The recruiting analytics every enterprise team should be tracking
It’s true of all organizations that poor recruiting and hiring processes = money wasted and business opportunities missed; but the impact is even greater for enterprise companies, for whom more is at stake when non-optimized processes meet massive hiring volumes.
Research has shown that every dollar invested in data and analytics yields returns worth over $9.00—a nearly-1,000% ROI. And if enterprise companies aren’t turning to analytics to continually iterate on their talent acquisition strategies and processes, they risk looking archaic beside the startups in their industries, who are using data to derive recruiting best practices from the very beginning. Talent analytics help you maintain that competitive advantage you hold in terms of longevity and brand awareness. Here’s what to track:
Recruiter Activity and Outreach Effectiveness
Are your sourcers and recruiters investing their efforts in the right places?
What do open/reply/interested rates look like when broken down by individual recruiter, talent pool, outreach type, recipient’s gender or race/ethnicity?
What content compels prospects to click, and which clicks lead to replies?
Source of Hire (Sourcing Channel Effectiveness)
How many qualified candidates are entering your funnel from any given source: LinkedIn, career page applications, social networks, job boards, referrals, internal candidates, agencies?
Where did your most successful candidates first hear about your job opening: your website, company Facebook page, job search sites, your referrals program?
“Sourcers are in Gem’s analytics all the time; they become intimate with what works in your hiring process and what doesn’t. The more time they spend in it, the more they understand their team’s unique recruiting landscape. That knowledge gets passed from sourcers to recruiters to hiring managers and talent leaders. That’s strategy being driven by someone whose core function is outreach. Now the whole ecosystem is way more strategic. Thanks to Gem’s analytics, sourcers are strategic hiring partners at Gusto, rather than just outreach executors. I’ve transitioned in my career in exactly that way.”
Time to Fill
How many days pass between the approval of a job requisition and the day the offer is accepted by a candidate? How well are you managing the process from start to finish?
Segment your process and measure how much time it takes to move candidates between stages. Where are recruiters spending too much time and energy? Are parts of your process redundant? Are there places you can automate?
Slice time-to-fill metrics by filters like source and location. If hiring takes longer for your Amsterdam office than it takes for your New York office, what can you learn from your Amsterdam process to apply to your New York process?
Recruitment Funnel Effectiveness
Where are candidates dropping out of process? Where are there bottlenecks in your funnel?
Remember that conversion rates that are too high can be as much of a red flag as those that are too low: if you’re not filtering out enough unqualified talent, you’ll be straining recruiting resources at one stage or another.
What’s the average number of days candidates sit in a given stage? How efficiently are recruiting coordinators working to schedule next steps? How long are hiring managers taking to make decisions? (Without tools that track time-in-stage, coordinator and HM efficiency are notoriously difficult to track.)
Offer Accept Rate/s
What’s the ratio of offers that are accepted to the total number of offers extended?
What are the trends in decline reasons?
Where is there a disconnect in communication about the role, or the org, or the culture, or what your offer will entail? What surprises or realizations are candidates having in-process that can be preempted by acknowledging them earlier? Are there patterns in offer-accepts across departments or locations?
Pipeline Diversity and Diverse Hiring Rate
What does diversity look like in the pipelines your team is currently building?
What do conversion rates for underrepresented talent look like throughout the funnel, from first outreach through hire?
Are certain groups disproportionately dropping out of the funnel at certain stages? Are systemic biases showing up—by role, recruiter, or hiring manager—as some candidate segments get stuck at certain stages of the funnel?
“I needed Gem’s Pipeline Analytics because I needed to know why we weren’t hiring more women engineers. Was it a problem in our interview process? Because if so, we would fix that parity issue as a first step. With Gem, I’ve proven and been able to communicate that our interview process isn’t very biased. That was invaluable because it allowed us to dispense with one speculation and move on to others.”
Senior Director of Global Talent Acquisition and Ops
Historical Data and Forecasting
Based on historical passthrough rates, how many candidates will you need in every stage of the funnel to make a single hire for a given role?
How long is the hiring process likely to take?
Where will hiring managers need to allocate resources based on this data; and where do you need to make a business case for resources—increasing headcount, having recruiters flex between businesses, or onboarding new recruiting technologies—so you can hit your hiring goals?
“With Gem’s Pipeline Analytics, you can observe variance. If the numbers are higher in some places and for some roles, what did we do right there? If they’re lower, what aren’t we doing? Metrics equal opportunities to pivot and optimize. They also ultimately make the team more conscious in their approach. Data ingrains a kind of mindfulness.”
VP of Global Recruiting
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