Recruiting dashboards tend to fill up with activity counts: applications received, interviews scheduled, emails sent. Activity is easy to measure and tells you almost nothing about whether the process works.
The eleven below measure outcomes and constraints. Each has a formula, a definition that has to be pinned down before the number means anything, and a way it goes wrong.
Speed
1. Time to fill
Formula: days from requisition approved to offer accepted, averaged across filled roles.
This measures the business cost of a vacancy. The definitional trap is the start point: approval, publication, or first sourcing activity. Publication is the most commonly used and the most comparable across companies. Whatever you choose, apply it everywhere.
2. Time to hire
Formula: days from candidate application or first contact to offer accepted, for that candidate.
Different question, different answer. This measures the candidate experience of your speed, not the business cost. A role can have a ninety-day time to fill and a twelve-day time to hire, if the winning candidate applied late. Both numbers are useful; conflating them is the most common mistake in recruiting reporting.
3. Stage duration
Formula: median days a candidate spends in each stage before moving or being rejected.
Use the median, not the mean — a handful of dormant candidates will drag an average until it is meaningless. This is usually the most actionable metric on the list, because it localises the delay. In most funnels the waiting is longer than the working.
Volume and conversion
4. Stage conversion rate
Formula: candidates advancing from a stage divided by candidates entering it.
Compute it per stage rather than end to end. A single overall conversion number hides where the loss happens. The trap: candidates who are still in progress. Either exclude open requisitions or use a cohort that has fully resolved.
5. Applications per hire
Formula: total applications divided by hires, for the same set of roles.
Rising sharply across the industry, and widely misread — a higher number is not automatically worse. It can mean your reach improved. Read it alongside conversion at first review, and see why this metric is broken on its own.
6. Qualified application rate
Formula: applications passing initial screen divided by total applications.
The number that tells you whether your job posting is doing its job. If it falls, the posting is attracting the wrong people, and no amount of screening efficiency fixes that upstream problem. Improving it is a writing exercise: six edits that change it.
Quality
7. Offer acceptance rate
Formula: offers accepted divided by offers extended.
A late-funnel quality signal. Below roughly eighty per cent, something upstream is wrong — expectations were not set, compensation was not calibrated, or the process took long enough for a competing offer to land. Segment by rejection reason or the number tells you nothing about what to fix.
8. Early attrition
Formula: hires leaving within the first year divided by hires in that cohort.
The closest available proxy for hiring quality. It is slow — you wait a year for the signal — which is why it is rarely tracked and always worth tracking. A screening process optimised for speed while early attrition climbs is not working, whatever the other numbers say.
9. Hiring manager satisfaction
Formula: a short structured survey at thirty and ninety days.
Two questions are enough: would you hire this person again, and was the process well run. Separating them matters; a good hire from a painful process and a bad hire from a smooth one need different responses.
Cost and source
10. Cost per hire
Formula: (internal recruiting cost + external recruiting cost) divided by hires in the period.
Almost always understated, because internal cost — recruiter salaries, interviewer time, tooling — gets omitted. The full breakdown with a worked example covers what belongs in each side.
11. Source quality
Formula: hires from a source divided by applications from that source, with cost per hire by source alongside.
Not volume. The channel producing the most applications is frequently the worst channel, and budgeting on volume is how recruiting money gets misallocated. See which channels actually convert.
Three rules for making these usable
- Write the definitions down. Most disagreements about recruiting numbers are definitional, not factual. A one-page definition sheet ends them permanently.
- Segment by role family. A blended number across engineering and warehouse hiring describes neither. Segment before you benchmark.
- Pair a speed metric with a quality metric. Any speed number can be improved by lowering the bar. Reporting time to fill without offer acceptance or early attrition invites exactly that.
If your system cannot produce these without exporting to a spreadsheet, that is a tooling problem worth fixing — see what Hireall reports on.