rma-failure-analysis

RMA Failure Analysis Skill

Raw RMA data lies: it mixes buyer's remorse, user error, and shipping damage in with real design and manufacturing defects. This skill turns returns into decisions — triage first so the Pareto is of verified failure modes, run the top modes through 8D discipline (contain now, root-cause properly, correct permanently), and price each mode in cost-of-quality terms so the fix competes for resources on money, not anecdote.

What This Skill Produces

• A triaged breakdown of returns using a standard RMA taxonomy
• A Pareto of verified failure modes with rates against units shipped
• An 8D-structured analysis for each top failure mode
• Cost-of-quality framing: cost per return, per mode, and the fix ROI
• Prioritised corrective actions with owners and cut-in points

Required Inputs

Ask for these if not provided; analyse whatever slice exists, but state the denominator caveats plainly:

• RMA records — return reasons, dates, symptoms, any teardown/FA findings
• Units shipped per period — the denominator; return counts without it are useless
• Product age mix — manufacture date or batch, to separate infant mortality from wear-out
• Cost inputs — per-return logistics, refurb/scrap cost, support cost per case (estimate and label if unknown)
• Known changes — ECOs, factory or component changes that bracket the data in time

Analysis Framework

Step 1 — Triage taxonomy. Bucket every return before any Pareto:

| Bucket | Meaning |

|---|---|

| NTF / CND | No trouble found — unit passes full test; count separately, it's a UX/expectation signal |

| CID | Customer-induced damage (drop, liquid) — a robustness signal, not a defect |

| OBF / DOA | Failed out of box — points at outgoing quality or transit |

| SW-resolvable | Fixed by update/reset — cheapest class to kill |

| Verified HW failure | Real defect, classified by subsystem and failure mode |

| Remorse / non-technical | Returned working — exclude from quality analysis, report separately |

Step 2 — Pareto verified failures only, by failure mode (not symptom — "won't charge" is a symptom; "USB connector solder crack" is a mode). Express each as % of units shipped in the exposed population, with the time window stated.

Step 3 — 8D per top mode (top 3–5 carry most of the cost): D1 team · D2 problem statement with data · D3 containment (screen stock, hold lots, factory rescreen — dated) · D4 root cause via evidence (teardown, cross-section, batch correlation), labelled [verified] or [hypothesis] · D5 corrective action chosen · D6 implementation with cut-in (ECO/date/serial break) · D7 recurrence prevention (test coverage, DFM rule, spec change) · D8 closure criteria (return rate for the mode falls to X by date Y).

Step 4 — Cost of quality. Cost per return = freight + refurb/scrap + support labour + replacement unit margin. Annualise per mode; compare fix cost vs failure cost; note warranty-accrual impact.

Output Format

RMA failure analysis: [product] — [period]

1. Summary — return rate vs target, headline modes, the one-paragraph verdict
2. Triage breakdown — table: bucket, count, % of returns, % of shipped
3. Verified-failure Pareto — mode, count, rate vs shipped, trend, batch correlation
4. 8D per top mode — the eight disciplines, with D4 evidence labelled verified/hypothesis
5. Cost of quality — per-return cost, annualised per mode, fix ROI table
6. Actions — containment (now) and corrective (cut-in) with owners and dates
7. Data caveats — denominator gaps, lag effects, unteardown returns

Quality Checks

• [ ] Every rate has a denominator and an exposure window — counts alone never appear
• [ ] NTF, CID, and remorse are separated out before the failure Pareto
• [ ] Pareto items are failure modes, not symptoms
• [ ] Every root cause is labelled [verified] or [hypothesis] with its evidence
• [ ] Containment actions are distinct from corrective actions, each dated and owned
• [ ] Cost of quality uses stated inputs; estimates are labelled as estimates

Anti-Patterns

• [ ] Do not Pareto raw return reasons — triage first, or NTF and remorse will drown the real defects
• [ ] Do not report return counts without units shipped and the exposure window
• [ ] Do not close an 8D at D5 — a corrective action without cut-in verification and recurrence prevention is a wish
• [ ] Do not treat NTF as noise to discard — a high NTF rate is a product or support failure of its own
• [ ] Do not root-cause by vote — teardown evidence and batch correlation, or label it a hypothesis
• [ ] Do not compare return rates across cohorts with different time-in-field — young cohorts always look better