Why CMDB Fails Even Before Discovery Is Implemented

[Abhijeet Upadh2]

In most post-mortems, CMDB failure is blamed on Discovery not working, integrations being unreliable, or data quality tools not being tuned properly. In reality, I’ve seen CMDBs fail long before any of those components were even switched on.

The failure usually starts with intent. Ask five stakeholders why the CMDB is being implemented and you’ll often get five different answers: Incident wants faster resolution, Change wants risk visibility, Asset wants compliance, Security wants assurance, and Architecture wants a system of record. None of these are wrong—but without prioritisation, the CMDB becomes everything and nothing at the same time.

The next issue is scope. Many teams attempt to model the entire enterprise landscape upfront because “Discovery can find it anyway.” What they end up with is a CMDB that is wide but shallow—thousands of CI records with minimal ownership, incomplete relationships, and no real consumer trust. Once trust is lost, no tooling can recover it.

Another early failure is treating CMDB as a technical implementation rather than a service capability. Ownership is vague, governance is light, and CI classes exist without clear lifecycle accountability. When incidents or changes don’t meaningfully depend on CI accuracy, people naturally stop caring about data quality.

The best CMDB implementations I’ve seen were deliberately conservative at the start. They aligned to one or two high-value use cases, limited CI classes aggressively, and enforced ownership early. Discovery didn’t “fix” the CMDB—clear purpose and consumption did. Discovery simply amplified whatever design decisions were already in place.