Readers of the new Industry Standard will be able to bet fake money on a variety of topics related to online business. For example, a prediction might state, "Apple will ship 10 million iPhones by the end of 2008" or "High-tech venture funding will decrease by 15 percent in Q2 2008."

The predictive market is just one leg of the new publication's offerings. It will also feature news stories and columns by influential industry thinkers such as Guy Kawasaki, an entrepreneur most famous for his former role as Apple's "chief evangelist," and Mark Anderson, CEO of the Strategic News Service.

Optimum conditions for wise crowds
Remember the old IT dictum "garbage in, garbage out"? The same applies to predictive markets. After all, "the problem with the global village is all the global village idiots," a saying that blogger Paul Ginsparg popularized.

The New Yorker columnist James Surowiecki, whose book "The Wisdom of Crowds" is widely credited with igniting the boom in predictive markets, said crowds can be smart if they address four conditions: diversity, independence, decentralization, and aggregation.

Why decentralize? Good decisions (or good bets) are made by individuals based on their own local and specific knowledge. The open source software development process is an example of decentralization in action.

Diversity is achieved largely through the absence of hierarchy (markets don't have vice presidents), which ensures that no single person has too much influence and that diverse viewpoints don't get shut out, said Surowiecki.

That may be why the new Industry Standard won't have is an editor in chief. "No single voice will dominate the discussion, which is why we decided to forgo the somewhat print-centric idea of an editor in chief, despite talking to some great people for the position," said Managing Editor Ian Lamont. "We want readers to get viewpoints from the widest range of contributors possible, with the common theme being that these contributors are all people who believe that the Web is a major paradigm shift in business."

Turning crowd predictions into revenues
HP has refined Surowiecki's ideas, developing a methodology that may improve the quality of predictions while using a group, instead of a crowd. Assuming that more knowledge equals a better prediction, HP's Huberman and researchers Leslie Fine and Kay-Ute Chen select participants with knowledge of a specific area — supply chains, for example — and then have them play a stock-market-based game.

The results of the game let the researchers grade traders on their willingness to take — or avoid — risk. They then participate in a market, and their predictions are adjusted by their risk scores. The players win real money, and their predictions are of real use to the company, Huberman said.

One of the most successful predictive markets, the Hollywood Stock Exchange, takes play-money bets on weekly movie grosses, Oscar nominations, and the like. Traders' predictions of opening-weekend returns are more accurate than the movie industry's forecasts, and the exchange has done a good job of foreseeing nominations as well. In 2002, its traders correctly predicted 35 of the 40 Oscar nominees in the top eight categories, Surowiecki wrote in The New Yorker several years ago.

The exchange monetizes those predictions by slicing and dicing the data collected on the site and selling (in very real money) it to movie studios and other interested parties, said NewsFutures' Servan-Schreiber. The exchange is private, so there's no way to estimate how much cash it generates, but it's successful enough to have been purchased by Kohlberg Kravis Roberts, a major private equity firm.

Taking a leaf from that playbook, the new Industry Standard expects to sell slices of the data it collects on the predictive market via IDC, IDG's market research arm, said Derek Butcher, The Industry Standard's vice president and general manager.