Quality ROI
Model what a faster, structured quality loop is worth for your plant. Every assumption is editable and labeled; the output is a range, not a promise.
Revenue & COPQ Pool
Measured surveys put total quality costs at 2.5–5% of sales revenue, and a 2026 global survey most often reports 5–10%. The often-quoted 15–30% band traces to 1950s rules of thumb with no modern sample. The slider spans 2–20% — set it where your plant actually sits.
How much of the COPQ pool an improvement programme can realistically address in a year. The 5–15% default is an illustrative modeling assumption — deliberately modest. Edit it to your own programme.
Investigation Effort
No published benchmark exists for engineering hours per 8D — two independent research sweeps confirmed the gap. Customer manuals impose the clock instead: containment within 24–48 hours, full response in 10–20 working days. The 20–40 hour default is illustrative; set your own from recent cases.
Illustrative default of 3–4 people; edit to match your team.
A peer-reviewed single-plant case study measured 36.7% less production-process time after structured 8D-based corrective action. We default below it, at 30%. A case study, not a benchmark — adjust to your experience.
Rates & Reaction Time
Anchors from official statistics: a German quality manager runs about €39/hour gross (median), which loads to roughly €50/hour. Loaded rates in Central and Eastern Europe typically run €15–25/hour; the US equivalent is about $69/hour loaded.
German employers pay €28 in non-wage costs per €100 of gross salary (Destatis) — a 1.28× multiplier. The comparable US convention from official compensation data is about 1.4×.
Supplier quality manuals commonly require containment within 24–48 hours. No independent study measures how much faster teams react with a digital loop versus spreadsheets — so this line uses your own before/after estimate, not a vendor claim.
Deliberately modest default. Surveyed full-outage costs run far higher — a 2023 survey of 3,215 maintenance leaders put the typical industrial figure near $125,000 per hour — but a quality deviation rarely stops a whole line.
Enter your revenue and investigation count on the left to see your savings range.
How to Use This Calculator
- 01Annual Revenue: Your total annual revenue in EUR.
- 02COPQ slider: Your cost of poor quality as a share of revenue — the spread is disclosed above the slider.
- 03Investigations: How many structured problem-solving cases (8D / A3) you start per year.
- 04Bands: Ranges you can edit — hours, team size, and the addressable COPQ share. They drive the width of the output range.
- 05Rates: Gross wage and the employer loading multiplier give the fully loaded hourly rate.
- 06Reaction: Your own before/after estimate of reaction hours saved per event, priced at your cost per hour.
Sources & Assumptions
Two kinds of numbers power this calculator. Measured sources are named below. Everything else is an illustrative modeling assumption — visible, editable, and labeled in place.
COPQ share of revenue
Measured survey core: total quality costs of 2.5–5% of sales (ASQ-member survey lineage); a 2026 global survey most often reports 5–10%; automotive total quality costs of about 4.4% appear in German research. The 15–30% band is a 1950s rule of thumb repeated without methodology — the slider discloses the full spread.
Wage loading
Destatis: €28 of non-wage labour cost per €100 gross salary in Germany (1.28×). Official US compensation statistics support about 1.4×.
Investigation effort
No published person-hours benchmark for an 8D exists. Elapsed-time evidence: a five-year automotive study of 85 problems saw median closure fall from about 21 days to under 7; customer manuals require containment within 24–48 hours.
Effort reduction
Peer-reviewed single-plant case study: 36.7% less production-process time after structured 8D-based corrective action. Used as supporting context for the 30% default, never as a general benchmark.
Reaction line
No independent published comparison of manual versus digital reaction latency exists — this line therefore uses only your own before/after inputs.