Enterprise metric systems: one definition for business, BI, and AI
A metric system that works for both people and AI must define meaning, calculation, scope, ownership, and verification.
Resolve identical names with different meanings
Revenue, sales, bookings, and GMV may describe different scopes across teams. Start by defining business meaning, source data, filters, and time grain.
Manage calculation logic as an asset
Do not leave metrics inside dashboard formulas or personal SQL. Record formulas, dependencies, aggregation, refresh cadence, and version history.
Design dimensions, hierarchy, and scope
The same metric can have different visibility and aggregation rules at group, region, store, or product level. Design metrics together with dimensions and permissions.
Add explanations and validation for AI
AI needs more than a number. It needs meaning, supported dimensions, exception boundaries, and example questions. BuildTable packages this context with the model.