The average cost-per-hire was $4425, and divided by an average hourly of $21 for recruiters in the US that works out to 210 man-hours per position filled. Now, obviously recruiters don’t spend all that time screening. In the SHRM Talent Acquisition Benchmarking Report from 2017, the average time-to-fill out of the 864 samples analyzed was 36 days. And what could be more complicated to evaluate quickly and thoroughly than human beings? If you want to be quick, it’s difficult to be thorough. If you want to be thorough, it takes time. Time pressure and quality don’t often find themselves hand-in-hand, though. Simply put: If you’re a recruiter, reducing your time-to-fill and getting the hire right is crucial. It’s a KPI that impacts best practices, improvement initiatives, and often individual assessments within the company. Time-to-fill is an incredibly important aspect of any recruiter’s day-to-day. So what does this mean in practice? Which recruiter problems does automated candidate screening actually solve?
The shortlist is intended as a helping tool - not a final decision on who gets included and excluded from the next stages of the hiring process. It’s up to the recruiter how much time they’d like to spend looking at how the screening was conducted. The result of this is a ranked list of those candidates that best match the job requirements - a shortlist, if you will. Step 4: Candidate shortlist forwarded to the recruiterįinally, when the screening system has parsed, checked, checked again and analyzed, it’s ready to rank. For the recruiter, this is probably the most interesting step of automated resume screening, because it takes a lot of routine, monotonous tasks off your plate. It can either be achieved in a chatbot interview, a video interview or a traditional face-to-face interview. This stage can take many different forms. At the next stage, the system spits out suggestions on what data needs to be clarified. Then it looks at each candidate and to which extent their qualifications match the job profile/description. Initially, it’s figuring out what the company needs. Step 3: Preparing a framework for interviewing/testingĭuring the first two steps of the screening process, the AI is collecting, analyzing and sorting data. More on how this makes for a fairer hiring process a little further down in the post. For the recruiter, this step replaces the work task of meticulously going through each resume and evaluating it against the job ad and its requirements. By combing through the text in each resume/CV you’ve received for your job listing, it effectively ranks and categorizes each candidate.īecause AI-powered systems are both powerful and automated, the initial sorting process is completed at lightning speed.
Once you’ve told it what to look for, it’ll do exactly that. And the AI is put to work doing what they do best: Look for patterns. Once the screening system has sorted the foundational data, it’s ready to examine the candidate pool. Step 2: Candidate pool resumes are uploaded For you, the recruiter, this stage means formulating a curated list of qualifications that corresponds with the business’ needs. When, on the other hand, the system is provided with clear-cut information, the chance of a strong shortlist improves considerably. The extra work will show in the final results.Įffectively, this means that if your requirements are poorly formulated or unclear, the screening will suffer. Hopefully, the AI-system is pre-trained on past placements and knows what has been working out in the past for similar positions.īut every job and every workplace is unique, which is why it makes sense to be very detailed when setting up the parameters for the system. High-performing AI technology is built to achieve one thing, which for this application is to find the perfect candidate matching the job description. Step 1: Establish requirements and characteristics First though, let’s do a quick rundown of how automated resume screening works in practice, and particularly what the process looks like for you as the recruiter.
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