Time to Fill
The number of days between a job requisition opening and a candidate accepting an offer for it.
Time to fill is the number of calendar days between a job requisition opening (the day it's approved and posted) and a candidate accepting an offer for that specific requisition. It measures how long a role sits open — a requisition-level clock, not a candidate-level one.
The formula is simple on paper: time to fill = offer-accepted date minus requisition-open date, in calendar days. The complexity is in getting the two endpoints right. The start date should be when the requisition was formally approved and opened for applications, not the day someone first thought about the role — using an informal start date understates the real number. The end date is the day the candidate accepts, not the day they start work (that gap belongs to onboarding, not time to fill). Most teams track this per requisition and then average or trend it by role type, location, or recruiter, since a single company-wide average tends to hide which specific roles are actually the slow ones.
Two requisitions, same week, different outcomes
Two warehouse-associate requisitions open on the same Monday at two different locations. Location A fills in 9 days: sourcing was fast because a referral pool existed, and the interview-to-offer step took two days. Location B takes 26 days: the posting sat for a week before real sourcing began, and a scheduling back-and-forth added another five days once applicants started coming in. Averaged together, the two requisitions show a blended time to fill of about 17.5 days — a number that hides both the strong result at Location A and the real, fixable delay at Location B.
In staffing & high-volume hiring
For staffing agencies and high-volume hiring teams, time to fill is usually the single number a client or hiring manager asks about first, because an open requisition has a direct cost: unfilled shifts, overtime for existing staff, or a client contract at risk. It's driven by both sides of the funnel — how fast candidates are sourced and screened, and how fast the pipeline moves once someone applies. A slow ATS, manual follow-up, or a scheduling back-and-forth over email all show up directly in this number.
Common mistakes
- Starting the clock from when a manager verbally mentioned needing to hire, instead of the requisition's actual approved-and-open date — this quietly inflates or deflates the number depending on how the informal start gets remembered.
- Confusing time to fill with time to hire (a candidate-level metric) and drawing the wrong conclusion about where a slowdown is actually happening — see time to hire for the distinction.
- Reporting one blended average across very different role types, which hides the specific roles or locations that are actually driving the number up.
Related terms & reading
Time to Fill FAQ
What's a good time to fill benchmark?
It varies heavily by role type and industry — a high-volume hourly role might fill in days, while a specialized or executive search can take months. The more useful comparison is your own trend over time and against your own past requisitions of the same type, not an industry-wide average.
What's the formula for time to fill?
Time to fill = the date an offer is accepted minus the date the requisition was opened/approved, measured in calendar days.
Does time to fill include the onboarding period?
No — the clock stops the moment a candidate accepts an offer. Everything after that (paperwork, background checks, the actual start date) is a separate part of the funnel, not part of time to fill.
Why does time to fill vary so much by role?
It reflects both how many qualified candidates exist for a role and how many steps the hiring process has for that specific role type — a role with a smaller candidate pool or an extra compliance step (like a license check) will naturally take longer regardless of how efficient the recruiting team is.
Should time to fill be tracked per recruiter?
It can be, but carefully — a recruiter working harder-to-fill role types will naturally show a higher average than one working easier roles, so comparing recruiters directly on this number without accounting for role difficulty can be misleading.
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