Quick answer: Quality of hire measures how well new hires work out compared with what you expected. For a small team, track three signals per hire: a manager rating at 90 days, how fast they got up to speed, and whether they’re still there at 12 months. Average them on the same scale and compare across roles and sources. It’s imperfect, but it’s the only recruiting metric that tells you whether your hiring decisions were right.
Why does quality of hire matter?
Because the other recruiting metrics can all look great while you hire the wrong people.
A fast, cheap hire who leaves in four months is a bad outcome. Time to hire and cost per hire would both report it as a success.
Talent leaders have been saying this for years. LinkedIn’s Global Recruiting Trends surveys in 2015 and 2016 found talent leaders named quality of hire as the single most valuable recruiting metric. LinkedIn’s own 2015 write-up of that survey also described it as the metric recruiters find hardest to get right. Not much has changed since.
What should you measure?
Pick a small set of signals and use them the same way for every hire.
| Signal | When | How | Scale |
|---|---|---|---|
| Manager performance rating | 90 days and 12 months | Manager answers: “How is this person performing against what we expected?“ | 1 to 5 |
| Ramp-up | 90 days | Manager answers: “Did they get productive faster or slower than expected?“ | 1 to 5 |
| Retention | 12 months | Still employed? | Yes or no |
| Hiring manager satisfaction | 90 days | ”Would you hire this person again?” | Yes or no |
Optional, if they fit your business:
- Role-specific output, like quota attainment for sales or ticket resolution for support
- Whether the hire was promoted or given more scope in year one
Don’t add more than five. Small teams abandon complicated scorecards.
How do you calculate a quality of hire score?
Convert each signal to a 0 to 100 scale and average them.
Quality of hire = (Performance score + Ramp-up score + Retention score) / 3Example for one hire:
- Performance 4 out of 5 = 80
- Ramp-up 3 out of 5 = 60
- Still employed at 12 months = 100
Quality of hire = (80 + 60 + 100) / 3 = 80
Then average across hires. That’s where it becomes useful: by role, by hiring manager, by source, by interview process.
What can quality of hire tell you?
It tells you which parts of your hiring process predict success.
Questions it can answer:
- Which sources produce the best hires? If referrals average 82 and a paid job board averages 55, that changes your budget. See employee referral programs for small teams.
- Do interview scores predict performance? If people who scored 5 in interviews perform no better than people who scored 3, your interview isn’t measuring the right things.
- Are some hiring managers better at picking? Sensitive, but useful.
- Did changing the process help? If you introduced a work sample test last year, did quality go up?
What makes quality of hire unreliable?
Be honest about the limits so you don’t over-read the numbers.
- Small numbers. With six hires a year, one bad hire swings the average hugely. Look at the individual cases, not just the average.
- Manager bias. The manager who hired someone may rate them generously. Ask a second person when you can.
- Onboarding effects. A good hire with bad onboarding can look like a bad hire. Quality of hire measures your whole system, not just selection.
- Survivorship. People who left early often don’t get a 12 month rating. Make sure they’re counted, or the average looks better than reality.
- Timing. You only know quality a year after the decision. Use it to improve the next year’s process, not this month’s.
How do you link quality of hire to your hiring data?
You need the hiring data and the post-hire data in one place, at least once a year.
Hiring data: source, interview scores, which interviewers, time to hire. Post-hire data: the ratings and retention above.
Most applicant tracking systems (ATS), including Canvider, stop at the hire. Canvider tracks status history, sources of hire, offer acceptance rate and time to hire, and lets you export analytics to Excel. It doesn’t collect 90 day performance ratings. The practical setup for a small team is a short sheet with one row per hire: export the hiring side from the ATS, and add the 90 day and 12 month signals from managers.
That’s not elegant. It’s 30 minutes a quarter, and it’s enough to see patterns.
What should you do with the results?
Change one thing at a time in your hiring process.
- If a source keeps producing low-quality hires, spend less there.
- If interview scores don’t predict performance, rewrite your questions. Our behavioral interview questions and interview scorecard template are a starting point.
- If ramp-up is consistently slow, the problem might be onboarding. See new hire onboarding after the ATS.
- If one role keeps failing at the same point, revisit what the role really needs. A skills-based approach often helps.
Pair it with speed and cost
Quality of hire alone doesn’t tell you whether you hired efficiently. Look at it next to time to hire and cost per hire. The goal is fast, affordable hiring that works out a year later. For the wider set of numbers worth watching, see recruiting metrics beyond time to hire.
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Frequently asked questions
What is quality of hire?
Quality of hire measures how much value a new employee brings compared with what you expected when you hired them. In practice it's usually a mix of the manager's performance rating, how quickly the person got up to speed, and whether they're still there after a year.
How do you calculate quality of hire?
A common approach is to average a few scores on the same scale, for example manager rating at 90 days, ramp-up rating, and 12 month retention (yes = 100, no = 0). Then compare the average across hires, roles and sources. The exact formula matters less than using the same one every time.
Why is quality of hire hard to measure?
Because it happens months after the hiring decision, it depends partly on the manager and onboarding rather than the hire, and small teams have too few hires for averages to mean much. That's why it works best as a simple, consistent check rather than a precise score.