Data stewardship
The human discipline of curating, approving, and correcting master data — the role that owns "is the customer record actually right?"
Data stewardship is what happens *after* the engine has done its work. Stewards review ambiguous merges, approve or split borderline clusters, edit survivorship rules when defaults produce wrong values, and respond to escalations from downstream consumers ("this customer's address looks wrong").
In a small org one engineer does this part-time. In a large org it's a dedicated role (or team) with explicit SLAs around review-queue throughput.
MDM tools that ignore stewardship — that just spit out clusters and assume the user agrees — produce technical debt fast. The good tools surface ambiguous decisions in a queue, capture the steward's reasoning in the audit trail, and let policy changes (rule edits) flow into future runs.