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C16 · PRACTICE GUIDE

Metrics & Analytics

Define measures that support decisions, with explicit populations, formulas and limitations.

A metric is useful when the team knows what decision it supports and how to interpret it. Distinguish customer outcomes, adoption behavior, operational performance and provider economics. Combine leading indicators with results instead of relying on a single headline number.

Put it into practice

  1. For each measure, record the decision, definition, formula, cohort, time window, source and owner.

  2. Set a baseline and target suitable to the context. Mark unavailable or unreliable data and investigate shifts before interpreting them.

  3. Review the metric set for gaming, overlap and unintended incentives. Retire measures that do not affect decisions.

What good evidence looks like

A versioned metric dictionary and a review that connects measures to decisions.

WATCH FOR

A common failure mode

Comparing inconsistent cohorts, mixing stock and flow measures or presenting a generic target as a universal benchmark.

What to measure

Definition coverage, data quality and the number of material decisions supported by reliable measures.

YOUR NEXT ACTION

Use the metric explorer to document one decision and the measure it needs.

Open the metric explorer

Practice guidance · Framework v1.0 · Published September 2026. Adapt the method to your business model, customer segment and decision authority.