Life After MDM Go-Live: How to Operate CluedIn Successfully

Video overview

Going live with Master Data Management is not the end of an MDM programme. It is the point where the operating model starts to determine whether the investment delivers lasting value.

This session explores what happens after CluedIn goes live, with a practical focus on how data teams keep business users engaged, avoid overwhelming stewards with growing backlogs and turn an initial MDM implementation into continuous data improvement.

A central theme is that traditional stewardship does not scale well when business users are expected to manually investigate every duplicate, validation failure or data-quality issue. CluedIn’s operating model instead allows AI agents to perform more of the repetitive investigation, classification, enrichment and issue detection work, while humans remain responsible for policy, ownership and higher-impact decisions. This aligns with CluedIn’s wider approach of moving stewardship from record-by-record repair towards governed, continuous data operations.

The video also explores how organisations can involve subject-matter experts without forcing them to live inside an MDM platform. Business participation can be federated into familiar workflows, while CluedIn retains governance, auditability and human oversight around data-management actions. CluedIn’s broader operating model is designed around permissions, workflow controls, explainability and human validation where required.

A practical 90-day approach helps teams build momentum after implementation: establish simple workflows and visible wins, expand into additional data domains, give agents more responsibility for repetitive data-management work and measure whether manual effort and recurring data-quality issues are actually falling.

The key lesson is that successful MDM adoption is not about creating a larger stewardship queue. It is about building an operating model where business expertise is captured, repeatable decisions become rules and governed agents increasingly handle the work that does not require human judgement.