A complete absence of reported issues immediately after introducing an enterprise Data Issue process is more likely to indicate lack of confidence in the governance process than genuinely flawless enterprise data. The certification material explicitly identifies lack of credibility in the process's ability to effect change as the plausible explanation.

Effective issue management depends on organizational trust. Employees need to believe that documenting an issue will lead to triage, ownership, escalation, root-cause investigation, remediation, and appropriate communication. If previous problems disappeared into a queue without action—or if raising defects creates organizational friction—users may simply stop reporting them.

DAMA-DMBOK2 treats Data Governance implementation as an organizational-change challenge rather than a purely procedural exercise. Governance must demonstrate authority, responsiveness, transparency, and measurable outcomes to establish credibility.

For Data Quality, issue volumes must also be interpreted carefully. “Zero issues reported” is not equivalent to “zero defects.” Complementary evidence should come from profiling, automated monitoring, quality metrics, user feedback, reconciliation, and operational outcomes.

Management should investigate reporting barriers, communicate resolved cases, establish clear escalation paths, and demonstrate that identified problems produce tangible improvements.

Reference Topics: DAMA-DMBOK2 Chapter 3 — Governance Adoption and Credibility; Data Issue Management; Chapter 13 — Issue Identification, Escalation, Root-Cause Analysis and Remediation.

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