When this topic matters
When managing operators, you need metrics. But wrong metrics can be worse than none — they lead to optimizing wrong things.
Question is not just "what to measure", but "what does measurement cause" — what behavior does it motivate?
What happens in practice
Typical metrics: call count, call duration, connection rate, conversion rate, meeting count.
Problem: some metrics work against each other. Maximizing call count goes against call quality. Maximizing call duration may be wasting time.
Why it fails
Too many metrics: operator does not know what to optimize. Or optimizes what is easiest, not most important.
Wrong metrics: measuring call duration can lead to prolonging unnecessary conversations. Measuring call count can lead to quickly ending promising conversations.
Missing context: 50 calls per day may be low or high, depends on segment and quality.
How to think about it
Principle: 1-2 primary metrics (what you actually want), 2-3 supporting metrics (context and diagnostics). No more.
Primary metric should be tied to outcome (meetings, pipeline), not activity (call count).
Activity metrics are for diagnostics ("why no meetings?"), not for management.
- Primary: conversion rate, qualified meetings
- Supporting: connection rate, qualified call duration
- Diagnostic: call count, time on line
- Rule: 1-2 primary + 2-3 supporting
What you gain and what you lose
Outcome metrics: right motivation, but harder to diagnose problems.
Activity metrics: easy control, but can lead to optimizing wrong things.
Combination: both types, but with clear priority.
When to apply
Always when managing team. But adapt metrics to phase: onboarding (more activity), experienced operator (more outcome).
Regularly review — metrics that made sense at start may not make sense when scaling.
1-2 primary metrics tied to outcome + 2-3 supporting for diagnostics. Activity metrics are for understanding "why", not for management. Adapt to phase and review regularly.