How to measure quality of hire in 2026

Every talent leader says quality of hire is their top priority. Very few can measure it.

This gap is not surprising. Quality of hire sits at the intersection of recruiting decisions and business outcomes, which means it depends on data that talent teams often do not own. But the pressure to close this gap is intensifying. When headcount is constrained and every hire needs to deliver, "we hired someone" is no longer enough. Leaders want to know whether recruiting is producing people who perform, stay, and grow.

Why measurement remains difficult

Only 25% of TA professionals feel confident in their organisation's ability to measure quality of hire effectively. The reasons are familiar: performance data lives in another system, hiring manager feedback is inconsistent, and definitions of "quality" vary by team. Many organisations default to metrics they can actually track, like time to fill or cost per hire, even though those metrics say nothing about whether the person hired will succeed.

The result is a blind spot. Recruiting teams operate without a feedback loop, which means they cannot learn from outcomes or improve calibration over time. This is especially costly in enterprise environments where 69% of organisations still struggle to fill roles, making every hire count even more.

A practical framework

Measuring quality of hire does not require a perfect system. It requires agreement on what matters and discipline around collecting a few signals consistently.

Start with three inputs. First, hiring manager satisfaction, captured 30 and 90 days after start date. Second, early retention, specifically whether the person is still in role at six and twelve months. Third, time to productivity, measured by how quickly the new hire reaches defined milestones. None of these inputs is perfect on its own. Together, they create a composite that reflects whether hires are landing well. Track them by role family, hiring manager, and source channel to identify patterns.

Skills-based hiring strengthens the signal

One reason quality of hire is hard to predict is that traditional hiring criteria do not correlate well with performance. Degrees and years of experience tell you where someone has been, not what they can do. Research suggests that skills-based hiring is five times more predictive of job performance than credentials alone.

This matters for measurement because it means you can improve quality of hire upstream, not just track it downstream. When you assess candidates on demonstrated skills and structured scorecards rather than proxies, you increase the odds that your hires will perform. And when your selection criteria are explicit, you can trace outcomes back to process and learn what is working.

Close the loop

The biggest unlock is connecting recruiting decisions to outcomes. Define what "quality" means for each role family before you start hiring. If you cannot articulate what a successful hire looks like at six months, you will not be able to measure it later. Then build a feedback cadence: collect hiring manager assessments, review early attrition, and compare outcomes across sources and interviewers.

Over time, this data compounds. You learn which interview signals predict success, which sources produce stronger hires, and where your process creates false positives. That feedback loop transforms recruiting from a reactive function into a system that improves itself.

The bottom line

Quality of hire is the metric that matters most, and measuring it is more achievable than most teams assume. You do not need a perfect data infrastructure. You need a shared definition of success, a small set of consistent signals, and the discipline to review outcomes regularly.

If you want to start, pick one role family, align on success criteria with hiring managers, and commit to collecting feedback at 30, 90, and 180 days.

FAQ

What is quality of hire?
Quality of hire measures how well new employees perform after joining, typically combining hiring manager satisfaction, retention, and time to productivity.

Why is quality of hire hard to measure?
‍It requires connecting recruiting data to post-hire outcomes, which often live in separate systems. Definitions also vary across teams.

What metrics should I use?
‍Start with hiring manager satisfaction at 30 and 90 days, retention at six and twelve months, and time to productivity.

How does skills-based hiring improve quality of hire?
‍Assessing candidates on demonstrated skills rather than credentials produces stronger predictions of job performance.

‍