly forecasts, some managers will eventually be celebrated *because* they decided to adopt decision markets. Someday, such markets will directly advise key decisions such on mergers, divestitures, subcontractor choice, promotions, demotions, and product introductions, adding billions of dollars in decision-value.

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Have a great day

In a corporate setting, if everyone above you has a vested interest in a certain outcome, and you correctly predict that the outcome will not happen, you will be punished and possibly fired. In many large organizations, being wrong when everyone above you is wrong too is fine, being right when everyone above you is wrong is dangerous.

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