Data & decisions · focused workspace

Rank Weight Sensitivity Lab

Rank options by weighted criteria and test how changing one criterion’s weight changes the winning option.

Baseline rankingCompare scenariosCSV & printable report

Make the next step clearer

Open CSV / project

Preparing the worked example…

Make it yours

Settings & assumptions

Option–criterion scores

Your result, explained

02 / RESULTS

Read the result in context

Use comparable, already-normalized scores where higher is better. A complete option-by-criterion grid and consistent weights are required. One weight varies from zero to the selected multiplier; ties remain visible.

How to use Rank Weight Sensitivity Lab

Explore the worked example. Score two options on cost, quality and speed, then vary the cost weight and watch which option leads.
Replace the option–criterion scores with your own entries. Set criterion to vary, maximum weight multiplier, sensitivity intervals.
Choose “Test ranking stability”. Review baseline ranking and weight sensitivity, then compare the visual overview with the detailed tables.
Capture alternative scenarios, download a reusable project and export the selected table or a report when you are ready.

A starting point

Score two options on cost, quality and speed, then vary the cost weight and watch which option leads. The example is illustrative and can be replaced.

Know what you are comparing

Should I enter raw dollars alongside percentage scores?

No. Scores must already be comparable, with higher meaning better. Normalize raw metrics yourself; the tool does not infer a suitable scoring scale.

Files, privacy & saving

Calculations run locally in a browser worker. Input CSV files use the column names in the downloadable template and keep your current settings. Projects restore inputs and up to four scenarios. Imports are limited to 1 MiB and 100 entries. There is no automatic saving. Public pages include advertising and optional analytics; see our privacy policy.

CSV exports contain the entire selected table. JSON and printable HTML reports include all result tables; open the report and use your browser’s Print command for PDF.

Using Rank Weight Sensitivity Lab

Rank options by weighted criteria and test how changing one criterion’s weight changes the winning option.

Explore the worked example. Score two options on cost, quality and speed, then vary the cost weight and watch which option leads.
Replace the option–criterion scores with your own entries. Set criterion to vary, maximum weight multiplier, sensitivity intervals.
Choose “Test ranking stability”. Review baseline ranking and weight sensitivity, then compare the visual overview with the detailed tables.
Capture alternative scenarios, download a reusable project and export the selected table or a report when you are ready.

Example

Score two options on cost, quality and speed, then vary the cost weight and watch which option leads.

Questions & answers

Should I enter raw dollars alongside percentage scores?

No. Scores must already be comparable, with higher meaning better. Normalize raw metrics yourself; the tool does not infer a suitable scoring scale.

Can I compare and save alternative plans?

Yes. Capture up to four calculated scenarios, restore their inputs and save them in a project JSON file. There is no automatic saving.

How do I bring in my own entries?

Download the CSV template, retain its column names and replace the example rows. Imports are limited to 100 entries and 1 MiB. A saved project also restores settings.

What should I check before using the result?