Instead, you could spend that time on more value-creating tasks. Let’s look at five arguments for why you should ditch screening CVs manually and seek digital solutions to support you instead.
Screening resumes manually used to dictate how HR companies did things because they didn’t have another option. It was part of why a recruitment companies were good; they spent a lot of time on every candidate and deciphered which ones should pass the first step in the hiring process. Nowadays, however, the tables have turned. Efficiency screams the loudest in todays’ HR departments and recruitment companies. It’s concluded that with the help of machine learning, a computer can do an initial screening of resumes faster and with better quality than a human could. A result is based mainly on our incapacity to store a lot of information for a longer time. A human can only hold so many candidates in their brains at once. In contrast, a computer can “remember” every candidate from a job application 10 years back.
We no longer praise those who completed a quality hire; we praise those who did it efficiently because efficiency is now equal to quality in the overall key metrics for recruitment departments.
Recruiters of today skim resumes for an average of 7.4 seconds. If you’ve received 200 applications, that amounts to 25 minutes. Doesn’t sound like much. But here’s the twist, the skimming itself can’t possibly give you a proper idea of why you decided to go for one candidate contra another. A whole lot of extra work comes with this approach. Not only do you have to jot down every person you’ve deemed suitable for the job, but you also have to double-check and remind yourself why you decided on that person, since it would be close to impossible to remember all of the good reasons when you have to keep 200 resumes in mind.
The candidate on her end has most likely spent a lot of time trying to create the optimal resume. She might have spent over 3 hours writing it whereas you only spend 7.4 seconds on it. Therefore, and when you call her up or request a face-to-face interview, you probably won’t remember many details of her past, which not only makes you look so and so, but it might make her second-guess applying for the job since it’s pretty evident that her effort wasn’t valued. The application itself states that a personal letter is required in many cases. So the candidate writes a personal letter, customized after your criteria. Still, you barely look at it, although it holds most of the information you need to make an informed decision. Again, that proves that her first effort for this company was close to worthless.
It’s proven that 65% of resumes received for a high-volume role are ignored. What does that say about quality hires? The fact that you don’t have the time to go through every application means that you definitely miss out on candidates that would’ve been an even better fit. On top of that, the human factor plays a huge part in how resumes are skimmed. You’re missing information, but, you’re also, unbeknownst to you, looking for information to your liking, from a personal point of view rather than a professional. That’s called affinity bias, and it is guaranteed to play a part in your every hiring decision. No person is excused from the subconscious workings of our minds.
The recruitment industry is going through changes to your benefit. We see a new digitalization solution for each step in the hiring process every day. One of them being automated CV-screening. The computer scans and screens resumes based on the input (criteria) you’ve given it. It has screened every resume in a matter of minutes and given you a neat shortlist of the best-fitted candidates. You can also be supported in your day-to-day work with text-based AI-driven interviews that act as an initial screening. Such interviews take place in a chat-window and are conducted by the AI. Hubert is one for example. It’s also possible to perform cognitive tests online which is a massive time-saver since you don’t have to meet with every candidate to perform the tests. To wrap it up; regarding bias, no, an AI is not free from bias, but it’s less riddled with them than we are.