What Is Quality of Hire?
Quality of hire measures how much value a new employee adds to your organization, based on their performance, retention, and manager feedback in the months after they start. It’s not a single number pulled from one report. It’s built from several signals that only become clear once someone has been on the job for a while.
It’s also a different kind of metric than what most hiring dashboards track. Time-to-fill tells you how fast you filled a role. Quality of hire tells you whether the person you filled it with was the right call.
There are two stages worth measuring, and most companies only look at one:
- Pre-hire signals: assessment scores, interview results, and source of hire.
- Post-hire signals: performance, retention, and manager satisfaction.
Tracking both matters because it shows you not just that a hire didn’t work out, but where in the process things went wrong.
Key Takeaways
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Which Metrics Go Into a Quality of Hire Score
There’s no single number that defines quality of hire. It’s built from a handful of indicators that, together, show whether a hire is actually working out. The right mix depends on the role and what your team can realistically collect data for. Most frameworks draw from some combination of these:
- Job performance: measured against the specific goals set for the role, not a generic rating. A sales hire and a support hire need different benchmarks even if both get scored at 6 and 12 months.
- Retention: tracked at 90 days, 6 months, and one year. This one doubles as an early warning system. If a group of hires from the same source keeps leaving early, the problem usually traces back to how they were sourced or screened, not how they performed.
- Hiring manager satisfaction: a short survey asking whether the hire met expectations and whether the manager would make the same decision again. It’s the most subjective metric on this list, which is fine as long as you’re not treating it as equivalent to hard performance data.
- Time to productivity: how long it takes the new hire to be fully contributing in their role.
- Team and culture fit: feedback from peers or a 360 review on how the hire is working with the people around them.
- 30/60/90-day check-ins: structured evaluations at set intervals that catch problems while there’s still time to address them, rather than waiting for an annual review.
How to Calculate Quality of Hire
Score each indicator as a percentage, then average them together to get a single quality of hire score.
- Pick 3 to 5 indicators you can consistently track. A handful of reliable numbers beats a long list of shaky ones.
- Convert each into a percentage. If 80% of new hires hit their 90-day goals, that metric scores 80.
- Average the scores. For example: (82 + 88 + 79) / 3 = a quality of hire score of 83.
- Look at groups, not individuals. Score everyone hired from a given source, role, or quarter. That’s where patterns show up.
Example: Say a new hire is still with the company at their 6-month mark, so retention scores 90. Their manager rates satisfaction at 85 out of 100. And their performance review shows they’re hitting 80% of their goals. Add those three numbers together and divide by three: (90 + 85 + 80) / 3 = a quality of hire score of 85. Run that same math across every hire from a given source or role, and you start to see which ones are actually paying off.
What to Do With the Results
A quality of hire score is only useful if it changes what you do next, whether that’s shifting recruiting budget, adjusting how a role is defined, or rethinking which pre-hire signals you trust.
The most direct use is figuring out which hiring channels actually produce good hires. If referrals consistently outscore agency placements, that’s a straightforward budget conversation, not a guess.
The bigger payoff comes from connecting pre-hire signals to post-hire results. If certain assessment scores or interview criteria reliably predict who scores well six months in, those signals deserve more weight in your process going forward. That’s the real value of behavioral data: it closes the loop between what you knew about a candidate before day one and how they actually performed after.
And when quality of hire is consistently low for a specific role or team, the problem usually isn’t the candidates. It’s something upstream, how the role was defined, how interviews were run, or how the new hire was set up to succeed once they started.
Why Quality of Hire Is Hard to Measure
Quality of hire takes more effort to measure than most recruiting metrics, since it draws from multiple systems, blends objective and subjective data, and needs months to fully play out. None of that makes it not worth doing. It just means the payoff comes with a little more patience than a metric like time-to-fill.
There’s no industry standard, which sounds like a downside but mostly just means the goal is internal consistency. You’re not chasing a universal benchmark. You’re building a method you can trust and repeat, so this quarter’s hires can be compared fairly to last quarter’s.
The data tends to live in different places: performance reviews here, retention records there, manager feedback somewhere else. That’s a solvable problem. Once collection is standardized or automated, pulling it together gets a lot easier.
Some of what goes into the score is subjective by design. Manager satisfaction and culture fit are opinions, and that’s fine as long as you’re clear about which inputs are judgment calls and which are hard numbers.
The one true tradeoff is time. A score built on 12-month retention data needs 12 months to fully form. The upside is that teams who start tracking early get a clearer, more reliable picture with every hiring cycle that follows.
Final Thoughts
The math behind quality of hire is simple. Knowing whether your indicators are actually worth tracking takes longer, sometimes a full year, before you find out if you picked the right three.
That’s the real problem with measuring it only after someone starts. By the time retention and performance data roll in, you’ve already made the hire. PI’s behavioral data gets you some of that signal earlier, using assessment scores and job-target fit to flag which candidates are more likely to stick around and perform once they’re in the role. You’re not eliminating the wait entirely, but you’re making a more informed bet going in, instead of finding out 12 months later that the process needs fixing.
