Beyond the Dashboard | Principle 9: Reconcile Metric Definitions Before Analysis
Teams don’t argue about numbers; they argue about definitions. Inconsistent metrics like MAU erode trust, stall decisions, and mislead AI at scale. Fix it upstream: build a Metric Dictionary with clear names, sources, formulas, and owners. One name, one definition.
TL;DR (for those whose last meeting was a debate about definitions)
- If teams argue about numbers, it’s usually not math they’re debating but definitions. Vague definitions aren't a data issue; they're a systems failure.
- Inconsistent metric definitions (like “Active User”) create conflicting truths, erode trust, and stall decisions. Your MAU might be four metrics in a trench coat pretending to be one.
- AI usually makes it worse, unless you’ve already solved the definition problem upstream. Feed it inconsistent data and you’ll get confident-sounding nonsense at scale.
- What you need is a Metric Dictionary, one source of truth with each metric's name, source, formula, and owner.