Time to hire is one of the most quoted recruitment metrics and one of the least consistently measured. For technology roles it matters more than most, because strong engineers, data specialists and security professionals often have several options. If your process is slow, the best candidate may accept another offer before you decide.
This article explains how to measure it properly, where technology hiring usually stalls, and how to speed things up without lowering the bar.
What time to hire actually measures
Different teams use the same phrase for different things, which makes comparison meaningless. Agree a definition and stick to it.
- Time to hire: from the moment a candidate enters your process, or is first approached, to the moment they accept an offer. It reflects how efficiently you move candidates through.
- Time to fill: from the moment the vacancy is approved to offer acceptance. It includes briefing, sourcing and any delay before the search begins.
- Time to start: from approval to the new hire’s first day, including notice periods.
All three are useful. The key is to know which one you are reporting, and to record the dates that let you calculate each.
How to measure it stage by stage
An overall figure tells you that a role was slow, not why. Break the journey into stages and record when each candidate enters and leaves them. A typical technology hiring journey looks like this:
- Role created and brief confirmed
- Candidates sourced
- CV screening
- Fit interview
- Technical interview or assessment
- Employer review
- Final interview
- Offer
- Hired
With dates at each stage, you can see how long candidates wait between steps, which is often where most of the elapsed time goes. Masarat.ai tracks every role through these stages in one employer portal, so status and ownership are visible at any time.
Where technology hiring usually stalls
Unclear briefs
If the requirements change after sourcing begins, the search effectively restarts. A precise brief and a well-written technology job description prevent this.
Screening overload
Large volumes of CVs take time to review, especially when hiring managers do it alongside their day jobs. Much of that time goes on CVs that were never a match.
Interview scheduling
Finding slots for several interviewers can add days at every stage. Technical interviewers are often the scarcest.
Slow or scattered feedback
When feedback sits in email threads and messaging apps, nobody can see which decisions are outstanding. Candidates wait, and some withdraw.
Late surprises
Discovering at offer stage that a candidate’s salary expectations, notice period or work authorisation do not fit sends the process back to the start.
How to reduce time to hire without lowering the bar
Speed that comes from cutting corners usually leads to a bad hire, which costs far more time later. The aim is to remove waiting and rework, not assessment.
- Start from profiled talent. A structured, pre-profiled talent inventory or a standing technology talent pipeline means sourcing does not begin from zero.
- Use AI for volume, people for judgement. At Masarat.ai, AI-assisted screening parses and scores CVs against the job description and prioritises candidates, and a recruiter validates every shortlist. Hiring managers review fewer, better-matched profiles.
- Score consistently. A scorecard rating experience, skills, achievements, progression, domain and application from 1 to 5 lets interviewers compare candidates quickly and fairly.
- Book interview slots in advance. Agree the panel and hold time in diaries before the shortlist arrives.
- Set feedback deadlines. Agree how quickly each interviewer will respond, and make outstanding feedback visible.
- Verify early. Confirm current employment, work authorisation, qualifications, and salary expectations and availability before a profile is shared.
- Replace CV piles with structured reports. A candidate report that sets out role fit, strengths and gaps, and interview findings helps managers decide without re-reading everything.
Our approach page shows how these steps fit into one end-to-end journey.
Common measurement mistakes
- Averaging everything. One very long senior search can distort the figure for a whole quarter.
- Ignoring withdrawn candidates. Record when and why candidates drop out. A pattern of withdrawals after a particular stage points straight at the problem.
- Starting the clock inconsistently. If some recruiters count from first contact and others from application, the numbers cannot be compared.
- Measuring only the recruiter’s part. Much of the elapsed time sits with interviewers and decision-makers, so their stages belong in the data too.
Clean, consistent data is what turns the metric from a number in a report into a list of fixes.
Report the metric in a way that drives action
Report by role family and seniority rather than as a single average, since a senior security architect and a junior developer will never follow the same timeline. Pair the metric with a quality measure, such as hiring manager satisfaction or retention after the probation period, so nobody is rewarded for speed alone. Review the stage data regularly with hiring managers and agree one or two changes at a time.
Frequently asked questions
What is a good time to hire for technology roles?
There is no single benchmark worth relying on. It varies by specialism, seniority, location and your own interview process. Measure your own baseline by role family, then aim to improve it.
Can AI reduce time to hire on its own?
AI can remove much of the repetitive screening and summarising work, but the overall timeline also depends on interview schedules and decisions, which stay with people. The biggest gains usually come from combining both.
How quickly can Masarat.ai shortlist candidates?
Faster than a search that starts from zero, because every search begins with pre-profiled talent and AI-assisted screening. Overall timelines still depend on the role and your interview schedule. See our FAQ for more detail.
Want to see where your process loses time? Send us one technology role and track it with us from brief to offer.