Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared

Traditional groups meetings are an inefficient and ineffective method for making forecasts and decisions. We compare two structured alternatives to traditional meetings: the Delphi technique and prediction markets. Delphi is relatively simple and cheap to implement and has been adopted for diverse applications in business and government since its origins in the 1950s. It can be used for nearly any forecasting, estimation, or decision making problem not barred by complexity or ignorance. While prediction markets were used more than a century ago, their popularity waned until more recent times. Prediction markets can be run continuously, and they motivate participation and participants to reveal their true beliefs. On the other hand, they need many participants and clear outcomes in order to determine pay-offs. Moreover, translating knowledge into a price is not intuitive to everyone and constructing contracts that will provide a useful forecast may not be possible for some problems. It is difficult to maintain confidentiality with markets and they are vulnerable to manipulation. Delphi is designed to reveal panelists’ knowledge and opinions via their forecasts and the reasoning they provide. This format allows testing of knowledge and learning by panelists as they refine their forecasts but may also lead to conformity due to group pressure. The reasoning provided as an output of the Delphi process is likely to be reassuring to forecast users who are uncomfortable with the “black box” nature of prediction markets. We consider that, half a century after its original development, Delphi is under-utilized. Disciplines Business | Marketing Comments Suggested Citation: Green, K.C., Armstrong, J.S. and Graefe, A. (2007). Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared. Foresight. Issue 8. This journal article is available at ScholarlyCommons: http://repository.upenn.edu/marketing_papers/157 Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared Kesten C. Green Business and Economic Forecasting Unit, Monash University, [email protected] J. Scott Armstrong, The Wharton School, University of Pennsylvania [email protected] Andreas Graefe Institute for Technology Assessment and Systems Analysis, Research Center (Forschungszentrum) Karlsruhe [email protected] Forthcoming in Foresight: The International Journal of Applied Forecasting (Fall 2007) This working paper offers a more detailed treatment of the issue than was provided in the published version.