To address this, the Data Management Capability Assessment Model (DCAM) provides a structured blueprint to establish a mature data governance program. Rather than treating data management as a one-time project, DCAM informs a program by embedding it into a company’s daily operational fabric. In short, to enjoy the benefits of the data you have, you need to govern it. So how do you go about that?
Strategy and Funding First
Many initiatives fail because they start with technology instead of a business case. DCAM forces you to align your data management strategy with high-level organizational objectives first. This ensures that your governance efforts are justified, funded, and visibly endorsed by executive management. Without this foundational support, governance often becomes an intermittent priority rather than a sustainable business function.
Managing Data as Meaning
A critical shift that DCAM introduces is the concept of managing data as “meaning.” Proper governance requires us to define data by what it represents in the real world, such as a customer, a product, or a transaction. This approach helps unravel data silos and creates a shared business glossary. By using DCAM to inform your architecture, you ensure that every data attribute is understood at its atomic level, eliminating the common problem of different departments using the same terms to mean different things.
Structure and Accountability
DCAM provides a rigorous structure for roles and responsibilities. It helps you establish a formal Office of Data Management and appoint executive owners, such as a Chief Data Officer. The framework clarifies the roles of data owners and stewards to ensure clear accountability for data quality and access. It also integrates the Internal Audit function, ensuring that your policies are not just suggestions but are enforceable and auditable.
The Data Control Environment
This component is where theory meets practice, making governance operational across the entire data supply chain. DCAM encourages collaboration between business units and cross-organizational control functions like information security and privacy. This ensures that data is protected and managed consistently from its initial source to its eventual disposal.
AI & governance
Modern governance programs must address the rise of Artificial Intelligence and advanced analytics. DCAM provides specific guidance here, emphasizing that AI is essentially dead in the water without high-quality, secure data. It informs your program by integrating data ethics to move beyond simple legal compliance. By following DCAM, you establish a Code of Data Ethics to monitor whether the outcomes of your data use are fair and appropriate.
Measuring Progress
Ultimately, DCAM acts as a benchmark. By using its six-point scoring system, you can objectively identify gaps in your capabilities and create a prioritized roadmap for improvement.10 This transforms data management from a subjective art into a quantifiable science.
DCAM is essentially the architectural blueprint for your data house that plans, identifies the necessary materials, and ensures the structure remains solid for years to come.