Cross-Impact Matrix Method
The cross-impact matrix method is a quantitative forecasting technique that asks how the occurrence of one future event changes the probability that other events will occur. Introduced by Theodore Gordon and H. Hayward in 1968, it begins with a set of forecast events and their initial probabilities and then captures the interactions among them in a matrix of conditional probabilities. Rather than forecasting each event in isolation, the method runs repeated Monte Carlo trials in which events occur or fail to occur and their cross-impacts propagate, updating the probabilities of the remaining events. The output is a revised, internally interactive set of event probabilities and a distribution over coherent futures, making explicit the web of mutual influence that simple independent forecasts ignore.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross-impact matrix method of forecasting. Futures, 1(2), 100-116. · DOI 10.1016/S0016-3287(68)80003-5
- Glenn, J. C., & Gordon, T. J. (Eds.). (2009). Futures Research Methodology, Version 3.0. The Millennium Project. · ISBN 9780981894119
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.