Automation debt and workflow diagnosis are becoming core productivity practices

Recent guidance emphasizes that successful runs do not guarantee correct outcomes: automations need owners, documentation, dependency tracking, monitoring, and retirement decisions. Workflow analysis frameworks recommend mapping actual execution, defining primary and guardrail metrics, and diagnosing process, technology, data, user, and governance problems before automating.