Introduction
Recruiting analytics is a broad and complex field. Established people analytics functions at large organizations normally have a whole team dedicated to analyzing and improving recruiting performance using the data produced by applicant tracking systems, talent intelligence platforms, and relationship management tools. This post is designed to help recruiting professionals and hiring managers to use basic analytics techniques to improve recruiting performance.
We’ll cover three core metrics that directly impact recruiting performance:
- Time to Hire
- Recruiting Capacity
- Cost per Hire
What is Time to Hire
Recruiters are commonly asked “When will my role be filled?” The answer is not always straightforward and requires a deep dive into historic hiring. Analyzing historic time to hire metrics can help to estimate how long a role will take to fill. No two roles are the same, so it’s important to account for increases or decreases based on:
- Role prioritization – when will the requisition be actively worked on?
- Recruiter requisition load – how many other competing roles is the recruiter managing?
- Current market trends -- how many potential candidates are in the market and how competitive is your offering (e.g. compensation, location, benefits)?
- Interviewer availability -- is there sufficient interviewer availability to quickly schedule an interview?
- Recruiting process – how quickly are current candidates moving through each stage of the recruiting funnel?
Time to hire can also be measured differently depending on the stakeholder. Recruiting teams may want to measure the time between a requisition approval or prioritization to when an offer is accepted to account for all variables under their control. Hiring managers will be more interested in when their new hire will start and will want to know the (much longer) total time between submitting a requisition request and candidate start date. It’s important to be consistent when measuring time to hire to manage expectations.
How to Improve Recruiting Capacity
Once time to hire for different roles is understood, it can be helpful to measure and optimize capacity across a recruiting team to ensure roles are prioritized and filled quickly. This is where a rough 6 month hiring forecast (including attrition backfills) can be matched to existing capacity to determine:
- Are there enough total recruiters available to fill expected demand for the next 6 months?
- Which recruiting teams are under/over staffed (e.g. by looking at expected backlog after 6 months)?
- If there is an experience gap for a type of role (e.g. deep machine learning roles may need a specialist recruiter)?
If total capacity available meets demand, rebalancing requisition load across the team may be an easy way to achieve hiring goals. A shortfall in one area can also be identified and mitigated early, providing enough time to upskill, reprioritize, or add capacity when it’s needed the most.
Cost per Hire
Measuring cost per hire can be contentious as time to hire is usually what most stakeholders care about. Understanding the cost to hire each role can have a huge impact on effectiveness when used to make decisions on recruiting strategy.
It can be hard to attribute cost per hire to each requisition as many of the expenses are spread over a large team and billed on an annual basis. Segmenting baseline cost per hire (recruiter salary plus standard services such as LinkedIn recruiter) and adding role-specific costs, such as advertising spend or event sponsorship, to a subset of roles can be helpful.
Perhaps the best reason to understand estimated cost to fill a new role is the business case for outsourcing the hiring process or incorporating tools designed to improve recruiting performance. Reach out if you want to discuss cost effective ways to accelerate hiring!
