ScholarGate
Assistent
Process / pipelineFutures studies / French prospective school

SMIC Prob-Expert

SMIC Prob-Expert — from the French Systeme et Matrices d'Impacts Croises, Systems and Matrices of Cross-Impacts — is the probabilistic cross-impact method in Michel Godet's la prospective toolkit. It takes a small set of fundamental hypotheses about the future and asks experts for both the simple probability that each hypothesis comes true and the conditional probabilities linking the hypotheses to one another. Because experts' raw estimates are rarely mutually consistent, SMIC's core is a quadratic optimisation that adjusts them minimally into a coherent joint probability distribution over the 2^n possible combinations of the hypotheses. Each combination is an image of the future — a scenario — and the corrected, or net, probabilities rank these images from most to least likely. The method thereby turns scattered expert opinion into a probabilistically weighted set of scenarios, identifying the few core futures that concentrate most of the probability mass.

Åpne i MethodMindSnartBruk, sammenlign, få veiledning
Verktøy og ressurser
Last ned lysbilder
Lær og utforsk
VideoSnart

Les hele metoden

Kun for medlemmer

Logg inn med en gratis konto for å lese denne delen.

Logg inn

Metodekart

Nabolaget av beslektede metoder — velg en node for å utforske.

Kilder

  1. Godet, M. (2006). Creating Futures: Scenario Planning as a Strategic Management Tool (2nd ed.). Economica. ISBN: 9782717852448

Slik siterer du denne siden

ScholarGate. (2026, June 23). SMIC Prob-Expert (Cross-Impact Systems and Matrices). ScholarGate. https://scholargate.app/no/futures-foresight-studies/smic-prob-expert

Hvilken metode?

Sett denne metoden ved siden av sin nærmeste slektning og les dem side om side — biblioteket legger bøkene på bordet; valget er ditt.

Sammenlign side om side

Referert av

ScholarGateSMIC Prob-Expert (SMIC Prob-Expert (Cross-Impact Systems and Matrices)). Hentet 2026-06-24 fra https://scholargate.app/no/futures-foresight-studies/smic-prob-expert · Datasett: https://doi.org/10.5281/zenodo.20539026