Tulevaisuusresilienssi ja strateginen ennakointi: kriisinkestävyyden harjoittelua bayeslaisella kausaalimallinnuksella

The article presents a method for exercising strategic future resilience. The method is based on representing scenarios with probabilistic causal inference and modelling using Bayesian Networks. The concept has been tested with experts of a Finnish city organisation to map the long-term consequences of a simulated chemical logistics disaster. The method yields an inter- nally consistent and quantitatively reinforced representation, a model of how the expert users conceive of possible worlds unfolding as a system of causal paths. The result is not a traditional quantitative ‘decision support tool’, detached from the actual decisions and the qualitative jud- gment on which they are based. Rather, the method is used to systematically map and trace the rationales and inferences that lead to decisive actions. The method allows strategic foresight and planning to be tenaciously calibrated with the uncertainties and complexities brought on by disruptive crises – a kind of futures resilience.