Multi-Metric Correlation Detection

The most valuable anomalies are not in individual metrics — they are in the relationships between metrics. Revenue is stable, but conversion rate dropped and deal count increased. Individually, neither conversion rate nor deal count is anomalous enough to trigger an alert. Together, they reveal a pattern: the team is closing more deals at a lower rate, suggesting quality degradation. Multi-metric correlation detection monitors the relationships between metrics and flags when the correlation structure changes. Metrics that normally move together stop moving together. Metrics that are normally independent start correlating. These structural changes are often more significant than individual metric deviations because they indicate a systemic change, not a one-time event.