Reports are a great way to understand the baseline of speed and efficiency when it comes to talent acquisition at your company. They can also measure progress to targets and adherence to business service level agreements (SLAs). However, if you are just starting your journey to becoming a data-driven recruiting organization, it can feel overwhelming to pick exactly which metrics to capture and focus on. A common pitfall I have observed as an analytics consultant is when clients try to report on too many things at once, and do not truly understand what their data is telling them and what the team’s next steps should be.
Though the reporting maturity and requirements differ from client to client, there are some core metrics that almost every team I’ve worked with is interested in reporting on. Here are 5 of those key metrics and how you might be able to incorporate them into your company’s reporting framework:
1. Time to Fill
What is “time to fill”?
“Time to fill” is an internal metric that reflects the time from when the budget for additional headcount has been approved, to when every budgeted headcount has been hired. It encompasses activities such as creating the job posting, distributing it to the relevant job boards and agencies, generating the candidate pipeline through job boards and sourcing efforts, conducting screens and onsite interviews, and finally, creating the offer and subsequent compensation negotiations and background checks.
Why does it matter?
This metric will reveal how fast the end-to-end recruiting process is, and you can share this information with hiring managers to provide an estimate of when a new opening on their team is likely to be filled.
How is “time to fill” calculated?
Though all companies may define this differently, a common calculation is days from when a requisition was approved to when all headcount on the requisition has been hired.
2. Time to Hire
What is “time to hire”?
“Time to hire” is an external metric that reflects the candidate’s experience while interviewing at your company. It is typically measured as the time from when a candidate enters the pipeline to when they sign their offer and are officially hired into the company. This metric encompasses the time it takes to review a candidate’s resume, schedule and conduct interviews, provide feedback, manage offer negotiations, and complete background checks if applicable.
Why does it matter?
A long time to hire creates a negative candidate experience, and can potentially cause your company to lose out on highly qualified candidates that may be simultaneously interviewing at other companies. Once you have a baseline of what your typical time to hire is, you can set realistic targets for your team to reduce this time, and monitor progress to the goal through weekly or monthly reports
How is “time to hire” calculated?
“Time to hire” is calculated best when a candidate enters the pipeline to when they are hired into the system (so they have accepted the offer, and passed the background check). Some clients I have worked with define the end date as to when the offer is sent, or when the offer is accepted (so the recruitment team’s job is complete when an offer is sent, regardless of the hiring outcome).
3. Days in Stage
What is “days in stage”?
“Days in stage” measures how long candidates are typically staying in each stage of your interview process. This is commonly reported in averages, but can also be done as a median or percentile if your company has lower candidate volume. Reporting as a median or percentile ensures your data is less sensitive to outliers (i.e. one candidate stayed in a stage significantly longer than the other candidates, and now the average days for all candidates appear to be higher).
Why does it matter?
“Days in stage” can help you identify if there are bottlenecks in your recruiting process, and where these bottlenecks are. This metric will help you understand if candidates tend to spend more time in stages owned by Talent Acquisition (i.e. resume review, recruiter screen) or if the lags are actually in stages owned by hiring managers or individuals outside of Talent Acquisition (i.e. technical assessment, on-site interview, background check). This data point will empower Talent Acquisition managers to have conversations with their team and hiring managers to tackle specific stages in the process that result in candidate stagnation.
How is “days in stage” calculated?
You can calculate the average “days in stage” as the time from when candidates entered a stage to when they exited the stage, for all candidates that were in a stage during a given period. If a candidate is still in the stage, you have the option to include their time into the calculation (using today’s date instead of when they exited the stage). This will act as a “rolling counter” that includes the time from stale candidates and can help encourage recruiters to keep a clean pipeline.
4. Offers Sent & Acceptance Rate
What is “offers sent and acceptance rate”?
This may technically count as two metrics, but I included them in the same metric because I rarely report one without the other. Offers sent is the count of offers sent in a period of time, and the acceptance rate is what percentage of those offers were signed, and the candidate actually ended up starting (i.e. did not renege on the offer or fail their background check).
Why does it matter?
The primary function of most Talent Acquisition teams is to find and hire qualified candidates. The volume of offers sent in a period is a direct measurement of how successful the team was in finding qualified candidates and guiding them through the recruitment process. Acceptance rate represents how attractive an offer and the company, in general, is to a candidate, and changes in acceptance rate over time (i.e. increasing or decreasing) may provide signals into how competitive a company’s offer is, compared to the market.
How are “offers sent and acceptance” rates calculated?
“Offers sent” is the count of offers by when they were sent. “Acceptance rate” is the count of offers sent in a period where the candidate was hired, divided by the total offers sent in the period.
5. Conversion from Recruiter Screen to X Stage
What is “conversion from recruiter screen”?
This is the most complex metric of the four I’ve shared so far, and something I typically see from companies with larger pipeline volumes spanning a longer period of time (i.e. 50+ hires over at least 6 months). This measures the average count of recruiter screens that are needed for one candidate to convert to a later stage interview (i.e. 10 candidates in recruiter screen for 1 to reach hiring manager screen). It gives you a sense of how many screens your team should be targeting to complete in a given time frame, in order to find at least one candidate that will reach a later stage (i.e. offer or hire). However, this metric is more accurate for larger companies with historical data, as all the conversion rates are based on historical performance. The metric can be misleading if you have low hire volumes, or have only recently started tracking this information.
Why does it matter?
This metric will help you with capacity planning and measuring the quality of candidates your recruiters are screening. If it typically takes 100 screens for one hire and a certain department has opened 15 new headcounts to be filled in this quarter, this is an excellent data point to help you push for additional budget to hire more recruiters or invest in an agency, as the existing team cannot support a headcount search that will require roughly 1,500 screens in less than a quarter (on top of existing searches).
This metric will also help you identify if a particular recruiter meets with more or fewer candidates than the team average to find individuals that reach later stage interviews. It may be an indicator that some recruiters have a better sense of what to look for when reviewing resumes, and can train other members on the team regarding what to look for in a resume or LinkedIn profile to filter out unqualified candidates more effectively at the resume review stage.
How is “conversion from recruiter screen” calculated?
You can calculate this by finding the total count of candidates that were in the recruiter screen in a given period, and dividing it by the count of these same candidates that reached a stage of interest. For example (candidates in recruiter screen in June 2021) / (candidates in recruiter screen in June 2021, that later reached on-site interview). You can report this as a ratio such as 80:1 for recruiter screen:offer, for example.
These are just a few metrics to get you started. If you start with reporting on these 5 metrics alone – it’s a solid foundation that will give you insight into nearly every aspect of your Talent Acquisition organization.
I am a Talent Analytics Consultant at Lever, which means I help clients use their recruitment data to understand team performance, bottlenecks in the hiring process, and uncover opportunities to become more efficient. I’ve worked with clients across almost every industry from technology to healthcare to retail, and companies ranging from startups with less than twenty employees to international holding companies.