Predictive markets are known to be extremely effective in forecasting political elections. They also help candidates see which issues they lead on, as well as the areas where their messaging needs work.
Smaller civic organizations can also benefit. The University of Iowa's on-campus club the University of Iowa Democrats -- the largest Democratic club in the state of Iowa -- uses Predictify’s tool to pull greater insights out of political public opinion polls.
Atul Nakhasi, a junior at the University of Iowa and president of the University of Iowa Democrats, is amazed at the insights.
“We’re going to have 120,000 caucus-goers in Iowa on the evening of Jan. 3, and if you just have two or three people making decisions, it’s not going to be reflective of the whole group. But now, if we can expand this throughout our entire membership and organization, we’re going to start reflecting the thoughts of the state of Iowa and coming up with a more accurate picture than what the polls are saying,” Nakhasi says.
The key to success in using predictive markets is to create the right amount of scarcity. If the online "market" that a company creates has too much of what it values as currency, participants’ "purchases" don’t predict anything because everyone is buying everything simply because they have the means to do so.
For most b-to-c companies, it’s much easier to predict outcomes by studying the average budget-conscious consumer than it is to study multibillionaires.
The cautious approach to collective wisdom
Several factors are contributing to the rise of crowdsourcing in today's competitive business landscape. Foremost is the fact that organizations can gain hard-to-obtain information without a lot of investment, since the economic barrier to entry for crowdsourcing initiatives is very low.
Also, there are fewer moving parts in crowdsourcing than in traditional external collaboration projects, such as focus groups and customer surveys. Once the project is launched, participation is not likely to require screening committees, nor active monitoring. The data-rich nature of the Web -- when coupled with a well-designed database and UI -- takes care of that automatically.
But the real carrot for companies looking into crowdsourcing is the knowledge that, when it comes to forecasting, wisdom is collective.
But for all its upsides, crowdsourcing does not work for every project or company. As a rule, crowdsourcing best fits structured transactions -- such as assigning keywords to an image, buying and selling stock, taking phone calls -- as opposed to more amorphous, customized tasks such as developing a marketing plan or corporate strategy. Let’s not forget, opening the gates to the masses does open your company to the usual risks.
Netflix’s predictive recommendations project, for example, almost burned corporate shorts when two computer scientists from the University of Texas were able to determine that for movies other than the 100 most popular, user ratings and the dates of those ratings when coupled with reviews found elsewhere on the Internet could be used to identify sources which were supposed to remain anonymous.
Yet for many organizations, there is just too much untapped knowledge within the company walls to forgo giving crowdsourcing at least an in-house chance.
As "The Wisdom of Crowds" author Surowiecki says, “Set aside the question of trying to reach outside the organization. One of the things that companies need to do a better job of [is] tapping the collective knowledge of the people inside their organizations. Just doing that would be an important first step.”