KB article

Business Definitions vs Calculation Logic

A metric is not just a formula; it is a business definition with boundaries.

arf-kbsemantic-integritysemantic-contractcanonical-metricsemantic-annotation

TL;DR

  • Logic alone does not describe meaning.
  • Definitions must explain scope, exclusions, and intent.

The problem

  • Measures are created without a clear business definition.
  • AI can read the formula but not the intent.

Why it matters

  • Without intent, AI answers can be correct but misleading.
  • Stakeholders may interpret results differently.

Symptoms

  • Stakeholders ask “What does this include?”
  • Two teams interpret the same measure differently.

Root causes

  • Definitions live in emails or docs, not in the model.
  • No standard for describing business meaning.

What good looks like

  • Every KPI includes a written business definition.
  • Definitions are stored alongside the calculation.

How to fix

  • Add descriptions to measures with scope and exclusions.
  • Create a lightweight metric dictionary.
  • Review definitions during model changes.

Pitfalls

  • Overly technical definitions without business context.
  • Keeping definitions in a separate system only.

Checklist

  • Business definition in measure metadata.
  • Scope and exclusions documented.
  • Definition owner identified.

Framework placement

Primary ARF layer: Semantic Integrity. Diagnostic bridge: semantic-reliability, change-reliability.