Node A3

Trade Study Matrix

A weighted decision matrix with the step most free tools skip: a sensitivity check that tells you whether your winner survives ±20% disagreement about the weights.

How to run a trade study that survives review

Set the weights before you score anything. The most common way a trade study gets quietly rigged — including by its own author — is scoring the alternatives first, noticing the "wrong" one is winning, and then adjusting weights until the preferred option comes out on top. Locking weights first, ideally with the stakeholders who will sit on the review board, removes that temptation and gives you a paper trail: the weights encode what the program values, independent of any particular solution.

Define what each score means. A 4 in "technical risk" should mean the same thing for every alternative and every scorer. Write a one-line anchor for at least the top and bottom of the scale ("5 = flight-proven at this scale," "1 = requires new physics") before scoring. Unanchored scores converge to the middle and the matrix stops discriminating.

Run the sensitivity check — then talk about it. A weighted sum is a model, and the weights are its least defensible inputs; two reasonable engineers will rarely set them identically. This tool perturbs each weight ±20% and re-derives the winner. If the winner never changes, say so in your report — "the selection is insensitive to any single weighting judgment" is a powerful sentence in front of a review board. If it does change, that isn't a failure; it tells you exactly which judgment call the decision actually hinges on, so you can argue that one properly instead of defending every number in the matrix.

Document the losing alternatives honestly. The purpose of the matrix isn't to prove the winner is perfect — it's to show the decision was made deliberately, with the trade-offs visible. Record what each losing option did best; requirements change, and last year's runner-up is often next year's baseline.

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