Compute · Assess & Decide · Data & Research

Rank product features with a collaborative weighted scorecard

A product team prioritizing a roadmap gets each feature's weighted value, cost normalized to the most expensive feature, absolute value, and a deterministic rank, computed exactly per the CWS formula.

You receive: A pure function computing each feature's weighted value, normalized cost, absolute value, and rank from attribute weights, per-feature build costs, and feature x attribute scores, graded on hidden cases.

Part of Choose Business Model

What's verified: STUD verifies the math (weighted value, normalized cost, absolute value, ranking with the fixed tie-break: lower normalized cost, then feature name) matches the CWS reference on held-out inputs; a feature x attribute pair missing from the scores rows counts as score 0, and when a pair appears twice the last row wins. STUD does NOT judge whether the weights, scores, or man-week estimates are good, nor whether the top-ranked feature is the right thing to build.