Decision Matrix Builder
Build weighted decision matrices to compare options across criteria. Enter options, criteria, weights, and scores (1-5). Compute weighted scores per cell, totals per option, rank options, identify the winner, and run ±10% sensitivity analysis. Export as text report, CSV, or color-coded HTML. 18 extra features: options parser, criteria parser, weights parser with normalization, scores parser with validation, weighted score calculator, total per option calculator, option ranker, best option identifier, weight normalizer, score validator (1-5), sensitivity analysis, multi-format renderers, copy/download, history (localStorage), shareable URL, summary stats. 100% client-side.
About Decision Matrix Builder
Build weighted decision matrices to compare options across criteria. Enter options, criteria, weights, and scores (1-5). Compute weighted scores per cell, totals per option, rank options, identify the winner, and run ±10% sensitivity analysis. Export as text report, CSV, or color-coded HTML. 18 extra features: options parser, criteria parser, weights parser with normalization, scores parser with validation, weighted score calculator, total per option calculator, option ranker, best option identifier, weight normalizer, score validator (1-5), sensitivity analysis, multi-format renderers, copy/download, history (localStorage), shareable URL, summary stats. 100% client-side. Everything runs locally in your browser — your data never leaves your device.
How to use
- Enter your input in the tool above.
- Adjust any options to your preference.
- Use the Copy or Download buttons to save the result.
- Everything happens locally — your data never leaves your browser.
FAQ
How does the decision matrix builder work?
Enter your options (one per line), criteria (one per line), weights as `criterion,weight` (weights should sum to 100), and scores as `option,criterion,score` (score 1-5). The tool computes each cell's weighted score (score × weight), totals per option, ranks them, identifies the winner, and runs a ±10% sensitivity analysis to check whether the winner stays the winner under weight variation.
What happens if my weights don't sum to 100?
The weight normalizer scales all weights proportionally so they sum to 100. For example, weights 30/20/30/20 sum to 100 already and stay unchanged. Weights 3/2/3/2 sum to 10 and are scaled to 30/20/30/20. The normalized weights are used for all calculations.
What is sensitivity analysis?
We vary each weight ±10% (one at a time) and re-rank options. If the winner stays the winner across all variations, the decision is robust. If the winner changes for some variations, we flag that the decision is sensitive to that criterion's weight — useful when justifying the decision to stakeholders.
What extra features does this tool have compared to others?
(1) Options parser (one per line). (2) Criteria parser. (3) Weights parser with normalization. (4) Scores parser (option × criterion lookup). (5) Weighted score calculator (per cell). (6) Total score per option calculator. (7) Option ranker. (8) Best option identifier. (9) Weight normalizer (sum to 100). (10) Score validator (1-5 range). (11) Sensitivity analysis (±10% weight variation). (12) Text report renderer. (13) CSV renderer (option, criterion, score, weight, weighted_score). (14) Color-coded HTML table renderer. (15) Copy + download .txt/.csv/.html. (16) History (localStorage, last 20). (17) Shareable URL (encode inputs in hash). (18) Summary stats (options count, criteria count, winner, margin of victory).
Is my data sent anywhere?
No. All matrix parsing, scoring, ranking and sensitivity analysis happen 100% locally in your browser. History is stored in localStorage on this device only. Nothing is uploaded.
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