Updated 2026-09-16
Time to fill measures the calendar days from requisition approval — or job posting — to candidate offer acceptance, capturing how long a seat stays open during recruiting. It differs from time-to-hire, which often starts at application or first contact.
| Metric | Typical start | Typical end | What it rewards |
|---|---|---|---|
| Time to fill | Req approved / opened | Offer accepted | Closing open headcount quickly |
| Time to hire | Candidate applied or sourced | Offer accepted or start date | Moving individual candidates fast |
| Time in stage | Stage entry | Stage exit | Finding bottleneck interviews |
Every day a requisition stays open carries vacancy cost — lost output, overtime on remaining staff, delayed projects — which feeds cost-per-hire calculations when salary loss is included. Long fills also increase candidate ghosting: strong applicants accept competing offers while your process idles in panel scheduling limbo.
High-volume and bulk hiring programmes track fill time by cohort — how fast did we staff the entire telecaller wave — not just individual reqs. Seasonal peaks punish slow async review: candidates complete AI screens Friday night and expect movement before Monday's competing drive.
Optimising time to fill without sacrificing quality requires structured first rounds that scale — phone screen automation, consistent rubrics — and fast human decisions on finalists rather than cutting interview depth blindly.
Varies wildly by role, market, and seniority. Compare against your own historical baseline and bottleneck stages — not generic benchmarks we cannot verify for your context.
Not if speed comes from automation of repetitive screens and faster scheduling — not from skipping rubrics or reference checks.
Longer fills often increase vacancy cost components in CPH models when salary loss is included. See cost-per-hire for formula context.
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