In addition to following James Surowiecki’s views on the ‘wisdom of crowds’, we also keep up with Ross Dawson–futurist, entrepreneur, and best-selling author. He spoke a few weeks ago at Creative Sydney’s Crowds + Collaboration event, sharing new perspectives.

You can find slides of his talk here, and there’s an elaboration of Dawson’s thinking on crowdsourcing at MyCustomer.com, from an interview after the Sydney event. He distills the state of the market of tools and platforms into six categories:

• Distributed innovation platforms
• Idea platforms
• Innovation prizes
• Content markets
• Prediction markets
• Competition platforms

You might have an idea which was our favorite:

Prediction markets bring together many opinions to predict the future, often based on “stockmarket-type” mechanisms, which provide a value of a particular prediction that you can buy or sell to make points or potentially money as a result of it going the way you correctly predict. One of the longstanding corporate users of this is Oracle. “For enterprise software companies it is notoriously difficult to forecast sales,” explains Dawson. “For many reasons, the sales pipeline that is put into CRM systems is often inaccurate. However, if you then ask the salespeople to predict what the sales are going to be for that quarter and you aggregate all of their opinions, you can get a far more accurate view of what the actual sales are going to be.”

Google is another user of prediction markets, using its employees to predict which of its innovations and new projects are most likely to be successful. “These are tools that actually aggregate many opinions through the classic ‘wisdom of the crowd’ in order to make more effective corporate decisions,” adds Dawson.

Futurists who understand the value of prediction markets must be onto something…

Last week, we attended the Front End of Innovation conference in Boston. We went in part because the agenda looked interesting but also because we were pleased and proud to see two of our customers—Tina Brown-Stevenson of Ingenix and Rami Levy of Motorola—as presenters/panelists.

We enjoyed Tina’s presentation on prediction markets, and we’re glad that someone reported back to the FEI blog about her presentation:

In a solid FEI Champions presentation to complement James Surowiecki’s keynote address, practitioner Tina Brown-Stevenson, Sr. VP Innovation and Information Group at Ingenix, talked through the implementation of a prediction market at Ingenix. As a lead-in to the details of the specific practical application developed at Ingenix, Ms. Brown-Stevenson drew upon examples from Mr. Surowiecki’s book The Wisdom of Crowds to outline the foundational philosophical elements for Ingenix’s overall approach.

We won’t complain when a neutral third party favorably compares us to Surowiecki. Tina shared some findings from several prediction market uses and confirmed that the size of the crowd is not what is important— as markets can be accurate with as few as 24 participants. Tina confirmed what Surowiecki talks about in his book— it is the independence and diversity of the crowd that enables prediction markets to be on average more accurate than a subject matter expert. Tina also shared the Ingenix approach to adjusting the interface to their constituent needs. While many public companies, such as Best Buy and Motorola, have found the traditional stock metaphor to be adopted well within their cultures, we adjusted the Ingenix interface to something easily understandable for Ingenix participants, both internal and external. Demonstrates the flexibility of our Foresight platform!

For Rami’s presentation, he shared his notes with us from the panel on innovation adoption. He described Motorola’s idea collection system and explained why an idea market was needed: to identify the best ideas by leveraging the “crowd.”

For Motorola, the value of our Foresight platform boils down to three ‘Rs’ in the enterprise:

• rewards: mostly intrinsic, e.g., collaboration, helping the company, helping others, forming relationships, learning)
• recognition: via leader boards in the market and built-in social media tools
• recreation: fun, like a game; easy to use with low barriers to entry; competition; social media access to enable “viral” messaging.

If you’d like a sense of the kind of bottom line value these three Rs offered Motorola, CFO.com has covered that topic.

We’re glad we went to the conference, and we’re glad that two of our customers are on the front end of innovation through their use of Foresight.

Excerpt from Michael J. Mauboussin’s Think Twice: Harnessing the Power of Counterintuition

Accurately projecting holiday sales is a crucial task for retailers.  A forecast that is too low leaves shelves bare and profits lost, while too much optimism leads to dusty inventory and pressure on profit margins.  So retailers have come up with a precise sales estimate.  To do so, most merchants rely on experts—individuals in the organization who gather information, study trends, and make predictions. 

                The stakes are especially high for consumer electronics firms because they generate so much of their revenue during the gift-giving season and the value of their inventory depreciates rapidly.  The pressure is really on the internal experts at consumer-electronics giant Best Buy, one of a multitude of retailers that rely on specialists.  So you can imagine the reaction when James Surowiecki, author of the best-selling book The Wisdom of Crowds strolled into Best Buy’s headquarters and delivered a startling message: a relatively uninformed crowd could predict better than the firm’s best seers.

                Surowiecki’s message resonated with Jeff Severt’s, an executive then running Best Buy’s gift-card business.  Severts wondered whether the idea would really work in a corporate setting, so he gave a few hundred people in the organization some basic background information and asked them to forecast February 2005 gift-card sales.  When he tallied the results in March, the average of the nearly 200 respondents was 99.5 percent accurate.  His team’s official forecast was off by five percentage points.  The crowd was better, but was it a fluke?

                Later that year, Severts set up a central location for employees to submit and update their estimates of sales from Thanksgiving through year-end.  More than three hundred employees participated and Severts kept track of the crowd’s collective guess.  When the dust settled in early 2006, he revealed that the official forecast of the internal experts was 93 percent accurate, while the presumed amateur crowd was off by only one-tenth of 1 percent. 

                Best Buy subsequently allocated additional resources to its prediction market, called TagTrade.  The market has yielded useful insights for managers through the more than two thousand employees who have made tens of thousands of trades on topics ranging from customer satisfaction scores to store openings to movie sales.  For instance, in Early 2008, TagTrade indicated that sales of a new service package for laptops would be disappointing when compared with the formal forecast.  When early results confirmed the prediction, the company pulled the offering and relaunched it in the fall.  While far from flawless, the prediction market has been more accurate than the experts a majority of the time and has provided management with information it would not have had otherwise.

Ben Kunz just published a BusinessWeek article with several interesting insights about how the Dow Jones industrial average signaled the recent market turmoil - very much like how a prediction market aggregates intelligence about future events.

How did Wall Street know what would happen? It acted like a prediction market, a pool of intelligence that can foresee the future. Prediction markets are simply bets on ideas: What do you think something is worth, and more important, what will it be worth tomorrow? When groups of people bet on something, their combined intelligence is often remarkably prescient.

As you may know, this is something that James Surowiecki discusses extensively in his book, The Wisdom of Crowds.  Ben also talked with Robin Hanson about why the traditional prediction methodologies fail:

The trouble with humans, it seems, is that even when we’re smart, we have access to imperfect information and follow the groupthink of our peers. Because we often disagree with other groups, we band together and end up agreeing too much with our own teams. No single leader can overcome such biases and data gaps to predict with certainty whether an action will succeed or fail. But Hanson suggests markets can do just that.

(Ben Kunz is director of strategic planning at Mediassociates, a media planning and internet strategy firm. He is author of the advertising strategy blog.)