Five numbered steps to build a weighted decision matrix. Criteria, weights, and scoring rules included.
Last updated: June 2026
Five example criteria with weights (User Impact 30%, Business Value 25%, and more) plus live weighted-score formulas in the sheet. Opens in Excel, Google Sheets, and Numbers with the score formulas already wired up. No email required.
Weighted scoring compares a fixed set of options against the same criteria. Start by writing down exactly what you are deciding and which options are in the running.
Formula
Decision matrix = one decision, 3-10 named options, scored against shared criteriaPro tip: If the decision is already made and you're building the matrix to justify it, stop. A gamed matrix costs you credibility the next time you need the team to trust a ranking.
Criteria are the dimensions you will judge every option on. Pick the ones that matter for this specific decision, and keep the list short.
Formula
Criteria set = distinct, defined dimensions relevant to the decisionPro tip: Longer criteria lists take more work to score. Remove overlap and criteria that do not affect the decision, without assuming a fixed limit applies to every team.
Weights encode what matters most. This is the step that makes the model yours, and the step teams most often dodge.
Formula
Weights = relative importance of each criterion; use percentages totaling 100% herePro tip: Equal weights are reasonable when criteria matter equally. If they do not, document why some deserve more influence.
Work through the matrix one criterion at a time, scoring all options on that criterion before moving to the next. This keeps the scale consistent.
Formula
Score = 1-10 per criterion, with cost and risk criteria scored invertedPro tip: Check the direction of cost and risk scores. If high cost or high risk receives a high rating, the formula will reward it.
Each option's weighted score is the sum of its criterion scores multiplied by the criterion weights. Rank descending, then interrogate the result before acting on it.
Formula
Weighted Score = sum of (criterion score x criterion weight) across all criteriaPro tip: The matrix informs the decision; it doesn't make it. If leadership overrides the ranking for strategic reasons, document the override instead of quietly re-scoring until the numbers agree.
Use the free weighted scoring calculator to define criteria, adjust weights, and compare normalized scores. Its sensitivity view shows how rating differences and weights affect the scores.
Open Free Weighted Scoring CalculatorUse enough criteria to represent the decision without counting the same concern twice. Five to seven is one possible starting point; fewer or more can be appropriate.
Discuss relative importance, assign weights, and document the rationale. For the manual formula, use percentages totaling 100%. Equal weights are valid when criteria matter equally; revisit weights when the decision or priorities change.
RICE is a fixed formula: Reach, Impact, Confidence, and Effort, always those four, designed for feature backlogs with user data. Weighted scoring lets you define the criteria and their importance yourself, which fits decisions RICE cannot express: vendor selection, strategic bets, tech debt, or anything where compliance, risk, or stakeholder priorities matter as much as user impact. Use RICE for standard feature prioritization and weighted scoring when the decision has dimensions RICE does not capture.
Settle weights before anyone scores, not after, because post-hoc weight changes look like ranking manipulation. Have each stakeholder force rank the criteria independently, compare the rankings, and negotiate the gaps in the open. The argument about weights IS the alignment work: a sales lead pushing for 40% on revenue and an engineer pushing for 30% on feasibility are surfacing a real strategic disagreement the matrix just made visible. If consensus fails, the decision owner sets the weights and records the rationale.
Skip it for routine backlog prioritization (RICE or ICE rank 20 features in a fraction of the setup time), for quick low-stakes calls where the overhead outweighs the decision, and for decisions that are already made, where the matrix would only exist to justify the answer. It earns its setup cost on complex, high-stakes choices: multi-stakeholder roadmap calls, vendor selection, or strategic initiatives with competing dimensions.