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Rapid Recall Key 01–20

  1. Capability Maturity Assessment: a process-improvement assessment using a maturity model to evaluate how capability characteristics evolve from ad hoc to optimal.
  2. DMMA: a method for ranking Data Management practices against maturity levels to characterize current state and improvement opportunity.
  3. Levels: 0 No Capability; 1 Initial/Ad Hoc; 2 Repeatable; 3 Defined; 4 Managed; 5 Optimized.
  4. L1: person-dependent, siloed, inconsistent practice with weak governance.
  5. L2: repeatable minimum discipline; defined roles/processes begin, with more consistent tools/oversight.
  6. L3: institutionalized scalable standards/processes, coordinated policy, reduced manual work, more predictable outcomes.
  7. L4: measured/controlled capability with performance metrics, risk management, centralized governance, standardized tools.
  8. L5: highly predictable capability focused on continuous improvement/optimization, automation/change management, and well-understood metrics.
  9. Each level builds capability characteristics needed for the next; acceleration can have cost/impact but does not erase prerequisites.
  10. Criterion score = effectiveness/progress on an item; maturity level = macro capability characteristics.
  11. Activity, Tools, Standards, People and Resources.
  12. Activity asks whether the process exists, is defined, is executed effectively/efficiently, and produces intended outputs.
  13. Tools asks whether common tools support/automate work, users are trained, tools are available/configured, and technology planning supports future capability.
  14. Standards asks whether common rules are documented, enforced, governed, and change-managed.
  15. People/Resources asks whether staffing, skills, knowledge, training, roles, and responsibilities are sufficient.
  16. Current state = evidence-supported maturity baseline today.
  17. Target/desired state = capability level needed or aspired to support strategy/risk needs.
  18. The gap identifies capability shortfall and helps prioritize risk and improvement.
  19. Regulation; Data Governance; readiness for process improvement; organizational change; new technology; Data Management issues.
  20. Evaluate current state; support operational/strategic direction; develop cohesive data vision; enable an integrated improvement plan.

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