CMMI Level 5 Root Cause Analysis

Problem It Addresses

Engineering and quality teams can often trace a failure to a person or to not enough time, but it is harder to prove why the system allowed it. This skill targets a specific incident, customer complaint, Cpk below 1.33, defect-density exceedance, or recurring audit finding. It guides a structured root cause analysis flow that turns symptoms into verifiable facts, statistically comparable causes, and actionable corrective or preventive measures, closing with both technical and management accountability.

How It Works

• Trigger assessment: decide whether the issue is worth an RCA, then define scope, team, and roles such as RCA lead, problem statement owner, domain expert, recorder, and management representative.
• Quantified problem statement: describe frequency, magnitude, trend, impact, loss, and baseline deviation, rather than subjective language; it can use Excel, PDF, screenshots, or Word inputs to extract key data.
• Broad cause identification: expand candidate causes using 5M1E, 8P, process steps, or PPT, with a human-first pass before AI-generated causes are compared and merged.
• Deep root cause mining: apply 5Whys across why it happened, why it escaped, and why the system allowed it, then test causes with the MIN principle—Missing, Incomplete, or Not followed—while requiring correlation, hypothesis testing, or at least two independent data points for key causes.
• Double zero closure and measures: verify technical zeroing and management zeroing checklists, then use 5Hows to confirm Owner, Deadline, acceptance criteria, validation method, and resource availability.

Boundaries and Notes

It fits teams that need a structured RCA record, cross-role review, and process improvement, especially for quality incidents, customer complaints, performance deviation, or schedule/cost/quality drift. If the issue is only a one-off operational mistake, lacks basic factual evidence, or requires automated incident forensics, this skill mainly provides the analysis framework and report structure rather than collecting logs, running experiments, or producing production-ready fixes.