Trainer Kit
Everything a DAMA chapter facilitator needs: the Meridian Retail case study, per-chapter one-pagers, warm-up questions, and ready-to-run workshop agendas.
Meridian Retail grew by acquisition: point-of-sale, e-commerce, loyalty, and warehouse systems that never agreed on what a 'customer' or 'net revenue' means. After a mis-sent marketing campaign reached customers who had opted out — and a board pack showed two different revenue numbers — the CEO appointed a CDO and funded a data management program. This platform is that program's control plane, eighteen months in: real progress, honest gaps.
Operating across India and the EU, Meridian must satisfy both the DPDP Act 2023 and GDPR — consent, purpose limitation, and retention rules appear throughout the story.
Chapter 3 — Data Governance
The exercise of authority, control, and shared decision-making (planning, monitoring, and enforcement) over the management of data assets. Governance sits at the hub of the DAMA wheel because every other knowledge area depends on it.
- •Enable the organization to manage data as an asset
- •Define, approve, communicate, and implement data policies, standards, and metrics
- •Monitor and guide policy compliance and data management maturity
- •Sponsor, track, and oversee the delivery of data management projects
- •Define data governance for the organization (readiness, discovery, alignment)
- •Establish the operating framework: councils, forums, stewardship model
- •Develop and maintain policies, standards, and the business glossary mandate
- •Underwrite issue management, escalation paths, and compliance reporting
- •Embed governance — move from project to sustained operating practice
- •Data governance strategy, charter, and operating framework
- •Policies, standards, and procedures
- •Roadmap, scorecard, and issue log
- •Business case and value statement for governance
- •Data Governance Council
- •Data Governance Office / DG Lead
- •Data Owners
- •Data Stewards
- •CDO
- •Policy compliance rate
- •Value delivered by governed projects
- •Issue resolution cycle time
- •Steward coverage by domain
- •Governance ≠ management: governance decides how decisions get made (oversight); management executes (E of the V — governance is 'do the right things', management is 'do things right').
- •Know the typical operating models: centralized, replicated, federated — and when each fits.
- •The most-tested artifacts: charter, policy hierarchy (policy → standard → procedure), and the RACI between owners, stewards, and custodians.
Before governance, every data dispute was settled by whoever escalated loudest. G. Patel chartered a governance council with the CFO as sponsor, published a three-tier policy hierarchy (policy → standard → procedure), and gave every domain a named owner and steward. The masking policy for customer PII was the first policy to go from draft to enforced, with evidence.
Open Data Governance (/governance) — advance a policy through its lifecycle, show the policy matrix and masking evidence export.
Policies with owners, an issue log with SLAs, and governance embedded in delivery gates rather than bolted on after.
- Meridian chose a federated model — central policy, domain stewardship. What in its history makes that fit?
- Which policy would YOU enforce first at Meridian, and what evidence would prove enforcement?
- How does the council avoid becoming a bottleneck for delivery teams?
- A.Governance is technical; management is business-oriented
- B.Governance ensures data is managed properly (oversight); management executes the work ✓
- C.Governance only handles security; management handles the rest
- D.There is no difference — the terms are interchangeable
- A.Procedure → Standard → Policy
- B.Policy → Standard → Procedure ✓
- C.Standard → Policy → Procedure
- D.Policy → Procedure → Standard