COMPEL Glossary / GL-09
Measurement Model
The structured framework for quantifying AI transformation progress and outcomes across four levels: strategic KPIs (organization-level), portfolio KPIs (aggregate across use cases), use-case KPIs (individual initiative performance), and operational KPIs (system-level health).
What this means in practice
The measurement model connects operational metrics upward through the hierarchy to demonstrate strategic value, and includes baseline methodology, target-setting logic, and variance analysis procedures.
Context in the COMPEL framework
The measurement model is designed in Model, instrumented in Produce, executed in Evaluate, and refined in Learn. It provides the quantitative foundation for value realization and continuous improvement.
Where you see this
Measurement Model is most commonly referenced when teams work across the Model , Produce , Evaluate and Learn stages — especially within the Value Realization layer . It appears in governance artifacts, assessment instruments, and delivery playbooks wherever COMPEL is operationalized.
Related COMPEL stages
Related domains
Synonyms
KPI framework , metrics framework , performance measurement system
See also
- Value Realization — The end-to-end process of defining, tracking, and verifying the business value delivered by AI initiatives — from initial value thesis through baseline measurement, deployment, post-deployment review, and ongoing benefit tracking.
- AI Operating System — A structured, repeatable management system that enables an organization to plan, govern, deliver, measure, and continuously improve AI capabilities across people, process, technology, and governance dimensions.
- Evidence Pack — The complete, auditable collection of artifacts, test results, decision records, and attestations that demonstrate an AI system meets its governance, compliance, and operational requirements.
Related Terms
Other glossary terms mentioned in this entry's definition and context.