Complaint Cause Finder Calculator

Turn complaints into structured causes with confidence. Score severity, frequency, and evidence quickly. Get ranked actions that teams can execute today.

Calculator Inputs

Used in your report and exports.
Higher frequency increases urgency and prioritization.
10 means high safety/contract risk.
FMEA Ratings
Higher numbers indicate higher risk.
Evidence Strength per Cause Category (0–5)
0 = no evidence, 5 = strong evidence from data or observation.
Categories follow the 6M cause model.
Context Signals
Check what applies. Signals adjust category likelihood.
Reset

Example Data Table

Complaint ID Type Process Step S O D Notes
C-2026-0107 Dimensional Production 7 5 6 Drift after long run; trend seen on SPC chart.
C-2026-0129 Packaging Packing/Shipping 4 6 4 Label mismatch after changeover; two SKUs staged together.
C-2026-0142 Functional Final Inspection 8 3 7 Intermittent failure; inconsistent readings on one gauge.

Formula Used

The calculator uses a Risk Priority Number: RPN = Severity × Occurrence × Detection. Each cause category then receives a weighted score that combines RPN, user-provided evidence (0–5), and context signals. Scores are normalized into confidence percentages to rank likely cause categories.

How to Use This Calculator

  1. Enter the complaint type and the process step where it was detected.
  2. Set Severity, Occurrence, and Detection using your team’s rating rules.
  3. Rate evidence strength for each 6M category using data and observations.
  4. Select context signals such as recent changes, alarms, or measurement issues.
  5. Submit to see ranked likely causes and suggested next actions.
  6. Download CSV or PDF to attach to your investigation record.

FAQs

1) Is this a root cause confirmation tool?

No. It ranks likely cause categories using your inputs. Confirm root causes with data, controlled trials, and documented verification before implementing permanent corrective actions.

2) What do the confidence percentages mean?

They are normalized scores across the six categories. Higher percentage means the model sees stronger combined signals for that category, not certainty.

3) How should we choose Severity, Occurrence, and Detection ratings?

Use a consistent internal scale, similar to FMEA guidance. Align ratings with customer risk, historical frequency, and how reliably the defect is detected before shipment.

4) What counts as “evidence strength”?

Evidence is measurable support: SPC trends, alarms, audits, photos, traceability, COA results, or verified observations. A 5 should be strong and repeatable.

5) Why include context signals like recent change or new lot?

Many complaints correlate with changes. Signals help shift the ranking toward categories commonly affected by changes, while still requiring you to validate.

6) Can we use this for service or delivery complaints?

Yes. Treat “Method” and “Man” as process and staffing drivers, and record evidence such as dispatch logs, pick accuracy, and training or scheduling issues.

7) What if Measurement ranks highest?

Pause decisions and verify the measurement system first. Run MSA/GRR, check calibration, and confirm the inspection method matches the specification definition.

8) How do we document containment and corrective action?

Record containment actions, affected lots, verification results, and effectiveness checks. Use the exports as an attachment, then link outcomes to CAPA records.

Related Calculators

Root Cause AnalyzerFishbone Diagram ToolCause Effect AnalyzerProblem Cause FinderIssue Root IdentifierFailure Cause AnalyzerDefect Root FinderQuality Issue AnalyzerProcess Failure AnalyzerIncident Root Analyzer

Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.