metric-diagnostics

What problem does it solve?

Diagnose why a metric changes or differs from expectation by reproducing the metric, choosing the right comparison, validating likely drivers, and producing a calibrated explanation. Use when the user needs to understand what drove a metric movement, anomaly, gap, or discrepancy.

Core Features & Use Cases

• Reproduce the metric behavior across contexts to verify consistency
• Validate driving factors using multi-source evidence and live reads
• Generate calibrated explanations suitable for dashboards and reports
• Use cases include anomaly investigations, reconciliation, and trend explanations

Quick Start

Identify the diagnostic question and initiate a reproducible metric-and-driver analysis to surface the main driver.