How do you calculate a window SKU complexity score?

Score the configuration on severity (build/quality impact), occurrence (how often it runs), and detection difficulty (how hard problems are to catch), each 1-10, then combine them with weights. With severity 7, occurrence 6, and detection 5, the example returns a weighted complexity score of 6.15.

What is a good window SKU complexity score?

There is no universal threshold — it is relative. Score your whole catalog, then treat the top quartile (often anything above roughly 6-7 on a 1-10 basis) as candidates for redesign, surcharge, or removal.

Why use severity, occurrence and detection instead of just part count?

Part count misses risk. A rare SKU with high severity and poor detection (defects ship to the field) can cost more than a high-volume but well-controlled configuration. The three-factor model captures that, which raw permutation counts cannot.

How is this different from a standard FMEA RPN?

It borrows the severity/occurrence/detection structure of FMEA but applies it at the SKU-configuration level rather than the failure-mode level, and it is weighted rather than a flat multiplication, so a single dominant factor does not unrealistically inflate the result.

How often should we rescore our window SKUs?

Rescore at each catalog review or when energy codes change, since new code-driven glass packages and frame options shift both occurrence and severity across the line.

Can a low-volume SKU still score high?

Yes. If severity and detection difficulty are high, a configuration that runs rarely can still post a high weighted score — exactly the SKUs that surprise plants with field callbacks.

Construction Products, Windows, Doors & Fenestration calculator

Window SKU Complexity Calculator

Window SKU Complexity is an FMEA-style risk score that quantifies how hard a given window configuration is to build, schedule, and ship right the first time. Fenestration plants juggle thousands of permutations — frame depths, glass packages, grille patterns, hardware, energy codes by state — and a handful of those SKUs quietly consume disproportionate engineering, setup, and rework. Manufacturing engineers, product line managers, and S&OP planners use this score to rank SKUs objectively instead of by gut feel. A high score flags configurations worth simplifying, repricing, or pulling out of the standard catalog.

What this calculator does

Score window SKU complexity risk from configuration severity, occurrence, and detection difficulty.
deciding whether a window SKU mix needs extra review, scheduling protection, or premium pricing
It blends configuration severity, how often the configuration runs, and how hard the resulting problems are to detect into a single weighted complexity score.

Formula used

Window SKU complexity score = weighted score from configuration severity, occurrence, and detection difficulty
Use the score to compare SKU mixes, not as a pass/fail certification metric.

Inputs explained

configuration complexity severity score:
configuration occurrence score:
complexity detection difficulty score:

How to use the result

Use it when rationalizing a window catalog, prioritizing engineering or tooling investment, or deciding which custom configurations to surcharge or discontinue.
The score is a relative ranking tool, not a pass/fail certification — a 6.15 only means something when compared against the rest of your SKU portfolio scored the same way.

Current U.S. benchmarks

U.S. housing starts run at 1,177k per year (Census, May 2026), down 8.7% from a year earlier, the demand driver for building products.

Common questions

How do you calculate a window SKU complexity score? Score the configuration on severity (build/quality impact), occurrence (how often it runs), and detection difficulty (how hard problems are to catch), each 1-10, then combine them with weights. With severity 7, occurrence 6, and detection 5, the example returns a weighted complexity score of 6.15.
What is a good window SKU complexity score? There is no universal threshold — it is relative. Score your whole catalog, then treat the top quartile (often anything above roughly 6-7 on a 1-10 basis) as candidates for redesign, surcharge, or removal.
Why use severity, occurrence and detection instead of just part count? Part count misses risk. A rare SKU with high severity and poor detection (defects ship to the field) can cost more than a high-volume but well-controlled configuration. The three-factor model captures that, which raw permutation counts cannot.
How is this different from a standard FMEA RPN? It borrows the severity/occurrence/detection structure of FMEA but applies it at the SKU-configuration level rather than the failure-mode level, and it is weighted rather than a flat multiplication, so a single dominant factor does not unrealistically inflate the result.
How often should we rescore our window SKUs? Rescore at each catalog review or when energy codes change, since new code-driven glass packages and frame options shift both occurrence and severity across the line.

Last reviewed 2026-05-12.