Weighted Scoring Models in Excel: Decision Matrices, Normalisation & Sensitivity
Weights that add up, min-max normalisation, SUMPRODUCT scores, knock-out criteria, pairwise (AHP-style) weights, sensitivity, evaluator panels and a decision dashboard: 8 labs for vendor selection, hiring and project prioritisation.
The first lesson is free — no account needed.
About this course
A weighted scoring model course that builds the decision matrices of one fictional retailer, Larkfield Outdoor, in a spreadsheet, for managers, procurement and HR staff, project offices, analysts and consultants. You turn importance points into weights that add up to 100% and block any weight above 40% with data validation, put dollars, weeks, feature counts and star ratings on one 0–10 scale with min-max normalisation, flipping it where lower is better, score and rank five software vendors with SUMPRODUCT, RANK.EQ and a SORTBY leaderboard, screen job candidates with must-have knock-out rules, derive weights from pairwise comparisons with an AHP-style consistency check, find the cost weight at which the winner flips, combine four evaluators and flag disagreement, and finish with a project prioritisation dashboard under a $900k budget. Fictional company and vendors, illustrative numbers. The first lab is free.
Lessons
- Criteria & Weights: Making Them Add Up to 100%Free
- Scoring Scales & Normalisation: Min-Max, Higher vs Lower Is Better Pro
- Weighted Score with SUMPRODUCT, RANK.EQ & a SORTBY Leaderboard Pro
- Must-Have Knock-Out Criteria with IF and AND Pro
- Pairwise Comparison Weights (AHP-Style Row Averages) Pro
- Sensitivity: How Far Must a Weight Move to Flip the Winner? Pro
- Multiple Evaluators: Averages, Spread & Disagreement Flags Pro
- Final Decision Dashboard: Score, Rank, Budget Cut-Off & Sorted Bar Chart Pro