One of the greatest advantages of Web 2.0 is the ease of being able to include a lot more people in any process where having more opinions is better than less. In essence, the web makes it easy to leverage the concept of the “wisdom of the crowds”, which says that large groups of people are smarter than an elite few, no matter how brilliant. Crowds are generally better at solving a whole variety of problems. They are also better at predicting the future. (For a lot more about the wisdom of the crowds, check out James Surowiecki’s book called “The Wisdom of the Crowds” – it is a great short read on the idea.)
But how exactly can an organization easily and efficiently collect and aggregate the wisdom of the crowds. A relatively new tool, called prediction markets, has started to gain traction with a wide variety of organizations, including corporations, non-profits, academic and government institutions. These organization use prediction markets to tap into the collective wisdom of their employees, customers, suppliers and business partners.
By using prediction markets, organizations can improve forecasting, decrease operating risk, learn more about competitors and understand the impact of business innovation. Prediction markets are also a great way to forge new communication and collaboration channels.
Other key advantages of prediction markets over other more traditional business intelligence methods include:
The ability to collect information on a real time basis
They have a quantitative perspective
They provide for anonymous input
How do prediction markets work in the real world and what does a prediction market really tell you? An example might be best. Let’s say a company knows a competitor is about to come out with a new product. The company does not have a good sense of how successful this new product will be and so, it does not know how aggressively it should respond. The company starts a prediction market, with its employee base. It poses a question, “What will the market share of Competitor X’s new product be in six months?” At the same time, it offers various potential outcomes (less than 1%, between 1% and 5%, between 5% and 10% etc.). Using a virtual account of play money, employees “trade” on these possibilities, buying the outcome they think is most likely and perhaps going short on the outcome that is least likely. What’s great about a prediction market is that it is run over time. So perhaps when the product first comes out, the employees think that it will be a winner, taking at least 10% of the market. But over time, as the employees learn more about the product’s features, as reviews are posted and more customer feedback is gathered, the employees can revise their opinion and give more updated input.
Ultimately, the company winds up with a range of probabilities for each answer. It might learn that 75% of its employees think the new product only as a 5% chance of gaining a market share of more than 1%. If that is the case, maybe the company does not need to allocate resources to fight the competitor. On the other hand, the market may reveal that the employees think that there is a 65% chance that the competitor will generate market share of more than 10%. Now, the company really needs to think more about its response and how it can limit the competitor’s product from gaining too much share.
You can also learn a lot from the marketplace data. There are many ways to ‘slice and dice’ the data and understand how people with different demographics trade. In the above example, since the company knows the geographic location of all its employees, it can analyze the data based on geographic location; from this analysis, the company might learn that employees at one location tended to have one opinion while those at another location generally traded a different way. The company may wonder why that is the case – what does one location know that the other one doesn’t?
Prediction markets are also a great way to generate additional interest in on-line content. Bloggers and other producers of content may write about a subject and then simultaneously post a market about the topic. For example, a business writer focused on the auto industry may write a column on the subject and then post a question about the long term viability of certain auto manufacturers. Readers of the content could participate in the market, with the out of the market in essence helping to generate additional content complimentary to the original column.
Prediction markets are used by many leading corporations such as Proctor & Gamble, CNN, Capital One, Cisco and Wells Fargo, just to name a few.
Now, if you have read this far, you are probably pretty curious about prediction markets. So, to learn more about them, check out the leading prediction market platform provider, Inkling, at its web site . You can also trade for yourself on public markets that are run for fun. The public market asks questions about a whole host of topics, including politics, sports, business and current events. Check out Inkling’s public site.