---
name: mohitagw15856/rma-failure-analysis
source: https://app.decimal.ai/s/mohitagw15856-rma-failure-analysis@1/SKILL.md
source_sha256: 76ac06cbcdf7
---

# 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