Demand risk is a serious threat to bottom-line performance at Intel and other manufacturing firms. Our studies identified numerous cases where poor information flow led to poor forecasts, which in turn led to decreased business performance.

Markets, and more generally IAMs, promise to help companies address demand risk and other business challenges by improving organizational information flow. Based on results to date, our IAM implementations appear to have had a desirable impact on forecast accuracy and stability. The key drivers that we believe have led to strong performance are 1) anonymity and incentives, which encourage honest, unbiased information, 2) the averaging of multiple opinions, which produces smooth, accurate signals, and 3) feedback, which enables participants to evaluate past performance and learn how to weigh information and produce better forecasts.

Although greater diversity in our participant pool may improve the collective forecast, many ways to increase diversity also increase the potential for bias in our real-world scenarios. Crowds have demonstrated the ability to solve problems such as estimating the weight of a steer [8] or choosing the winner of an upcoming election. But, the prediction may not turn out so well if the new diverse opinions come from those who will profit from selling a heavier steer or from members of the election campaign team for one of the candidates. We hope to explore this issue in upcoming phases of our research.

Our framework for designing IAMs is enabling us to systematically develop new solutions for a number of business problems, and experience, be it in the form of successes or failures, will make us more effective designers. Of particular interest are forecasts that tend to break the simplest IAM designs, predictions with long horizons or predictions whose outcomes may never be known. For instance, was product A better to bring to market than product B? We are defining solutions to these problems today and will soon be testing them in our organization.

Many business processes in use today are neither perfectly effective nor efficient; yet, they are the lifeblood of the organizations that use them. IAMs are a new approach toward business management, promising, and at the same time frightening to potential adopters. As with many such innovations, starting small and running in parallel to existing processes are keys to success. As our trials are demonstrating excellent results at remarkably low cost, expanding their use at Intel is a natural and expected outcome.