By Gal Almog, cofounder and CEO of Talenya
When it comes to hiring tech talent, the Johnny Lee song, Looking for Love, comes to mind.
“I spent a lifetime lookin’ for you. Single bars and good time lovers were never true. Playing a fools game hopin’ to win. And tellin’ those sweet lies and losin’ again.”
Cue the familiar chorus.
That’s what’s happening in the talent acquisition industry. The truth is many companies are looking in all the wrong places to find talent for hard-to-fill jobs.
A recent survey by worldwide recruiter Hays finds that while companies have high expectations to hire in 2018, a severe skills shortage in the fastest-growing sectors could hamper plans.
The shortage is so severe that 92% of employers say the problem is negatively affecting productivity, employee satisfaction and turnover.
One of the reasons is a whopping 95 percent of the people companies want to hire for critical jobs are not looking.
What’s more, job descriptions are unrealistic. Companies don’t have an accurate picture of the talent pool in their region and many would rather stay rigid than widen the pool to find good candidates.
For example, fully 80 percent of machine learning engineers with Ph.D.s. are scooped up by Google and Facebook, especially those that have patents.
Yet, when we were conducting a search for one tech company, they refused to budge on their requirement for a Ph.D. As a result, a candidate with a master’s degree that was well-qualified was hired by another company, and the job went unfilled for months.
This is a problem, as talent is scarce for highly trained tech jobs like machine learning engineers, data scientists and front-end developers.
These professionals are like rockstars, receiving two to three job offers for every open position, so companies that are more flexible with their requirements have a better chance of landing a good hire.
Companies Aren’t Being Proactive
In many companies, talent acquisition is not forward thinking, with roles being filled in reaction to someone leaving or in the case of startups, when a company gets an infusion of capital.
Many use the “post and pray” approach, hoping that just because they’re XYZ company, they’ll attract the talent they need.
Why are companies so reactive when it comes to hiring?
I think the answer is many are overwhelmed. In his Editor’s Letter, HR Thrive editor James Davis, says, “HR has always been a pretty tough job…and hasn’t gotten any simpler with the introduction of HR technology.” He goes on to tick off the plethora of acronyms from HRMS to ATS.
So, while HR professionals struggle to make sense of all the new technology to perform their job, they also are faced with the time-consuming process of sourcing candidates. While technology is available to help with this, it still doesn’t free them from having to be experts in search.
That said there are companies offering tools that promise to make the HR manger’s job easier and companies successful.
AI Has Entered the Recruitment Industry
As in many industries, artificial intelligence (AI) has arrived in HR to improve search. According to the Deloitte Human Capital Trends report, 38 percent of companies use AI, and 62 percent expect to do so by the end of this year.
With talent scarcity and low unemployment, AI will quickly emerge as a key tool for the HR manager’s toolbox. Research already is proving its success.
According to a Deloitte Bersin report, companies that use AI, predictive data analytics and other technology tools are more successful than those who don’t. Bersin’s research indicates that these companies show 18 percent higher revenue and 30 percent greater profitability compared to those that don’t use these tools.
In addition to helping source candidates, AI can prevent bias in hiring.
“The practice sharpens the talent acquisition function by using data-driven analytics and digital, cognitive tools to better source and assess candidates and prevent possible misjudgments caused by bias or false logic,” according to Deloitte’s press release on the report.
LinkedIn Isn’t Enough
It is sad to acknowledge that after almost 60 years of traditional recruiting ― since employers started to pay placement fees ― and more than 15 years since LinkedIn was founded, nothing dramatically has changed in the traditional $200 billion global recruitment industry.
Relying on LinkedIn and other traditional recruiting methods doesn’t cut it anymore because most companies want passive candidates – those who already have jobs and are not seeking to make a move.
These days most recruiters use LinkedIn to find people, but it’s not enough.
Enter AI recruitment.
AI uses bots to crawl the web and scour hundreds of sites including personal websites, meetup groups, and tech chat rooms, in addition to traditional social media sites.
Not only do these bots find a good match, but they also predict the likelihood that someone is open to a job change.
Matching the candidate to the job description and predicting the likelihood they would switch is one of the best ways to make a successful hire.
Poor Job Descriptions
Today, a company’s exhaustive list of job requirements may not fit the talent pool, and they may overlook talent in their own backyard.
Sitting down with employers and tweaking these descriptions to reflect what is truly essential can help find the right fit.
AI algorithms can apply different skills scenarios, allowing employers to see how minor revisions to a job description can return different results – in real time.
With employer feedback, these algorithms can learn to search for new candidates that best fit the job description.
So how can AI improve the hiring process?
Find Passive Candidates Likely to Switch Jobs
Research shows that the percentage of passive candidates is increasing compared to active candidates looking for a job.
With a 4.1 percent unemployment rate, as of February 2018, it is even more difficult to find the highly skilled IT talent companies are looking for.
Still, we know that about 80% of the talent pool is open to new opportunities and willing to at least listen to what recruiters have to offer them. In the high-tech industry, people change jobs, on average, every two years, so 1 out of 4 candidates is interested in a new job.
The question is, who is that candidate?
AI and machine learning algorithms can help by finding candidates who are likely to switch jobs by looking at things like how long someone is in a job, whether their company is downsizing, and other factors.
Then, those candidates can be matched with job criteria to find the best candidate to recruit.
Save HR Managers from Being Experts in Search
Using the right technology can change candidate sourcing from a manual to an automated process, saving time and money.
This helps hiring managers, so they don’t need to be experts in search and instead can focus on other value-added priorities.
Optimize Job Requirements and Provide Accurate Picture of Talent Pool in Your Region
Time and again, we’ve seen companies with false expectations about the talent in their area.
Many think just because they have a job opening, people will flock to their company. But this isn’t true.
For hard-to-fill tech jobs like machine learning, data scientists, front-end developers and cybersecurity specialists, talent is scarce.
Sometimes, employers don’t really know what they’re looking for or want to insist on requirements that are not realistic.
Recruitment technology can show them the real talent pool for the job they’re trying to fill.
Sometimes it’s a matter of reducing the years of experience, lowering educational requirements or seeing if a skill can be learned on the job. All of this can be done in real time to find the best fit for your organization.
Make Faster Hires
We all know how hiring can drag on.
Unfilled jobs cost money, and the process for finding candidates is expensive – billions of dollars are spent on job advertising and even after people apply, companies on average spend approximately $4,000 per candidate on interviewing, scheduling and assessments, according to research firm Bersin.
Open positions can go unfilled for months for many reasons, including a lack of communication between the HR manager and the department head looking to fill a position.
Conversely, companies using AI can sit down with HR managers and run different scenarios in real time. They also can get feedback from employers and input that data into the algorithm to further refine the search. Technology can speed the process from months to days.
Fill the Pipeline, Instead of Being Reactive
Study after study shows that being reactive is not the best approach to hiring. Having candidates in the pipeline instead of running ad hoc searches leads to more successful hires.
Algorithms can help identify potential candidates, especially for hard-to-fill jobs, changing hiring from a reactive to a proactive process.
Don’t Forget the Human Element
While technology is great, we will always need the human element in hiring. That’s why hiring managers should work with CIOs and other tech leaders in their business to assess which tools and processes work best.
Leveraging the domain expertise in your organization can improve the process of finding and hiring the best talent, as they speak the language of your candidates and can provide feedback that in turn can improve the algorithms.
What This Means for Companies
I believe the recruitment industry is ripe for disruption. Just like Uber disrupted the ride-sharing industry, technology firms using AI and machine learning will improve the recruitment industry.
Companies need to take stock of their workforce goals and consider how AI can improve them. Finding a recruitment partner with experience in the industry and the most advanced technology will lead to better and faster hiring.
About Gal Almog
Gal Almog is the CEO and co-founder of Talenya, a technology company that disrupts the recruitment industry using big data, machine learning and a revolutionary, new business model. For more information, visit www.talenya.com. You can follow him on Twitter @galalmog or connect with him on LinkedIn.