Filter the matrix with cross-consistency assessment

Identify which value combinations are impossible or contradictory to reduce the space to viable solutions.

Why it works

A large morphological matrix typically contains thousands of potential combinations, most of which are either technically impossible, logically contradictory, or wildly impractical. Cross-consistency assessment pairs each value with each value on every other dimension and marks incompatible pairings. This eliminates much of the combinatorial space without value judgments about quality — only about feasibility — leaving a reduced set of coherent, viable combinations to evaluate.

How to do it

1. After building the matrix, take two dimensions at a time and ask: "Can value X on dimension A coexist with value Y on dimension B?"
2. Mark incompatible pairs; any combination containing an incompatible pair is eliminated.
3. Repeat for all dimension pairs; the remaining combinations are your viable solution candidates.

Evidence

Cross-consistency assessment is a formal technique developed within General Morphological Analysis by Tom Ritchey building on Zwicky’s work. It is used in policy analysis and futures research to systematically reduce large combinatorial spaces. Ritchey documents the cross-consistency matrix explicitly as the mechanism that collapses a multi-thousand-cell space down to internally coherent configurations by pairwise-marking impossible value combinations. (anecdotal)

The technique is established in futures and policy research; its effectiveness compared to other filtering methods in creative applications has not been formally trialed.

Sources

• Ritchey (2011), Wicked Problems — Social Messes, Springer — documents General Morphological Analysis (GMA)
• Ritchey, T. (2011). Wicked Problems – Social Messes: Decision Support Modelling with Morphological Analysis (Risk, Governance and Society, Vol. 17). Springer.
• Ritchey, T. (2013). Wicked Problems: Modelling social messes with morphological analysis. Acta Morphologica Generalis, 2(1), 1–8.

Common mistake

Applying quality judgments ("this combination is unlikely to succeed") during the consistency step rather than only feasibility judgments ("this combination cannot exist") — which reintroduces the intuition bias the method is designed to bypass.