Taking a cue from Spotify, the recruiting industry is poised to create tailored playlists of design professionals looking for the ideal job.
I love listening to music. I think I have a fairly diverse palate. I like jazz – Coltrane, Monk, and Davis. I like old school hip-hop – Tribe Called Quest, De La Soul, and Run D.M.C. I’m a huge fan of the Police and ‘80s bands like Dexys Midnight Runners, Devo, B-52’s, and the Talking Heads. I love Jamiroquai and the Brand New Heavies. And, I can even hang with opera – think Turandot and Maria Callas.
It sounds crazy, and I’m fine with it. It’s funny because before the Spotify app came along, I was just a guy with a rambling collection of music from all genres. Now, not only does Spotify organize all of my music by categories and preferred playlists, but the Spotify algorithm observes my listening behavior and makes recommendations of other artists and songs that it thinks I may like. I look forward to my “Discover Weekly” playlist every Monday morning. Because of this algorithm, my musical selection has undergone a tremendous expansion.
This type of algorithmic programming and machine learning is creeping into every facet of our lives, including what we listen to or buy from Amazon – and yes, even how we recruit design professionals.
You didn’t think I was going to spend an entire article talking about music and playlists, did you? No, I just want to drive home the point that technology is changing the way we do everything. Recruiting is no exception.
Here are a few ways that well-placed algorithms and machine learning can help every HR department remove human biases and improve the hiring process.
For several decades now we’ve had personality tests to determine the types of profiles that perform the best in a variety of firm cultures. Now, algorithms will apply statistical modeling to candidate information from applications and other online forms that you put out there to gather information. This information, when parsed through a capable algorithm, can help HR departments predict the likelihood of whether a candidate will be a good fit.
Instead of relying solely on a hiring manager, the algorithm can draw from a wider bank of information and process an enormous amount of data points that can help determine which potential candidates will be appropriate for a position. In most cases, an algorithm can create a rating score of each candidate and compare that to historical information on former hires to determine the potential for success or failure. It sounds like a monumental task, but we are talking about a millisecond of computer time to give you the information you need to make a good hire.
In an upcoming episode of The Zweig Letter Podcast, we have some very talented programmers who will discuss the growth of algorithms and machine learning in the recruitment space. It will shed additional light on this subject.
Like humans, I don’t think computers will be infallible when it comes to the recruitment process. But I suspect that someone will develop a reliable algorithm that will make recruiting talent for your firm a much easier task. I know I can’t wait to use it. Firms are already employing this technology. Will your firm be next?
Randy Wilburn is director of executive search at Zweig Group. Contact him at firstname.lastname@example.org.
This article is from issue 1186 of The Zweig Letter. Interested in more management advice every week from Mark Zweig, the Zweig Group team, and a talented list of other guest writers? Click here to subscribe or get a free trial of The Zweig Letter.