How should root cause analysis proceed when data shows multiple independent incidents with different causes?

• A. Treat each incident separately and stop at the first observed cause.
• B. Aggregate data to identify systemic factors; look for underlying latent conditions; use cross-case synthesis to find common root causes or systemic failures affecting multiple incidents.
• C. Assume all are isolated and unrelated.
• D. Focus exclusively on administrative controls.

Answer: (B)

When several independent incidents occur with different immediate causes, the aim is to uncover systemic factors that allow failures to happen across cases. Pooling the data from all incidents reveals patterns or weaknesses not visible when each event is looked at in isolation. These patterns point to latent conditions—underlying flaws in design, procedures, training, supervision, governance, or culture—that create opportunities for different failures to occur.

Cross-case synthesis involves comparing incidents to find common root factors or systemic failures, even if the surface causes differ. This helps identify the real sources of risk that span multiple events and guides corrective actions that raise defenses across the whole system rather than just addressing a single incident.

This approach is more effective than treating each incident separately or assuming all are isolated, since those methods miss the bigger picture of how a system’s design and processes can enable repeated failures. It’s also broader than focusing only on administrative controls, because root causes may lie in design flaws, equipment or maintenance issues, human factors, or governance gaps that require more than procedural fixes. By identifying and addressing these systemic factors, you can implement targeted, wide-ranging improvements to prevent multiple incidents in the future.