What do Google, BestBuy and guessing the number of jellybeans in a jar have in common?


Yes, it is a cliched blog title, but you’re the one reading this…

The answer to the question posed in the title: They have all benefited from the use of prediction markets. For an explanation of what a prediction market is, read the previous post. This post has to do with potential uses for prediction markets. Google uses the wisdom of the crowd to direct you to the right page – the one that best fits your search criteria, has the richest content, and has a lot of other links pointing at it. Jeff Severts used prediction markets with success in predicting gift card sales at BestBuy to 99.5% accuracy when traditional forecasting methods were off by 5%. And, most importantly, Stanley Gyoshev and Gordon Murray achieved astonishing success in using prediction markets to guess the number of jelly beans in a jar!

Now, as useful as the jelly bean example may be, I believe there are some more practical uses in the Google and BestBuy vein. In many organizations with whom I work, I hear procurement people say that the forecasted volumes that they give to their suppliers are either too high or too low. Some companies tend to overestimate in order to secure better deals, and some underestimate, conscious that gaining a reputation for not delivering on promises hurts current and future supplier relationships. However, most of the time, inaccurate forecasts come about honestly – the forecasting techniques currently employed just don’t get the job done. You never know when an end product will experience a spike in popularity, or a rapid decline.

On the other hand, the knowledge of whether an end product is likely to spike or decline does exist…in the minds of all the people who produce, manage, market and buy the end product. Not only do these people have that knowledge, they also know about the level of emphasis the next marketing campaign will put on the product, whether there is likely to be a push from the retailer (or other touch point with the consumer), whether the product is likely to be a good fit with the target segment of consumers, and hundreds of other variables that affect purchase volumes. How, you ask, could people know all that stuff?! Well, no individual (and certainly not the Director of Marketing) knows all of those things, but collectively, those associated with the purchase of that input product or service do. Prediction markets facilitate the rapid aggregation of that knowledge by allowing those with inside information to profit from it. As the group grows larger, the individual errors caused by incomplete information and personal biases are removed.

Forecast accuracy can greatly improve supply chain efficiency, supplier relationships, etc., and prediction markets are a potentially effective way to achieve that objective.


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