What recruiting metrics matter most?

The ones tied to outcomes and bottlenecks: time-to-hire (median and average), funnel drop-off by stage, cost-per-hire, and source attribution. These tell you where hiring is slow, where candidates are lost, and which channels are worth the money — unlike activity counts that just measure busyness.

What's the difference between time-to-hire and cost-per-hire?

Time-to-hire measures speed — how long from application (or sourcing) to accepted offer. Cost-per-hire measures spend — the total cost to make a hire, divided across hires. You want both: a fast process that's wildly expensive, or a cheap one that takes months, are each broken in different ways.

Why track median time-to-hire and not just the average?

Averages get distorted by a few outlier roles that take forever. The median shows the typical experience, while the average reveals whether a long tail is dragging you down. Looking at both tells you if you have a systemic speed problem or a few stuck reqs.

How do you measure source attribution?

By tracking which source each candidate came from through to hire, so you can see which channels actually produce hires — not just applicants. On 100Networks this is part of the analytics dashboard, alongside funnel drop-off and cost-per-hire, with scheduled email reports.

The Recruiting Metrics That Actually Matter (and How to Track Them)

Most recruiting dashboards measure motion, not results. Number of calls made, emails sent, candidates contacted — all busywork metrics that go up whether or not you hire anyone good. The metrics that actually run a hiring function answer three questions: Where is it slow? Where are we losing people? What's worth the money? Here are the ones worth watching and how to track them without living in a spreadsheet.

The metrics that matter

1. Time-to-hire (median and average)

How long from application to accepted offer. Track the median to see the typical candidate's experience, and the average to catch a long tail of stuck roles dragging everything down. If the two diverge sharply, you have a few reqs quietly rotting — find them.

Speed is also conversion: the longer this number, the more finalists you lose to faster competitors. That's the whole argument for compressing time-to-hire with automation.

2. Funnel drop-off by stage

Where candidates fall out. A big drop between "applied" and "screened" might mean a screening backlog; a drop at "interview scheduled → interviewed" often means scheduling friction. Drop-off tells you which stage to fix, instead of guessing.

3. Cost-per-hire

Total hiring spend divided across hires. It's the number that exposes an expensive habit — like leaning on agencies — and the one to compare when you weigh AI recruiting against a staffing agency.

4. Source attribution

Which channels produce hires, not just applicants. A source can flood you with applications and produce zero hires; another can send five candidates and land two. Attribution moves budget toward what actually works.

Activity metrics vs. outcome metrics

Activity metric (weak)	Outcome metric (strong)
Emails/calls made	Funnel drop-off by stage
Candidates contacted	Time-to-hire (median + average)
Interviews scheduled	Cost-per-hire
Applications received	Source attribution to hire

Activity metrics feel productive and tell you almost nothing about whether hiring is working. Outcome metrics point at the specific thing to fix.

Stop assembling this by hand

The reason teams track vanity metrics is that real ones are painful to compute manually — pulling stages, timestamps, and sources into a spreadsheet every week. On 100Networks the analytics are built in: a funnel dashboard with drop-off, time-to-hire (median and average), cost-per-hire, source attribution, and recruiter activity — plus scheduled email reports (daily, weekly, or monthly) so the numbers arrive without anyone building them.

When the measurement is automatic, you actually look at it — and pair it with consistent evaluation like structured interviews so the quality behind the numbers holds up.

The bottom line

You can't fix what you only measure as activity. Track time-to-hire, drop-off, cost-per-hire, and source attribution — the metrics that name the bottleneck — and automate the reporting so looking at them isn't a chore. That's how a hiring function improves on purpose instead of by luck. See the analytics in the product overview.