Change failure queue

Failure creates more work

A failed change often creates a second stream of work: diagnosis, communication, rollback, repair, validation, and follow-up. If that stream is not visible, planned feature work may appear to slow for unexplained reasons while recovery work consumes capacity.

A concrete example

Suppose an illustrative release causes elevated errors. The deployment is rolled back quickly, but two follow-up fixes and a verification task remain open for a week. The original failure is one event; the remaining items form a recovery queue that should be tracked separately from new feature demand.

Use it for learning

Track queue age, reason, service, and whether the item is customer-facing or preventive. Pair the queue with change failure rate and recovery time. A large queue may indicate weak follow-through, but a small queue can also mean work is being handled informally and is not recorded.

Limitations

Definitions of failure and closure vary. Security findings, rollbacks, and incidents may enter different systems. Align event boundaries before comparing teams or time periods.