TEKsystems recently put out a report showing that approximately 80 percent of all IT professionals believe that a skills gap exists in tech industries today. Backed by claims of mass projected growth in the field that the U.S. won’t be able to fill, as well as multiple articles and resources written on how to bridge the gap, it’s hard to argue that it’s not real. Obviously, there is an actual, tangible number of open jobs out there that are not being filled — but the point of contention is why?
While it isn’t news that the gap exists, it is news that IT professionals and IT leaders disagree on what’s causing it. In the same TEKsystems report, 70 percent of IT leaders that were surveyed viewed actual lack of skill to be the main hindrance in hireability, while only about 25 percent of actual IT professionals agree. IT professionals, instead, believe that a disparity between actual education and skill required versus the education and skill sought in the job description is the problem.
David Wagner further explores the problem in an article he authored on InformationWeek, mentioning that when IT professionals were told why they didn’t get the job, only 25 percent of them were told they lacked the skill for the job, while 29 percent of them were told they were overqualified (overqualification was actually the No. 1 response).
The question raised is: How is it possible that such a huge skills gap exists when only 1 in 4 applicants are being told they don’t have the skills, while another 1 in 4 are being told that they’re overqualified?
To answer this, we have to dive into the hiring process. First of all, the reasons that employers give as to why a candidate was not hired may not reflect the actual reason for the pass. Alison Green writes on AskAManager.com that lawyers often advise managers “not to be specific about reasons [they weren’t hired], because it can open the door to legal issues.”
Not everybody actually knows why they didn’t get the job.
For example, if a hiring manager turns down an applicant, citing that she doesn’t know a programming language such as Python, but then hires another applicant that wows the manager in some other way, even though this new applicant also does not know Python, the original applicant might get the impression that she was not hired because she is a woman, or is pregnant or myriad other things. The company will then have to spend time and money addressing the lawsuit, so they prefer a bland partial-answer — such as, “You’re overqualified.”
Of course, there may be many other reasons that cause a hiring manager to pass on an applicant that seemingly don’t warrant feedback, but the point is that not everybody actually knows why they didn’t get the job — especially in situations when the job remains unfilled. Enter the Purple Unicorn.
Kenneth Chestnut of Amazon Web Services wrote a piece on LinkedIn, titled Beware of the Purple Unicorn (with Wings) When Hiring, in which he cautions hiring managers against over-specifying job qualifications while searching for candidates.
“Many companies don’t understand their hiring needs,” Chestnut says, “and, as a result, have only a vague idea of what defines a great job candidate… [as such], companies will end up posting job descriptions for which no ideal candidate actually exists.” As such, hiring managers will pass over many applicants who are most likely qualified for the job, but that are not the elusive “purple unicorn with wings” they were looking for.
This presents an interesting situation. Either these companies are alright with the job remaining unfilled, or they are looking for something that doesn’t exist. This isn’t surprising, when we take into account the fields of big data and the Internet of Things (IoT).
In 2015, the U.S. hit the mark of having about 25 Internet-connected devices per every 100 inhabitants, and that number will only continue to grow (with estimates indicating that we might see up to 25 billion Internet-connected devices by 2020). The field of “big data” itself seemingly came out of nowhere, the term being coined (according to Forbes) in February of 2010.
Since then, both the IoT and big data have become huge buzzwords across many major industries, and companies are finding that they either need to join the fray or bow out of modern business.
Unfortunately, these companies’ hiring managers seem to know as much about big data as they do about what’s required to harness it, because requiring three to five years of experience in a field that’s only been around for approximately five years means two things.
Hire for what you can’t teach and focus on education and training for the rest. Jason Hayman
First, the fusion of skills that comprise a field such as data science are varied. Secondary education generally isn’t properly training tomorrow’s hires in all of these skills (let alone most of them), so finding all of them in one person is like trying to find… well, a purple unicorn. The second is that this field has not been around long enough for many to have actual experience in it, so “equivalent experience” is generally out the window.
So what’s an IT hiring manager to do? In an interview with CIO.com, TEKsystems’ research manager Jason Hayman advocates separating the essential skills from the this-would-be-nice-to-have skills in the job description, as well as focusing on the future of prospective employees rather than the immediate “now.”
“Hire for what you can’t teach and focus on education and training for the rest,” says Hayman. “How ambitious is this candidate? How dedicated? What’s their willingness to learn? Focus on what their innate skills are, rather than matching a laundry list of requirements.”
Of course, sometimes, that laundry list of requirements is simply a list of requirements that only a seemingly superhuman programmer or data scientist could fill. The good news, according to InsideBigData.com, is that the conventional mindset is beginning to change and “the search for a single Superman is [being] wisely replaced with building a team of people with complementary skills.”
If more employers and hiring managers would either relax their standards when creating job listings and focus more on how well an employee can be trained to do their job, or begin to assemble the winged purple unicorn out of various parts, the STEM skills gap would fade into myth.
Because, horses are as commonplace as skilled programmers, horns pop up as frequently as engineers and wings are as natural as computer scientists — but if you put them together, you just might have something that looks like a unicorn with wings.