Markets Rule, Even in Politics

This is a line from L. Gordon Crovitz’s opinion article in the Wall Street Journal called “Trading on the Wisdom of Crowds” from April 28th. Prediction markets have been popular posts here on talkDIG the last couple of weeks and I apologize if I am sounding like a broken record. But the topic seems to be appearing every where. I rarely read the opinion section in the WSJ, but the title caught my eye. Crovitz discusses the topic of prediction markets and the deadly accurate Iowa Electronic Market. Now, if you think prediction markets are a fairly recent phenomenon, think again. According to Crovitz, some $165 million in today’s dollars were wagered on the 1916 election where Woodrow Wilson defeated Charles Evans Hughes.

One interesting topic that Crovitz raises is the difference between using the traditional form of predicting political results, statistical polling, and using a prediction market that trades future results like stocks. There are plenty of examples that prove that a properly formed market will provide more accurate results then a statistical polling sample set.

Are you convinced yet that prediction markets can be an effective tool for your organization? Have you identified any areas, either internally or externally where a prediction market can more accurately predict an outcome?

Example Prediction Market for IT Projects

A colleague of mine forwarded me this great research paper on an example internal prediction market for an IT project. The research is not fully complete, but there were a few interesting nuggets that support the usage of internal markets for accurate predictions This is the topic that Bo Cowgill from Google will be presenting at DIG next month.

The research paper highlights 4 key needs for an accurate prediction market

1. Ability to aggregate information and knowledge from individuals
2. Incentives to encourage active participation
3. Feedback to participants based on market prices
4. Anonymous trading

The results from the case study were quite positive. Acxiom Corporation was the test case and used the Inkling Markets software to host the market to predict 26 milestone events of an internal IT project. Two results jumped out at me. The market was 92% accurate on the milestone events (24 for 26) and had an 87% participation rate (33 participants). There was also a higher perceived level of collaboration as a project team, which had positive impact on the outcome.

The authors of the paper are Herbert Remidez, Jr. Ph.D. and Curtis Joslin from the University of Arkansas. Looking forward to seeing further output from the research.

Politics: There's No "I" in "DIG"

What do sports, politics and DIG have in common? Well, of course, it’s prediction markets. There’s Protrade, and Tradesports and the Iowa Electronic Markets and, well, Las Vegas itself, kind of. But thinking across to the other themes of the conference, the similarities disappear. Much has been said and written about the use of data and analytics in sports (Moneyball, footballoutsiders.com, 82games.com), but the closest most politicos get to analysis is focus groups, commissioned polls and a cornucopia (or is it hodgepodge?) of cognitive biases (“we need to focus on ‘soccer moms!’”).

In the last few years, some individuals and organizations have begun to make a dent in this space; notably among them Get Out the Vote: How to Increase Voter Turnout by a couple of Yale professors who base their recommendations on actual research. More recently, Brendan Nyhan at Duke reports on his blog the founding of “The Analyst Institute,” which states as its mission “for all voter contact to be informed by evidence-based best practices. To ensure that the progressive community becomes more effective with every election, we facilitate and support organizations in building evaluation into their election plans.”

It’s not as if there isn’t incentive to win, and it’s not as if there’s a lack of interested funding. So why is politics behind the curve on data and analytics? Is there a rational (or irrational) belief that politics need to be managed by gut? Or are there structural reasons? Or am I mistaken in thinking politics is late to the game, and that McCain is hiding the next Billy Beane somewhere on the Straight Talk Express?

Prediction Markets Explained

Last week, Mark Lorence posted a topic for discussion on prediction markets and questioned if it would have been an effective tool for British Airways in the opening of the T5 terminal in London. I wanted to provide a quick follow up, as the topic of prediction markets was in the NY Times yesterday with references to different organizations that are using them to predict sales forecasts, store openings and project completion dates.

If you have an interest in the software and services companies who provide platforms to facilitate a prediction market, you should check out Inkling Markets, Consensus Point and NewsFutures. Each company provides the technology and infrastructure to setup and manage prediction markets. To give you a sense of the type of problems that a prediction market can be used for take a look at the Inkling Markets home page. They have examples such as "Improve Forecasting of Performance Indicators", "Expose Quality Problems" and "Predict Risk in Your Supply Chain". All real issues that many organizations need to address.

If you want to see how a prediction market may work for something like sports, politics or weather, I would recommend taking a look at TradeSports.com. You could argue this is simply a gambling website since the trading is performed with real money, but if you look a little closer you will find some interesting information. For example, according to the current "2008 Democratic Presidential Nomination", the current trading price for Barrack Obama is 85.5, which means that 85.5% of the market predicts that he will be the democratic nominee. In other words, the "market" strongly believes he will be the nominee. If I were to purchase options at this price and he were nominated, I would earn $14.5 per block of shares ($100 - $85.5) I purchased. If he did not receive the nomination, I would lose my entire investment since the value would be $0 when the market expires, which should be August 28th at the DNC.

Bo Cowgill from Google, who is a speaker at the DIG 2008 conference, runs Google's internal prediction markets. He is also an expert on the topic and operates his own blog on the topic of prediction markets. Also take a look at Midas Oracle. We are looking forward to hear Google's story from Bo at the conference.

One interesting side note is that there is a market on TradeSports.com for Google's Lunar X project and if it will be won on/before 12/31/2012. The current price is 24.3.

Predicting Lost Luggage

I read an interesting article on prediction markets by Gary Stix in the March, 2008 issue of Scientific American. The bulk of article discusses the success rate of the Iowa Electronic Markets in predicting election results based on buying and selling “securities” – portfolios of contracts for both candidates. In presidential elections from 1988 to 2004, the Iowa Electronic Markets have predicted final results better than the polls three times out of four.

The article provides a great description of how the market works. It also highlights other prediction markets that allow speculators to predict almost any conceivable event, from a Chinese moon landing by 2020 (Foresight Exchange) to Katie Couric departing from CBS News (Intrade) to the first human-to-human transmission of avian flu (Avian Influenza Prediction Market).

While these events are important, and might be fun to risk a few dollars on prediction, I was most interested in the internal markets that are being established to gauge the success of business efforts:

“Attracted by the markets’ apparent soothsaying powers, companies such as Hewlett-Packard, Google and Microsoft have established internal markets that allow employees to trade on the prospect of meeting a quarterly sales goal or a deadline for release of a new software product. As in other types of prediction markets, traders frequently seem to do better than the internal forecasts do.”

I wonder whether an internal prediction market may have help with the disastrous opening of Heathrow Airport’s new Terminal 5. Despite headlines like this:



they clearly weren’t ready for their opening week - hundreds of cancelled flights, thousands of lost bags, and a financial and PR nightmare for British Airways and BAA.



There has been a lot of Monday-morning quarterbacking (or the equivalent soccer term) about the decision to open the new terminal in “big bang” fashion. Critics have suggested a phased approach might have reduced the problems, and citied other major infrastructure projects (like the new St. Pancras rail station) as examples. I’m guessing that the executive team considered both options and researched other airline terminal openings before making their decision. (I remember when the new Pittsburgh airport opened in 1992; the last flight landed at the old airport about 10 pm, and army of people and moving vans transferred all the operations equipment to the new terminal about a mile away, and the first flight landed at the new airport at 6:00 am. Despite some initial problems with the automated baggage-handling systems, this big-bang approach went much more smoothly that Heathrow’s.)

Would an internal market, reflecting the collective knowledge of the Heathrow employees, have predicted such a chaotic opening? Experts still don’t know exactly how prediction markets work. I’m wondering whether the accuracy might have something to do with the “degree of influence” the market participants have over the outcome.

For many events – like predicting the amount of snowfall in Central Park, or the outcome of the NCAA tournament games – a trader has no influence over the outcome and is, effectively, guessing.

For other events – like predicting an election outcome or the success of a new movie – a trader has limited influence. An individual vote influences election results (unless you’re a Republican living in Massachusetts). A person can attend the opening of a movie and tell all their friends how great it was.

Most intriguing are those events where traders have significant or considerable influence over the outcome – the sales manager responsible for meeting the quarterly target, the project manager trying to launch on time, or the baggage handlers at Heathrow who not only have to use the new systems but have to show up at a new location before they even see their first bag of the day.

Is there a correlation between “amount of influence” and “accuracy of prediction?” Can markets provide field-level insight that executives can’t (or won’t) see? If a “Terminal 5” market had existed and “successful opening” contracts were trading at low prices, would BA chief executive Willie Walsh have used this information to delay the opening, conduct more testing, and phase-in new operations over time?

Does your company use prediction markets? Have they been successful?

NCAA Update: Well, the Selection Committee looks pretty good as – for the first time in NCAA men’s basketball history – all four No. 1 seeds are in the Final Four. Would a prediction market have helped? According to this news story,

“…of the 500,000 fans playing on CBSSports.com, more than 51,000 correctly predicted the final four teams…”

Assuming that some of those 10% were basketball junkies while others picked their brackets based the team’s jersey colors, can we can draw any conclusions about a “wisdom of the crowd” factor in the NCAA tournament?