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Professor Andrew McAfee of Harvard Business School has been thinking and writing recently about what he calls “Enterprise 2.0″. It’s his structure to thinking about modern technologies in a business context, based on the ties between individuals within an organisation.

He describes Enterprise 2.0 as four layers, and one of those four is prediction markets. Prediction markets in his system seek to tie together and leverage the knowledge of people that have no other ties in the business. For example, a marketing guy may never know or meet the shipping & receiving manager, but they could both be trading on Quarter 4 sales of a key product.

Other technologies are used for people with different levels of ties. He matches strong ties with wikis, weak ties with social networking tools, and potential ties with blogging.

Professor McAfee goes into much more detail in his blog post on Enterprise 2.0 here. Additionally, he recently gave a speech at the Defrag conference, which was covered by zdnet here. In that speech he was quoted saying:

“There is a missing play here,” McAfee said. “I can’t think of a single reason not to deploy predictive markets.”

Perhaps even more exciting is that he’s teaching future MBA students at Harvard about these technologies. His Harvard Business School course 1550 will be addressing Google’s prediction market and how prediction markets fit into the concepts of management in the information age.

Readers of this blog are likely already convinced of the benefits of prediction markets. People like Andrew McAfee will help convince future business leaders that their employees can be used to provide companies with better business information and make better business decisions. Steps like this are important and good signs for the prediction market industry.

It seems that each month brings one or two new entrants to the prediction market software industry. (I can’t bring myself to use the term “space.”) There is now a lot of variety in the industry, with well-established companies, open source options for the ambitious, and new entrants that are pushing the envelope of what we consider a prediction market. As a consultant that works with a number of these companies to help meet my clients’ needs, I thought it would be useful to review the options as of November 2007.

This is my review of the different software available. Please comment below or contact me with comments, criticism, or corrections. All views below are mine and mine only.

I’ve tried to address software that you can license/download to use on your site, as well as public sites. This post is long, but is comprehensive.

Top Vendors

All of the following prediction market software vendors are well established in the industry, and have a background of successful clients and projects. I have personally talked to or worked with all of these companies, and would certainly recommend any of them. They are listed in alphabetical order.

ConsensusPoint - ConsensusPoint licenses their ForesightServer software, either as a hosted, on-demand solution or on a server within your network. Written largely by Ken Kittlitz, the software has evolved over a number of years and with feedback from a significant number of clients. A particular benefit is the potential separation between the front-end user interface and the back-end market software and database. Depending on how much time and effort you want to invest, you can completely design your own user interface for a custom solution.

Who to talk to - Dave Perry

Gexid - Gexid is a new software package, and has been used by Nokia in a project run by Bernd Ankenbrand, who just finished his PhD. I don’t know much about the software, but Bernd had some interesting results that he presented at the London prediction markets conference. From what I understand Gexid integrates a good chunk of consulting effort to complete a prediction market solution. Company established in Germany.

Who to talk to - Bernd Ankenbrand

Hollywood Stock Exchange - HSX is still the most prominent play-money prediction market out there. It, too, has over ten years worth of development effort. From what I understand, using HSX as your prediction market platform is most suitable for quite large-scale projects. Their past clients include big media prediction markets associated with magazines, television shows, etc. The back-end tools around data reporting and demographics on the system are particularly powerful, as they are the core of the main HSX business.

Who to talk to - Alex Costakis

Inkling - Inkling is one of the “new” kids on the block, having only been started in fall of 2005. (It was developed and partially funded through Paul Graham’s Y Combinator program.) Developed using the Ruby on Rails platform/framework, it has a slick user interface and can easily be rolled out for your needs. A particular benefit is their recent automatic free trial promotion… just sign up on their site and get going!

Who to talk to - Adam Siegel

InTrade/Tradesports - While InTrade and TradeSports are two separate companies now, the same software platform powers them both. They have occasionally licensed this platform for use by other organisations. Most prominently, the Financial Times used the InTrade platform to run the FTPredict site this summer (as discussed at the London conference here.) Though it can potentially be a bit expensive, the biggest benefit of this software is the “battle-hardened” nature of the platform.

Who to talk to - John Delaney

Newsfutures - Newsfutures is one of the few veteran prediction market software platforms, having been originally developed in 2000. They have a strong team, and have developed further related products for companies that don’t feel comfortable with a strict prediction market. (These include their competitive forecasting and idea pageant products.) The benefit of Newsfutures is that they do have these innovative ways of getting the same information in a structure that may be more appropriate for a particular company.

Who to talk to - Emile Servan-Schreiber

Nosco - Nosco has been around for about 18 months now, and has developed a great looking suite of software packages around prediction markets and collective intelligence. They talked about these at the London prediction market conference, and they include a news exchange, idea exchange, and traditional prediction market. So far they’ve had two top-tier clients in Denmark. They clearly have an excellent web design and graphic design team; everything they produced (slides, screenshots) were extraordinarily well done. Company is established in Denmark.

Who to talk to - Jesper Muller-Krogstrup and Oliver Pedersen

Pro:kons - Pro:kons has been in the prediction markets business for a decade, in some form or another. Their work now consists of prediction markets and new media projects. They’ve done some impressive work getting a prediction market platform rolled out for Swiss public television to predict the recent Swiss elections. In order to do this, they had to work with seven different television station identities and four official Swiss languages! They also presented at the London prediction market conference. Company is established in Austria.

Who to talk to - Gunther Fadler and Peter Gollowitsch

OpenSource Options

A number of open source prediction market software packages have been developed over the years. The software listed below is Beta-level or more stable.

Zocalo - Zocalo is written by Chris Hibbert, who was partially supported by CommerceNet during one phase of the development. It is certainly still in development, and you can contact him for more details.

IdeaFutures (aka ConsensusPoint, version 1) - IdeaFutures is the original version of ConsensusPoint’s software. When the ConsensusPoint ForesightServer software was completely rewritten, the previous version of source code was open-sourced. Though clearly not as fancy as the current version, this is certainly a stable and well-used platform.

Serotonin - I’m not terribly familiar with this piece of software, but it is listed as a Stable/Production-level in SourceForge.

MarMix - MarMix is based on USIFEX, which was previously developed by Peter McCluskey. It’s listed as Beta-level in SourceForge.

USIFEX - USIFEX is a prediction market platform that is no longer running, but does openly provide the source code at the link above.

Idea/Innovation Management specific software

These companies/solutions don’t offer prediction market software, but do offer solutions that are close cousins - software for idea selection.

Rite Solutions - Rite-Solutions “Innovation Engine” software was featured in a New York Times article last year. While not strictly a prediction market, their software certainly embodies collective intelligence and crowd wisdom. Employees can submit new ideas, help fund ideas with play-money, and also help move the ideas ahead by completing small tasks that are necessary to move the project forward. In addition to an Idea selection software, it’s really an Idea Management software.

InnovateUs - Again, InnovateUs is not a traditional prediction market software, but uses funding and voting to help identify new ideas out of a pool. They have at least one great client, and are based out of Chicago.

New prediction market software sites

Some of these companies provide private markets for organisations, and some just maintain a public site. I’ve tried to detail the differences below.

PrediCom - PrediCom has been working with prediction markets for a few years, and they have their own platform. They don’t seem to do much work here, and their software is always tied into their consulting services.

Xpree - Xpree was started this summer by Mat Fogarty, who previously championed and ran prediction markets at Electronic Arts using Inkling. They have gotten a beginning version of their software running that you can trial here. Xpree is focusing on a solution that is extremely simply for people to use, to help encourage maximum participation in a business environment. (Mat discussed this at the London prediction market conference.)

Nimanix - Nimanix is a new prediction market software company headquartered in Tel-Aviv. They maintain a (lightly-traded) public market, and are actively selling their solution to business clients. Their software appears to be a strict CDA model, with no market maker.

Qmarkets - QMarkets is a new software company, and is headquartered in Tel Aviv. It is very similar to the Inkling model, with a public marketplace and quick & easy setup of subdomains on their network. The site is quite new, and there is currently little activity on the public site.

AskMarkets - AskMarkets has been developed by George Tziralis in conjunction with his PhD thesis. While currently in private beta, it will hopefully be rolling out soon.

Foresight Markets - Foresight Markets is yet another prediction market platform. While their website is up, it appears that the software is still under development.

New sites, not prediction markets, but “Wisdom of Crowds” generally

GuessNow - GuessNow is probably the most prediction market-like of all these sites, and many people might call it so. You can choose which outcome of an event you believe is most likely, and most importantly, express your confidence level. The more confidence you express, the more points you win if you’re right and the fewer points you win if you’re wrong. (In their scheme, you always win some points just for participating, even if you lose.) My only problem with the site is the number and size of the ads… it’s a little chaotic to my eyes.

Predictify - Predictify has been in the mainstream blogs a bit recently with a couple of mentions on the Freakonomics blog. Unfortunately, Predictify really isn’t a prediction market… it’s a sophisticated polling and market research mechanism. That’s not to say it doesn’t use the “wisdom of crowds,” just that some of the assumptions that James Surowiecki talks about in his book don’t necessarily apply. The reason I say it’s not a market is that a user cannot express their confidence in their prediction. It makes it difficult to sort out the knowledgeable forecasts from the un-knowledgeable forecasts. Unique about Predictify is that companies can submit market research questions, and those that predict right can win the fees that the company pays to Predictify for the listing.

Foretal - Foretal is an interesting site, and has been running for just a couple of months. It combines a Free side, where you can vote (not trade) on what you believe will happen in an event, with a Free and Cash side. Predictions that are Free and Cash have the Free/voting system running concurrently with a Cash betting system that is essentially a pari-mutuel market. You choose how many 1 Euro contracts you wish to bet on whatever options are available. (They take a 5% commission.) On the legal side, Foretal says they are based in Malta, and don’t take cash bets from the United States.

BluBet - BluBet is another site that’s not really a prediction market. It somewhat resembles a pari-mutuel betting system, where you bet on a winner and the people who successfully picked the winner split the pot. However, in this case (like others discussed in this section) there is no way to express the confidence in your bet. If you are absolutely confident in your bet, you have no way to be able to bet any more than the person who chose a random selection.

ZiiTrend - ZiiTrend is really trying to integrate a prediction market and a social network. The prediction market software is quite slick, but stretches what it means to be a prediction market. While you can specify values, like you can specify the price at which you want to trade, there is no way to vary how much you want to risk. It’s simply a vote, but a variable vote. From what it looks like, they want to focus on the social network aspect of this site, and aren’t looking to sell/licence the software.

RIP - No longer available

CrowdIQ - CrowdIQ started around the same time as Inkling, but never seemed to get traction. You can still see elements of CrowdIQ around everywhere, as ConsensusPoint uses the CrowdIQ page layout/style in their default prediction market “look and feel.”

FreeMarket - FreeMarket was developed by Jesse Gillespie, but has since taken the software down. (See here.) Essentially even though he said he couldn’t support it, he kept getting quite a number of questions and requests for help. He’s moved on in his interests, so he just took the software down. That said, I have an old copy, so e-mail me if you’re interested.

Summary

Wow, there are a lot of options out there for prediction market software, prediction market public sites, and general “wisdom of crowds” (such as idea selection and voting systems.) Whether you’re looking for software to use internally in an organisation or you’re looking for public sites where you can try different types of interaction, there are many choices for you. I hope that the list above is useful for you.

As always, please feel free to contact me with questions or concerns. If you don’t want to miss any posts, why don’t you sign up for this blog via e-mail? Just click here and you’ll be all set.

Thanks to Lionel Page, I had the chance yesterday to present and talk to a group of academics across a number of different departments at the University of Westminster Business School. (Lionel is a Research Fellow there.)

My talk made a general introduction to prediction markets, and then I discussed my paper from the Journal of Prediction Markets. (The part covering my paper was largely the same as what I presented at the New York and London conferences.)

The start of the discussion, around prediction markets in general, was very useful and stimulating. In a discussion around measuring risk and probabilities, we talked about some interesting potentials for using prediction markets around credit risk, prompted by this summer’s events in the credit markets. While direct assessment of credit risk would likely be too complex for individuals to aggregate, other factors in risk equations might be very appropriate for prediction markets. This could very applicable for large international firms, as a market could aggregate information far more quickly than standard reporting routes.

We also talked about some of the challenges of prediction markets, particularly regarding incentives. Again, there is always a balance that needs to be struck when designing a market and incentive programme. A person should have incentives to participate, but never so much of an incentive (and so little a potential cost) that a trader could gain by sabotaging a project or incentive. (For example, they should not be able to massively short the chance that a project will be done on time, and then work against it being done on time.) This is a delicate question, and also reaches back to whom you invite to the market and what kind of questions you’re asking them.

Overall, it was a great afternoon with Lionel and his colleagues. I hope more of their students hear about prediction markets and how they can be used in a modern business.

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I’ve recently upgraded the comment system for Mercury’s Blog. It now uses Disqus, and makes it much easier to comment and see threaded comments. If you have something to say, it’s now much easier to say it!

I’ve recently read about a very unique software product, developed by a company in New York City. That product is called FogBugz 6.0, and was written by Fog Creek Software. The company is famous for the blog started by its founder, Joel Sposky, called “Joel on Software.”

FogBugz 6.0 is a software bug tracking and project management program that uses an innovative approach to forecasting ship dates based on what they are calling “Evidence Based Scheduling (EBS).” I think this software is likely very excellent at what it does. I also think that this type of feature is the perfect foil for how and why prediction markets can be used to forecast project management dates in companies and other organisations.

Prediction Markets and Evidence Based Scheduling provide the exact same core forecast data. A probability on when a project will be completed, and a plot showing how that probability has changed over time. Where they differ is in approach: bottom-up versus holistic.

Bottom-up approach:

Evidence Based Scheduling is a very data-centric approach. Each developer tracks their estimate to complete a given project segment. The software then provides a timer to measure exactly how much time was actually spent completing that segment. With that data in hand, the time it will actually take for a given developer to complete future segments can be calculated, with individualised standard deviations.

What the software requires is a list of project segments and who they’re assigned to. Monte Carlo simulations sum them all together to create the final probability curve.

What’s great about it: It’s data-based, and managers can dive down into the data to see why (and who) is the reason that a project may or may not make it out the door in time. Evidence Based Scheduling is also automatic, and doesn’t require any other interaction from the user to develop the forecasts. In a very data-rich task environment, this could be an excellent tool.

The problems with it: This works particularly well within its specific context, but I am skeptical that this would work elsewhere. Here are my concerns:

• Poor data / Garbage In=Garbage Out: The reason this implementation works is because each task is tracked and timed individually. The moment that the discipline around the process is lost, the data quality will suffer, and that will directly impact the forecast.
• Scope Creep: This method is based on having all tasks detailed. If a project suffers from scope creep, where additional features are consistently added throughout, the forecast is essentially meaningless. There are plots within this EBS to attempt to show this phenomenon, but the fundamental issue is still there.
• Can it deal with complexity?: I’m not convinced that EBS will deal well with projects that have lots of moving parts, or significant internal political issues. Political issues in particular can take completely de-rail well-run projects, and there is nothing in EBS to account for these complexities. (This is a bit of a combination of the two points above.)

Holistic approach:

Prediction Markets are another way to forecast when projects will key milestones. This can be done in a variety of ways, depending on your business needs. (You can find out more on prediction markets by watching these short videos: What is a prediction market? and How can I use a prediction market in my business?)

What’s great about it: Prediction Markets capture the holistic picture of a project. Instead of trying to forecast base-level data and then sum each part up, prediction markets forecast what you really want to know. Incentives encourage each user to express what they’re thinking, and their knowledge and history with similar problems at your company and in your industry. Even better, their level of activity corresponds to the depth of their conviction; if someone doesn’t feel they know enough they won’t trade heavily and those with heart-felt conviction will trade significantly more; it’s self-selecting.

The problems with it: Compared to Evidence-based Scheduling, prediction markets do have some issues. These are where prediction markets don’t do as well:

• No audit trail. While prediction markets provide forecasts, managers and executives can’t necessarily dive down into the data to see why they are changing. This can be mitigated by adding forums/discussion boards to the market, or providing a capacity to ask people why they traded after making a transaction.
• Less scientific “feel”. Evidence-based scheduling looks great because you can see and understand the building blocks of how forecasts are built. Prediction markets are based on people, their information and their incentives. Despite the fact they’ve been proven to work better than other forecasting methods, the “science” of prediction markets is based in economics, not in statistics.
• More work is required. Employees need to spend a few minutes of their time throughout the week/month in order to trade. EBS simply runs in the background (other than making the initial forecast of how long it will take to complete a segment of work). Time spent on a prediction market site can also be seen as a distraction by some managers, despite the valuable feedback it provides them.

Summary:

Evidence-Based Scheduling is a fantastic tool in its context; I just believe there aren’t many business problems where it can be effectively used. Prediction Markets use a holistic method to look at a project in total. While there isn’t as strong an audit trail in a prediction market, the full scope of the problem in the context of the company and the industry is taken into account. For many organisations, a prediction market will be the optimal solution.

Screenshot from FogBugz 6.0 website.

Cross-posted to Midas Oracle.