A decision matrix (also called a weighted scoring model or Pugh matrix) turns a messy “which one should we pick” into a transparent calculation. You list the options, name the criteria that matter, assign each criterion an importance weight, and score every option against every criterion. The weighted totals reveal the winner and — just as importantly — show how close the race was. This builder computes the result live and generates a prompt that makes an LLM explain the trade-offs in plain language.
How it works
You enter your options (the choices) and your criteria, giving each criterion an importance weight from 1 to 10. Then you score each option against each criterion on a consistent scale. The tool multiplies every score by its criterion weight, sums the products per option, and ranks them — updating instantly as you type. The display normalises the weights so you can see what share of the decision each criterion controls. Alongside the live result, it assembles a prompt containing your full matrix and asks the model to narrate which criteria decided the outcome, flag any near-ties, and recommend what to verify. Everything runs in your browser.
Tips and examples
Keep your scoring scale consistent — pick 1 to 5 or 1 to 10 and use it for every cell. Set weights before you score, so the importance of each criterion is decided independently of how the options happen to perform. When the top two totals are within a few percent, treat the matrix as inconclusive and add a tie-breaking criterion rather than forcing a call. Use the generated prompt to produce the write-up you share with stakeholders: it converts the bare numbers into a defensible argument and exposes the assumptions a reader should challenge.