We often describe recruiting as an art—the art of recruiting involves researching and interviewing top talent that we know in our gut is a perfect fit for the position and the company. Yet with the advent of big data and analytics in our recruiting practices, it’s easy to see why some are now thinking of recruiting as a science. After all, these tools allow us to use metrics and data to measure recruiting success and evaluate the best sources for talent. Our recruitment and retention strategies now need to include metrics to support their efficacy.
But does that mean the days of relying on human judgment to make good recruiting choices are over? Not really. In fact, truly successful recruiting is a mix of both art and science. It takes both experience in reading candidates during interviews and analytics to determine how to find the best candidates. Finding a happy medium between art and science lets you use the best tools and know-how available to establish a good recruiting strategy.
Here are some examples of how recruiting is both an art and a science.
Recruiting as an Art
Gut instinct. No amount of metrics, analytics or big data can ever replace that gut feeling a recruiter gets when she knows she’s found the right candidate for the job. The Merriam-Webster Dictionary defines art as “a skill acquired by experience, study, or observation.” It is in that definition that recruitment is an art—through experience and observation, recruiters are able to detect whether a candidate is a good fit or not. That instinct is really based on years of experience and it’s not something that can be replicated systematically. Of course there are instances when one’s gut instinct fails, but its basis on experience means that it’s a helpful tool when it comes to choosing candidates.
Innovation and creativity. Candidates are people, not robots. They respond to certain situations differently and sometimes unpredictably. There’s no scientific formula to determine who might inspire his team with new creative ways of thinking or become an innovative leader. Determining which candidate will possess certain qualities desired for the role is difficult to do through numbers and metrics. Sometimes it boils down to a je ne sais quoi in each individual that big data simply can’t pick up on.
Human judgment. Before, recruiters would have to go through hundreds of resumes when looking for top candidates. Now we have analytic systems that can filter through thousands of resumes, scanning for keywords to pick the candidates who seem to have the most relevant experience. But can those systems read between the lines? The old adage “past performance is not always an indication of future success” could not be more true in describing how effective recruiting should work, and the systems scanning resumes can’t pick up on what’s not there the way a recruiter can during a face-to-face interview with a candidate.
Recruiting as a Science
Analytics. Science, as defined by the Merriam-Webster Dictionary, is “something that may be studied or learned like systematized knowledge.” The systemization of knowledge is what also makes recruiting a science. It allows us to systematically examine each part of our recruiting process and break it down into general knowledge (or best practices) that can be analyzed and applied. Through this systemized process we can more clearly see what works in our recruiting strategy, for instance the best ways to reach the candidates we want. Are they more responsive to posts on our social media pages? Are they finding us in newspaper ads? How do they get to our website’s careers page?
Assessment tools. Once candidates are preliminarily selected, they can be further filtered down using assessment tools that help recruiters determine how likely they are to be successful in the job. These tools are more objective, thus yielding consistent results based on candidate responses. Examining the metrics from these tools can also help us determine whether they’re getting us what we want or not. For instance, if candidates are consistently evaluated in a certain way, yet the turnover rate among new candidates is increasing, then the assessment process might need some tweaking. Without a systemized assessment process it would be harder to determine what works and what doesn’t.
Training. Another way in which science is applied to recruiting is through training, again because it is a systemized process that can be tracked and learned from. Training can encompass anything from interview how-tos for hiring managers to coaching new employees. Through training, we can have more control over the recruiting process and adjust it depending on any evolving needs.
Clearly there are arguments for why effective recruiting is both an art and a science. Do you think it’s more one than the other?