By Anastasiia Kuzmenko, head of talent acquisition at F1V
"What about our recruitment metrics?" That question was like a nightmare when I first heard it.
At that point, I was the first (and only) recruiter at the company I worked for. I didn’t measure anything — I was filling roles, and everything seemed fine. But when my supervisor asked for regular analytics updates, I realized I had to change my approach.
At first, I didn’t like this task. The analytics stuff is quite boring and complex at first, so it’s a normal reaction for someone who’s not an analyst in their job. It’s similar to how most people don’t like olives when they first taste them.
But later, I got it: This actually saves money and time (two critical things for startups!) and is worth the effort.
From spreadsheets to ATS – and back again
Let’s just say my first attempts at spreadsheets were far from perfect, but I had to start somewhere.
My first step was tracking candidates in the pipeline each week. A bit later, I also began analyzing which channels they came from. The next thing was getting into the applicant tracking system (ATS) analytics (back then, I used Breezy, now it’s TalentLyft), and I noticed that its data wasn't 100% accurate.
Since then, I’ve mostly relied on tables and cross-checked numbers from the ATS with my own records. In the ATS, I usually look at applicant sources and other, less critical data.
Using spreadsheets can cover your basic needs and isn’t something to be ashamed of — especially if you don’t have the budget for fancy tools.
Or, if you have, you can test popular analytics and visualization platforms when you get better at the whole thing. There's no need to push yourself into advanced tools like Power BI or Looker Studio right off the bat.
While preparing a presentation for the whole team back then, I calculated metrics for each funnel stage over the past year — and it hooked me.
After that experience, at every company, I make tracking recruiting metrics my team’s routine from day one. How else can you solve bottlenecks that might surface? Or how can you forecast, for example, the time you might need to hire a C-level pro or a candidate with specific experience?
Collecting analytics pays off. It will guide the entire recruiting process, enabling you to forecast hiring, provide stats to hiring managers, and even assess how large your talent acquisition team needs to be.
Track 5 key recruitment metrics
I recommend monitoring the following metrics: 1) time to fill/time to hire; 2) source of hire; 3) cost per hire; 4) offer acceptance rate; and 5) the recruiting funnel's effectiveness.
My team does this every month to keep improving. But you can choose a different period — quarterly, biannually, annually, or whenever you need a report.
Is a role taking too long to fill? Calculate time to fill/time to hire and think about what can be slowing down the process. The market benchmark is two to three months. At F1V, we need about 40 days to fill a vacancy, though sometimes we find the right fit in just a few days.
To assess your recruiting budget and figure out which sourcing channels to focus on, look at the source of hire metric. The F1V team uses LinkedIn as a primary sourcing channel, with job websites being quite effective for us, too.
Calculating cost per hire also aids in budget planning and must be listed in a company’s P&L. It typically ranges from $3,000 to $5,000. According to a recent study, the average benchmark is $4,700.
If you want to evaluate how attractive your job offers are, check your offer acceptance rate. The average benchmark in 2023 was 73%.
Analyzing every stage of the recruiting funnel can give lots of insights. This breakdown shows where candidates fall off and whether we’re moving the right ones forward.
My team analyzes six markers:
- Sourced to hired.
- Pre-screen call to CV sent.
- CV sent to tech interview.
- Tech interview to final interview.
- Tech interview to offer accepted.
- Final interview to offer accepted.
Read more on tracking cost per hire and time to hire in my article on TechCrunch.
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