Nasdaq measures governance success through three core metrics, each tied to business impact. Discovery efficiency tracks how business users (not just data scientists) find assets using business-aligned terms. Quality monitoring measures failure frequency and resolution time for regulatory obligations and market decisions. Utilization and cost-benefit analysis tracks who's using assets and compares production costs against value — including soft numbers like regulatory fines avoided.
Key takeaways:
Discovery metrics must account for different personas — business users need business-aligned terms, not just technical documentation
Quality metrics track asset failure frequency and time to resolution, critical for regulatory obligations and market participation decisions
Utilization metrics show how many users and AI systems actually leverage assets, revealing what's valuable versus what's waste
Cost-benefit analysis compares production/governance costs against direct revenue (selling datasets) and soft value (fines avoided)
Cross-market metrics measure global reuse and sharing patterns as governance expands beyond single-entity thinking
