Industries ripe for prediction markets
February 1st, 2007If you're new here, you may want to get Mercury's Blog by Email or subscribe to my RSS feed. Thanks for visiting!
Prediction markets are powerful tools in business forecasting. However, their use and the business problems they solve will vary between industries. I’d like to discuss a couple of scenarios where prediction markets can be particularly valuable.
You’ll notice an interesting phenomenon when it comes to early adopters of prediction markets; an inordinate number of pharmaceutical companies are listed. They are the best example of the type of company that needs prediction markets the most: industries where massive research and development costs are spent before any revenue is generated. Pharma’s have a real need to understand which potential drugs and research areas will be successful so they can focus their resources. It’s a similar situation for movie studios, which is why HSX likely has the client list that they do.
Does your company fit that mold? Do you need to make a massive investment before any revenue is generated? Then a prediction market is a good solution for you. Early identification of product popularity and schedule will easily make your business case. If you’re banking on a fall release for a product you expect to be very popular for the back-to-school and holiday market, you need to understand both if it will be ready in time, and if it’s going to be as good as the project manager is reporting. Would you rather know in June that you have problems, or experience the stress of not meeting quarterly earnings targets with a sub-standard product?
That isn’t the only type of business that can be well-served by prediction markets. Mature industries with key variable costs or demand will also see business success through a prediction market tool. As an industry matures and consolidates with fewer players, certain variables can dramatically affect profitability. For example, Hewlett-Packard has used prediction-market-type tools to forecast RAM prices, and has seen forecasting error drop from 4% to 2.5%. They may not seem significant, but multiplied over the sheer volume purchased each year can be a tremendous cost savings. This is exactly what Arcelor has done in the steel industry, as well. Their fairly small prediction market has demonstrated consistently better forecasts in quarterly demand than previous forecasting methods.
These are only two of many different types of businesses that could be well-served by prediction markets. I hope to provide examples of others in the future. As always, please feel free to comment here or contact me with any questions!