Cross-Impact Analysis

Cross-impact analysis is a forecasting technique that models how a set of possible future events influence one another, so that forecasts account for the fact that real events are interdependent rather than isolated. Theodore Gordon and H. Hayward introduced the cross-impact matrix method in their 1968 Futures paper, motivated by the observation that judgmental forecasts such as Delphi estimate the likelihood of each event separately and ignore that the occurrence of one event can sharply raise or lower the odds of others. Olaf Helmer's 1977 work refined the approach, distinguishing the original correlational formulation from a causal cross-impact model and addressing the internal-consistency problems that plagued early matrices. The method specifies prior probabilities for events and conditional 'cross-impact' probabilities between them, then simulates the system to produce internally consistent joint outcomes and revised probabilities.