Metric Baselines and Owners

A metric without a baseline is a number without a verdict. Knowing that an agent resolved 72 percent of conversations tells you nothing until you compare it with the bar: how well a good person does the same job. There is no universal pass mark, so each use case needs its own baseline set against human performance.

Baselines also fail quietly when nobody owns them. Thresholds that drift, alerts that nobody reads, and dashboards without a named reviewer turn observability into decoration. Each core metric needs both a threshold and a person accountable for reviewing it.

Anchor every metric to a human bar

• Define baselines for the five core areas: response quality, user trust, system health, conversation abandonment, and escalation rate.
• Set the threshold against how well a competent person performs the task, not against an arbitrary percentage.
• Record a named review owner for every metric so a breach has a clear first responder.
• Treat baselines as living values that you revisit when the use case, model, data, or audience changes.

Wire thresholds into review routines

1. Document each metric with its definition, data source, baseline value, threshold, and review owner in a single register.
2. Use session tracing and analytics to measure actual quality, abandonment, and escalation rates before fixing the baseline numbers.
3. Define the action each threshold breach triggers, such as investigation, prompt or topic changes, or a temporary rollback.
4. Schedule recurring reviews where owners confirm metrics hold or adjust thresholds with a recorded rationale.