Weighted Decision Matrix

How to use this tool

1. Add the options you are choosing between (e.g. "Job A", "Job B").
2. Add criteria that matter to you (e.g. "Salary", "Location") with importance weights 1–10.
3. Score each option on each criterion from 1 (poor) to 10 (excellent).
4. The matrix calculates the weighted total and ranks your options automatically.

What is a weighted decision matrix?

A weighted decision matrix is a way to compare options against criteria that matter to you. Give each criterion an importance weight, score every option on the same 1–10 scale, and combine those values into a ranked total. This is one form of multi-criteria decision analysis. A classic Pugh matrix is related, but it compares each option with a baseline using better, same, or worse ratings; this tool uses absolute scores instead.

The calculation is weighted total = Σ (score × weight). For example, an option scoring 8 for Cost (weight 7), 7 for Quality (weight 9), and 6 for Speed (weight 5) earns 149 points. If the total weight is 21, a perfect 10 on every criterion would earn 210 points, so this option is at 71% of the maximum. The weighted average, 7.1 out of 10, makes the result easier to compare when you change the number or weight of criteria.

How to use it

1. List your options: the alternatives you are choosing between (e.g., three job offers, two apartment choices).
2. Define criteria: the factors that matter to you (salary, location, growth potential, work-life balance).
3. Assign weights: choose values from 1–10 to reflect relative importance. For example, a weight of 8 has twice the influence of a weight of 4; the values do not need to add up to a particular total.
4. Score each option: rate each option on each criterion (e.g., 1–10 scale).
5. Review the results: the highest-scoring option wins on paper - but if the result surprises you negatively, that gut reaction is data too.

A matrix is useful when several alternatives have trade-offs, such as comparing job offers by compensation, commute, growth, and flexibility. Discuss scores before relying on the ranking: a one-point difference is only meaningful if everyone applies the scale consistently. Check the weight shares to see how much each criterion contributes, and export the table as CSV when you want to review or share the assumptions in a spreadsheet.

Limitations

A decision matrix cannot capture every uncertainty, interaction between criteria, or deeply personal value. Scores are judgments, and the highest result is only the best option according to the scores and weights you entered. Use the ranking as one input to a decision, then review important factors that may not fit neatly into the table.