A lightweight operating model connecting ownership, classification, lineage, quality, access, lifecycle, third-party use, AI governance and assurance to normal delivery and operations.
Operating cycle
and domains
decision rights
baseline
dependencies
retention / sharing
exceptions
remediation
Decision rights matter
Owners, stewards, platform teams, security, privacy, risk and data teams need clear responsibilities and escalation paths. A role without decision rights is not an effective governance role.
Use a clear control hierarchy
Policy → Standard → Control → Procedure / Pattern → Evidence
This keeps policy connected to delivery and makes assurance practical.
Govern the real data flow
For critical data, governance should be able to show owner, classification, authoritative source, lineage, quality rules, access model, retention, third-party use, AI use, open exceptions and current review evidence.
Measure control, not activity
- % of critical datasets with named owners.
- % with current classification and lineage.
- High-risk access exceptions.
- Undefined retention or unreviewed third-party transfers.
- AI use cases with incomplete provenance.
Core principle
Governance works when decision rights and evidence are embedded in normal delivery and operations.