Decision Matrix
Weighted scorecard (Pugh matrix) to break any tie
List the options, list the criteria, set weights. The matrix picks the winner.
| Criterion | Weight | |
|---|---|---|
| Weighted total | ||
Highest weighted score across all criteria.
About Decision Matrix
What a decision matrix is
A decision matrix (also called a Pugh matrix or weighted scorecard) is a structured method for comparing options against multiple weighted criteria. You list the alternatives in columns, the criteria in rows, assign each criterion a weight (its importance), score each option against each criterion (typically 0–10), and the matrix multiplies and sums for you. The option with the highest weighted total is the recommended pick.
It's the most-used decision tool in engineering and product design for a reason — it forces the decision-makers to:
- Name the criteria explicitly (instead of arguing past each other)
- Agree on weights before seeing scores (so politics doesn't bend the criteria after the fact)
- Score each option in isolation (one criterion at a time)
- Trust the arithmetic at the end
Where it came from
The technique was formalised by Stuart Pugh in his 1981 paper "Concept Selection: A Method That Works," and his 1990 book Total Design. Pugh was a British engineer at the University of Strathclyde who designed it for product-concept selection at the early-stage gate of an engineering project. The method has since spread to procurement, hiring panels, vendor selection, software architecture choices, and family-scale decisions (which house to buy, which school to send the kids to).
When to use it — and when not to
Use a decision matrix when:
- There are multiple criteria and they're not equally important.
- The team disagrees about which option is best, often because each person is implicitly weighting different criteria.
- The decision is reversible-but-expensive (vendor choice, hiring, architecture pick) — the upfront cost of structuring is justified.
- You'll need to explain or defend the choice later. The matrix is the audit trail.
Don't use it when:
- One option is obviously better. Don't add ceremony to a clear decision.
- The decision is time-sensitive. Spending a day on a matrix to choose lunch is theatre.
- The criteria are truly impossible to weight (e.g. genuinely incommensurable values like "does this match our mission"). A matrix forces a number, and that number may smuggle in false precision.
How to set good weights
Weights are where the matrix lives or dies. Two common patterns:
- 0–10 scale, where 10 means "this is a must-have, the option must score well on it," 5 is "important," 1 is "nice to have," and 0 is "don't even include this criterion." This is the default in our tool.
- Forced ranking, where you assign 100 points total across all criteria. This prevents weight inflation ("everything is a 10") but is more painful with many criteria.
For weights to be useful, set them before you score any option, ideally with a separate stakeholder than the one who'll score. Pugh originally recommended this stakeholder separation explicitly.
Common pitfalls
- Criterion overlap. Cost, budget impact and price are the same thing scored three times — you've just tripled the weight of money. Audit your criteria list and merge duplicates.
- Loaded weights. The person who already knows what they want sets the weights to engineer the answer. Mitigation: set weights collaboratively before any option is on the table.
- False precision. A 0–10 scale suggests you can distinguish a 7 from an 8. You can rarely actually do this. Treat anything within ~10% of the winner as effectively tied — and at that point fall back to qualitative judgement, not the matrix.
- Missing a kill criterion. Some options have a deal-breaker (regulatory non-compliance, security flaw, contract clause). A pure-weighted matrix can pick something the team will then veto for a 0-score reason. Filter dealbreakers out before weighting.
What this tool gives you
- Drag-edit any cell — name, weight, score. No save button; everything is live.
- Auto-saves to localStorage — close the tab, come back, your matrix is intact.
- Live weighted total at the bottom of each option column.
- Trophy on the winner the moment the numbers land.
- No account required. The matrix lives in your browser only; Pro users can save it as a named workspace and sync across devices.
Frequently asked questions
Yes — a Pugh matrix (sometimes called Pugh decision matrix or Pugh concept selection matrix) is the classic weighted-criteria decision tool formalised by Stuart Pugh in 1981. Modern \"decision matrix\" tools, including this one, are descendants of it.
The tool uses 0–10. Pugh's original method used -1/0/+1 against a baseline option, but 0–10 generally communicates better with non-engineers and produces a clearer winner. Keep scoring consistent — if 7 means "good" for one criterion, 7 should mean "good" for all of them.
Weight = how important a criterion is, set once for the whole decision (e.g. Cost = 5, Time = 4, Quality = 3). Score = how well a specific option performs on that criterion (e.g. Vendor A scores 7 on Cost, Vendor B scores 9 on Cost). Final per-cell value = weight × score; the column sum is the weighted total.
In your browser only (localStorage). Closing the tab is safe. Clearing site data wipes it. Pro users can save the matrix as a named workspace and sync across devices.
Genuinely tied results (within ~10%) usually mean either (a) your criteria list is missing a real differentiator or (b) the two options really are equivalent on the criteria you care about — in which case pick on cost, momentum, or the team's gut.
Use your browser's "print to PDF" for now; a built-in CSV / image export is on the roadmap. The auto-save means the matrix is also recoverable from localStorage if you need to read it programmatically.
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