Process / pipelineFutures Foresight StudiesFutures studies / French prospective schoolPipeline

La Prospective Morphological Scenarios

Also known as: Godet Morphological Scenarios, Prospective Scenario Building, French School Scenario Method, Morphologie des scenarios

Within the French school of la prospective developed by Michel Godet, morphological scenario construction is the integrating stage that turns the outputs of structural and actor analysis into a small set of coherent images of the future. Building on Fritz Zwicky's morphological method, Godet decomposes the studied system into a set of dimensions or components, attaches to each a few mutually exclusive hypotheses about how it might evolve, and treats the Cartesian product of these hypotheses as the morphological space of all conceivable futures. Because that space is combinatorially large, the method's analytical work lies in reducing it: pruning combinations that are internally incoherent, implausible, or incompatible with the strategies of key actors, until a handful of contrasted, self-consistent scenarios remain. Distinct from general morphological analysis, this is the scenario-building application that consumes the variables identified by MICMAC and the actor positions mapped by MACTOR.

Key highlights

  • Systematically enumerates the full space of possible futures, reducing the risk of overlooking a plausible configuration.
  • Anchors scenarios in the system's real drivers and actor power relations through its integration with MICMAC and MACTOR.
  • Makes the construction transparent and traceable, since every retained scenario is a defensible combination of explicit hypotheses.
  • The coherence and actor-compatibility filters yield scenarios that are internally consistent and politically credible, not just imaginable.

Intuition

This section is available to Pro members. Upgrade to Pro

How it works

This section is available to Pro members. Upgrade to Pro

When to use it

Use Godet's morphological scenario construction when you need a systematic, traceable way to generate a small set of internally coherent scenarios for a complex system whose drivers and stakeholders have already been analysed. It fits naturally as the synthesising stage of a full la prospective study, downstream of structural analysis with MICMAC and actor analysis with MACTOR, where the goal is to anchor scenarios in the system's genuine variables and power relations rather than in unaided imagination. The combinatorial transparency makes it valuable when stakeholders demand to see that the possibility space was systematically explored. It is less suited to quick, lightweight foresight exercises, to problems where the dimensions cannot be cleanly separated into discrete hypotheses, or where the upstream structural and actor analyses have not been done and the morphological table would rest on shaky foundations.

Strengths & limitations

Strengths
  • Systematically enumerates the full space of possible futures, reducing the risk of overlooking a plausible configuration.
  • Anchors scenarios in the system's real drivers and actor power relations through its integration with MICMAC and MACTOR.
  • Makes the construction transparent and traceable, since every retained scenario is a defensible combination of explicit hypotheses.
  • The coherence and actor-compatibility filters yield scenarios that are internally consistent and politically credible, not just imaginable.
Limitations
  • The morphological space explodes combinatorially, so reducing it depends on judgement-heavy coherence and plausibility filtering.
  • Forcing each dimension into a few mutually exclusive hypotheses can flatten continuous or finely graded uncertainties.
  • It presupposes the substantial upfront work of structural and actor analysis, making a full study lengthy and resource-intensive.
  • Results can appear deceptively rigorous while still resting on subjective hypothesis definitions and elimination choices.

Common pitfalls

This section is available to Pro members. Upgrade to Pro

Applications

This section is available to Pro members. Upgrade to Pro

Frequently asked

How does this differ from general morphological analysis?

General morphological analysis is the broad Zwicky-derived technique of decomposing any problem into parameters, listing each parameter's possible values, and exploring the resulting configuration space, used across design, policy, and problem-structuring. Godet's morphological scenarios are a specific scenario-building application of that logic inside la prospective. The distinctive features are that the dimensions and hypotheses are drawn from prior structural analysis (MICMAC) and the elimination of configurations respects the actor strategies and power relations from MACTOR, and that the endpoints are developed into dynamic paths from present to future.

Why is reducing the morphological space the crucial step?

Because the full morphological space is the product of the number of hypotheses across every dimension, it grows multiplicatively and quickly contains far more configurations than anyone could analyse, the vast majority of which are incoherent or impossible. The value of the method comes from disciplined reduction: applying internal-coherence, plausibility, and actor-compatibility filters to keep only the handful of configurations that form believable, mutually distinct worlds. Without rigorous, explicit reduction the enumeration is merely overwhelming, so the elimination criteria are where the analytical judgement and traceability of the method reside.

Do the scenarios get probabilities?

Morphological construction itself produces coherent qualitative configurations rather than likelihoods, but within la prospective it is often combined with probabilistic tools. In particular, SMIC Prob-Expert can be applied to the underlying hypotheses to elicit and correct expert probabilities and rank scenario combinations by their probability. So while the morphological stage focuses on which futures are coherent and which actors would permit them, the broader toolbox allows the resulting scenarios to be weighted, helping decision-makers distinguish the more from the less probable among the retained set.

Sources

  1. 1.
    Godet, M. (2006). Creating Futures: Scenario Planning as a Strategic Management Tool (2nd ed.). Economica.
    ISBN 9782717852448
  2. 2.
    Bishop, P., Hines, A., & Collins, T. (2007). The current state of scenario development: an overview of techniques. Foresight, 9(1), 5-25.

You have read it. What now?

Cite this page

ScholarGate. (2026, June 23). La Prospective Morphological Scenarios. ScholarGate. https://scholargate.app/futures-foresight-studies/morphological-scenario-godet

La Prospective Morphological Scenarios | ScholarGate