Decision Matrix (Weighted Scoring)

Criteria (name, weight)

Weights are relative; we normalize to sum=1. Scores are 0–10 by default.

Criterion	Weight	Direction

Add options, then fill scores. Direction “lower is better” flips a criterion (e.g., cost).

Option	Scores

Click Compute ranking.

For each criterion, we bump its weight by ±X% (others fixed), renormalize, and see whether rankings flip.

X = percent change (e.g., 20 means ±20%).

How scoring works

We normalize weights: wᵢ = weightᵢ / Σ weight.

Each option gets a weighted sum:

score(option) = Σ ( wᵢ * sᵢ )

If direction is "lower is better", we transform sᵢ → (maxScore - sᵢ).
(Default maxScore=10.)

This is a simple, transparent model—good for forcing clarity, not for pretending certainty.