5WHY Root Cause Analysis Guide
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About this skill
Problem
Many issue investigations quickly drift toward explanations like “operator error” or “normal wear,” without a concrete control or root-cause test. 5WHY is often treated as asking “why” five times, but the useful discipline is to validate each answer and check whether a proposed action can prevent the same failure from recurring.
How It Works
- The user provides an initial issue, such as a machine alarm, surface scratch, or output drop.
- The agent starts a structured follow-up: “Why did XX occur?”
- Each response is checked in three layers: conciseness, requiring one cause at a time; invalid-answer filtering, removing subjective judgments, uncontrollable factors, and normal operating states; and ambiguity confirmation, asking when the answer cannot be reliably classified.
- Once a response passes validation, the agent proposes one specific countermeasure and checks whether that countermeasure can prevent the same issue from happening again.
- If it cannot, the answer is treated as an intermediate cause and the next question is “Why did the previous answer occur?” If it can, the agent outputs the root cause and summarizes the full analysis path.
Boundaries
This skill fits fault diagnosis, quality defects, and production anomalies where the analysis can be closed through cause-and-effect reasoning. It is less suitable for one-off advice, vague complaints, or problems that require external data lookups. Each turn should stay focused, ask one question at a time, and avoid mechanical five-round counting; the stopping condition is whether the proposed action validates the root cause.
Use Cases
- After a machine alarm stops production, ask structured why questions and test whether a fix eliminates the fault.
- When product surface scratches recur, filter out subjective answers like operator carelessness and continue root-cause tracing.
- During an efficiency-drop review, split multi-part causes into single elements and produce a complete analysis chain.
- In a quality anomaly retrospective, validate whether proposed actions prevent the same defect from reoccurring.
Best For
- Equipment engineers handling machine alarms: need actionable fixes rather than operator-error explanations.
- Quality engineers reviewing surface scratches: need to split subjective causes and verify the root cause.
- Production managers analyzing output drops: need to separate normal wear from abnormal triggers and record findings.
- Operations engineers doing anomaly retrospectives: need a complete question chain and final conclusion.
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