3 ideas
Data management is decomposed into functions (what activities must be performed, like data quality or metadata management) and capabilities (the combination of people, processes, and technology needed to execute them). This separation lets an organization assess whether it has the means to perform a function before assigning ownership or building processes around it.
A data management operating model defines how roles, processes, and structures connect across the organization so that governance is not a standalone department but an integrated operating layer. It specifies decision rights, accountability, and the interaction points between business and IT, turning abstract governance principles into a repeatable working mechanism.
Rather than starting with grand strategy, the framework views data management as assembled from concrete deliverables and artifacts that each function produces. By identifying the tangible outputs first, an organization can reverse-engineer the processes, roles, and tools required, making implementation traceable and verifiable instead of aspirational.