diagnostic-action

Root cause analysis systematically identifies why a problem occurred by generating multiple plausible hypotheses, examining their mechanisms, and ranking them by likelihood and impact. This approach uncovers the underlying reason rather than just treating symptoms, essential for debugging, incident investigations, and preventing recurrence.

Diagnosis identifies and explains why a problem happened; fixing prescribes a solution. Diagnosis comes first—it clarifies root causes, ranks competing hypotheses, and identifies what data you're missing before you act. This prevents applying incorrect fixes based on incomplete understanding.

Effective diagnosis creates several plausible hypotheses with documented mechanisms showing how each could cause the observed symptoms. Rank them by likelihood and impact, then identify which missing data would confirm or eliminate each candidate. This structured approach prevents premature conclusions and guides investigation priorities.

Use root cause analysis for incidents with significant impact, recurring failures, or systemic problems where understanding why matters more than quick fixes. Troubleshooting addresses immediate symptoms; root cause analysis prevents the problem from reoccurring and applies across IT systems, software, networks, and infrastructure.

Document observed symptoms clearly—what failed, when it occurred, what changed, and the scope affected. Collect environmental details, error logs, and timeline data. Diagnostic analysis requires comprehensive symptom description; missing context limits hypothesis ranking and may hide the true root cause.

Root cause analysis applies to debugging software, investigating IT system failures, analyzing network incidents, examining infrastructure problems, and reviewing operational processes. The diagnostic approach—generate hypotheses, rank by likelihood, identify missing data—works consistently across all these domains.