Time to hire = hire date − application date, averaged over the hires in a window. It is deliberately candidate-centric: the clock starts when a person enters your pipeline, not when the role was opened — that longer interval is time to fill, a different metric that also counts sourcing lag.
Why speed matters in IT services hiring: strong engineers run several processes in parallel, and every silent week is a week a competing offer can land in. Speed is also the cheapest lever to pull — improving it costs process discipline, not budget.
Where the days actually hide:
- Screening pile-ups — CVs waiting on a single reviewer.
- Feedback lag — interviews done, scorecards unwritten, debrief unscheduled.
- Offer assembly — approvals and compensation back-and-forth after the panel already said yes.
The fix starts with measuring per stage rather than end to end: one average hides whether you lose the week at screening or at offer.
In Helia, recruiting analytics compute average time-to-hire from application to the hired stage, show hires over the last 90 days, break down average time spent in each pipeline stage from the stage-change history, and give a per-recruiter view of offers, hires and time-to-hire — so the slow step has a name.