Time to Promotion
operationalpure operational · mobility · days · organization
The average time employees take to be promoted from their last hire or promotion date.
Why it matters
What you measure connects, through the construct(s) it operationalizes, to outcomes organizations care about. The strongest evidenced links below (effect size × evidence × consequence):
How it’s computed
- Formula
- Average elapsed time since last promotion or hire for promoted employees
- Measurement model
- operational (a formula over systems data) — not a reflective survey scale; “reliability” here means data quality, not internal consistency
What it operationalizes
This metric measures the construct(s) below from operational data. Through them, it connects to the meta-analytic relationship network — the bridge from what you measure operationally to what the science knows.
What we know
Synthesized Bayesian priors over relationships involving this metric’s construct(s) — the meta-analytic evidence, with 95% confidence intervals and between-study heterogeneity (I²). Follow a row for the full distribution, contributing studies, and code.
| Relationship | r (95% CI) | I² | k | Evidence |
|---|---|---|---|---|
| ← Career Development (predicts) | [0.21, 0.25] | — | 1 | meta-analytic |
| ← Career sponsorship (predicts) | [0.09, 0.15] | — | 1 | meta-analytic |
| → Career satisfaction (correlates) | [0.20, 0.24] | — | 1 | meta-analytic |
| → Voluntary Turnover (predicts) | [-0.14, -0.08] | — | 1 | meta-analytic |
| ← Mentoring (predicts) | [0.08, 0.12] | — | 1 | meta-analytic |
| ← Proactive Personality (predicts) | [0.07, 0.25] | — | 1 | meta-analytic |
Use it
Track Time to Promotion and its drivers in the People Analytics Toolbox — the registry’s evidence wired into deployable measurement.
Related metrics
Programmatic access: /api/v1/metrics/metric.time_to_promotion · /api/v1/evidence-statements?construct=construct.internal_mobility.