Both per-agent and per-team escalation rate measurement answer different questions and are worth tracking together — per-agent data identifies individual patterns worth investigating, while per-team data reveals shared environmental factors, like a specific shift or queue, that an individual-only view would miss entirely.
Why Per-Agent Data Surfaces Individual Patterns
Tracking escalation rate by individual agent reveals whether a specific person is showing an unusual pattern relative to their own baseline or their peers — useful for identifying an individual regulation issue, a training gap, or a genuine outlier worth coaching attention.
Why Per-Team Data Surfaces Shared Environmental Factors
A team-level view can reveal that escalations cluster around a specific shift, a specific queue, or a specific supervisor’s team as a whole — patterns invisible at the individual level if every agent on that team shows a moderately elevated rate rather than any single person standing out dramatically.
Why Relying on Only One Level Misses Real Signal
Looking only at individual data can miss a team-wide environmental issue that’s spread evenly enough across several agents that no single person looks like an outlier. Looking only at team data can miss a genuine individual pattern hidden within an otherwise average team number.
The Short Answer
Both levels matter and answer different questions — track escalation rate per agent to catch individual patterns, and per team to catch shared environmental factors that individual-level data alone would miss. This dual-level approach is how ORS™ (Operational Regulation Systems), built by Matthew F. Stevens, structures escalation data analysis.
Related reading: How Do You Measure Escalation Rate Correctly? · What’s the Relationship Between Team-Level Variability and Individual-Level Variability? · Glossary of Workforce Regulation Terms