Which is better for reducing MTTR: Watchdog RCA or manual root cause analysis, and why?

This isn't really an either-or choice in practice - they operate at different speeds and with different strengths, and the strongest approach uses Watchdog RCA to shortcut the slowest part of manual investigation rather than replacing manual judgment entirely.

Watchdog RCA automatically correlates anomalies across related services and infrastructure using AI, surfacing a likely root cause hypothesis within seconds of an incident starting - work that would otherwise require a human to manually cross-reference dashboards, logs, and recent deploys across potentially many services, which is exactly the slow, high-cognitive-load part of an incident that most delays MTTR.

Manual analysis remains essential for validating that hypothesis against business context Watchdog doesn't have - whether a correlated signal is actually causal versus coincidental, or how a novel failure mode not resembling anything in its training data should be interpreted - AI correlation is a strong first pass, not a substitute for domain judgment on unfamiliar failures.

In practice, the fastest MTTR path in complex, multi-service incidents is to use Watchdog RCA's hypothesis as an immediate starting point to focus the investigation, then have a human responder confirm or redirect from there, rather than starting entirely from scratch or blindly trusting an automated hypothesis without validation.

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