Decision Matrix Calculator
List your options and the criteria that matter, give each criterion a weight, and score every option. The calculator ranks the options by weighted score, says how decisive the lead is, and tests whether the winner survives a different judgement about the weights.
Your matrix
Each column is a criterion with its weight; each row is an option. Score every option on every criterion, where a higher score is better.
| Option | ||||
|---|---|---|---|---|
Results
Secondary data analysis
Top option
0.3
Lead over second place
Stable
±20% weight check
| Rank | Option | Weighted score (out of 5) | Share of maximum |
|---|---|---|---|
| 1 | Secondary data analysis | 3.95 | 79% |
| 2 | Interview study | 3.65 | 73% |
| 3 | Survey study | 3.4 | 68% |
Secondary data analysis leads Interview study by 0.3 points, 6% of the maximum score.
How the top score was calculated
Secondary data analysis: 0.4 × 5 + 0.25 × 2 + 0.2 × 5 + 0.15 × 3 = 3.95
Sensitivity check
Each weight in turn is moved 20% down and 20% up with the others unchanged, and every option is re-scored. The last column shows how far that one weight would have to move before another option draws level.
| Criterion | Weight | Winner at −20% | Winner at +20% | Change that ties the lead |
|---|---|---|---|---|
| Feasibility | 40% | Secondary data analysis | Secondary data analysis | −37.5% (Interview study) |
| Personal interest | 25% | Secondary data analysis | Secondary data analysis | +40% (Interview study) |
| Access to data | 20% | Secondary data analysis | Secondary data analysis | −75% (Interview study) |
| Career value | 15% | Secondary data analysis | Secondary data analysis | +200% (Interview study) |
The winner holds: no single ±20% change in a weight alters the top option.
How to Use the Decision Matrix Calculator
- 1. Choose the scale and the weight format. Score on 1–5 for quick judgements or 1–10 for finer ones. Enter weights as percentages that total 100, or as points of any size — 3, 2, 1 means the first criterion counts three times as much as the last.
- 2. Name the criteria and the options. Columns are criteria and rows are options. Add up to eight of each; the example compares three research designs for a dissertation.
- 3. Score every cell. Higher must always mean better, so a criterion like cost becomes affordability: the cheapest option gets the highest score.
- 4. Read the ranking, then the sensitivity check. A large lead that survives every ±20% change in a weight is a robust result. A narrow or fragile one is a prompt to look harder at the weights and the evidence, not a verdict.
How a Weighted Decision Matrix Works
Each criterion's weight is divided by the total of all the weights, so the weights become shares that add up to 1. Each option's score on a criterion is multiplied by that criterion's share, and the products are added:
Weighted score
Sᵢ = w₁sᵢ₁ + w₂sᵢ₂ + … + wₙsᵢₙ, where w₁ + w₂ + … + wₙ = 1
Because the weights are normalized, the result stays on the scoring scale: a weighted score of 3.95 on a 1–5 scale means 3.95 out of 5. It also means percentages that do not quite reach 100 still work — the calculator scales them and tells you it has.
Worked Example: Choosing a Research Design
A student weighs feasibility at 40%, personal interest at 25%, access to data at 20% and career value at 15%, then scores three designs from 1 to 5. These are the calculator's default inputs.
| Option | Feasibility (40%) | Interest (25%) | Data (20%) | Career (15%) | Weighted score |
|---|---|---|---|---|---|
| Secondary data analysis | 5 | 2 | 5 | 3 | 3.95 |
| Interview study | 3 | 5 | 3 | 4 | 3.65 |
| Survey study | 4 | 3 | 3 | 3 | 3.4 |
Secondary data analysis wins with 0.4 × 5 + 0.25 × 2 + 0.2 × 5 + 0.15 × 3 = 3.95, a lead of 0.3 points over the interview study — 6% of the maximum score. No ±20% change in any single weight alters the winner, so the result is stable. The tipping points add nuance: if personal interest mattered 40% more than the student first said, the interview study would draw level. A winner that is reliable but not overwhelming is common, and worth knowing before you commit.
Reading the Sensitivity Check
Weights are judgement calls, so the check asks whether a different judgement would change the answer. Each weight in turn is moved 20% down and 20% up with the others held fixed, the weights are normalized again, and every option is re-scored. The tipping point then solves exactly for the change in that one weight at which the runner-up draws level — because each weighted score is a ratio of two straight lines in that weight, the crossing has a closed form rather than needing trial and error.
- Stable: no ±20% change alters the winner. The ranking reflects the scores, not fine-tuning of the weights.
- Sensitive: at least one change flips it. Ask whether that criterion's weight is really settled — if not, the matrix cannot choose for you.
- Large tipping points (+200%, or “no change does”) mean the criterion barely affects the outcome; small ones mean it is doing most of the deciding.
Weighted Matrix vs. Pugh Matrix
A Pugh matrix, developed by the design engineer Stuart Pugh for concept selection, compares every option with one reference option, the datum. Each cell is better (+), worse (−) or about the same (S), and the pluses and minuses are counted. It is quick, needs no numbers and is good for screening many early ideas. A weighted decision matrix scores every option on an absolute scale and weights the criteria, which makes it better for a final choice among a few well-understood options — and is what this calculator builds.
Frequently Asked Questions
- What is a weighted decision matrix?
- It is a table that lists options as rows and criteria as columns, scores each option on each criterion, and multiplies the scores by weights that reflect how much each criterion matters. The option with the highest weighted total ranks first. It is also called a weighted scoring model, a prioritization matrix or a decision grid.
- How do I choose the weights?
- Decide them before you score, so the scores cannot steer the weights. One method is to share out 100 points across the criteria; another is to rank the criteria and give the most important the most points. Then use the sensitivity check: if the winner flips with a modest change to a weight you are unsure about, settle that weight first.
- Do the weights have to add up to 100?
- No. The calculator divides every weight by their total, so 3, 2 and 1 give the same result as 50%, 33.3% and 16.7%. If you choose percentages and they total something other than 100, they are scaled and you are told.
- Should I use a 1–5 or a 1–10 scale?
- Use 1–5 when your judgements are rough, since finer scales invite false precision. Use 1–10 when you have measurements behind the scores and want to keep their differences. What matters most is that each number means the same thing on every criterion, so write down what a 1, a 3 and a 5 look like before you start.
- What if two options tie?
- A tie, or a lead under about 5% of the maximum score, means the matrix cannot separate them with the criteria you gave it. Revisit the evidence behind the closest scores, or add the criterion that actually distinguishes them — often something you left out because it was hard to score.
- Can a decision matrix make the decision for me?
- No — it organizes a decision. Its output is only as good as the criteria, weights and scores you give it. Its real value is that it makes your reasoning visible and testable, so you can explain the choice and see exactly which assumption it depends on.