The enterprise defines how its data assets are managed and improved, consistent with its strategy and objectives; it communicates the data management strategy to every stakeholder and assigns roles and responsibilities. A data management function is created and made responsible for the activities that serve the objectives. Roles and responsibilities cover both data management and how governance and the function work together. Business and technology develop the strategy jointly, so its objectives, priorities and scope mirror the enterprise's objectives and have stakeholder agreement. Those objectives, priorities and scope are communicated and adjusted in response to feedback. Metrics show whether the objectives are being met. The sequenced plan for putting the strategy into effect is tracked and updated after progress reviews. Statistical and quantitative methods test how well the strategic objectives serve business objectives. The enterprise looks into innovative processes and new regulatory requirements so the programme remains fit for future needs, and it contributes to good practice in its industry.
This control maps to 1 controls across 1 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.
The graph holds this control, the 1 it maps to, and the evidence behind each claim, over MCP and REST.