Where the financial exposure appears
Poor data can increase remediation effort, prolong testing, create manual workarounds, delay business validation, and introduce uncertainty into cutover planning. These effects can accumulate even when no single data issue appears financially significant.
What executives should ask
Which data risks could affect the critical path? What is the estimated remediation effort? Which issues have business owners? What evidence supports readiness? Which risks are accepted, and by whom? These questions connect data management to program governance.
Make risk measurable
Executives do not need every technical detail. They need a concise view of exposure, impact, ownership, trend, and required decisions. A structured readiness view can make that information easier to govern.
Axiums perspective
Data risk should be visible in the same language as other transformation risks: impact, probability, ownership, mitigation, and readiness.
- Connect data issues to cost and milestone impact.
- Track ownership and remediation, not only defect counts.
- Make residual data risk explicit.
- Use evidence to support executive decisions.