Finding the right employees to grow your business is such a massive pain point that investors have pumped billions of dollars over the past decade into trying to alleviate this headache — $400 million in venture capital for recruiting and hiring technology so far in this year alone, according to a TechCrunch post from last week. The question is, is all the innovation in the hiring space making it easier for you to actually find the right employees, or conversely for job seekers to find the right jobs?
We can certainly see that it’s easier than ever to advertise a job and to find résumés. That’s thanks to a wave of job aggregators and marketplaces. For a long time, these solutions helped alleviate a prevailing pain — not enough applicants for the employer, not enough postings for the job seeker. In this sense, technology vastly improved upon the paper-based world of job classifieds. But as job aggregators and marketplaces have scaled, ratcheting up the volume of postings and résumés, a new problem has emerged: sorting through the noise. Imagine a pile of résumés — there’s no way to know if the right candidate will be passed over. Not good for the employer, nor the job seeker.
What happens as the job aggregators and job marketplaces continue to grow and the volume of candidates and jobs increases?
Aren’t there solutions to help us with the résumé pile? What about tools that filter résumés based on criteria such as keywords and categories? The essential problem with such tools is that they can only analyze information that is self-reported, and therefore not completely reliable. They are also biased toward skills and experience, which don’t provide the full picture on a candidate’s ability to do the job. The reality is that screening and judging candidates according to résumés and similar information has the same success rate as a coin toss.
So, what’s the answer then? If throwing technology at the résumé problem is not the right solution, then we’re back where we started with job aggregators and job marketplaces failing to move the needle. The bigger they get, the less likely it becomes that the right person is matched with the right job, which diminishes the long-term value of these platforms.
The right answer is the one that addresses the fact that employers don’t want to have to advertise their jobs and job seekers don’t want to have to search through job postings to find employment. What both of them would really like to do is wave a magic wand and be connected with the perfect match of a job or employee. Could technology create this reality? Or is this notion simply a dream or something akin to science fiction? Actually, no. It is the future of hiring and we see it emerging today in something called job matching.
Essentially, job matching solutions help employers and job seekers cut through the noise to pinpoint, respectively, the right person and the right role at the right time. This is where the innovation in hiring will be.
In fact, this TechCrunch article, posted this week, reports that job marketplace Elance-oDesk, which just raised $30 million, has been working to improve its matching capabilities.
Given that matching is the future of hiring, it makes sense to define the criteria for success. As I see it, there are three essential elements of a successful solution:
Leverages the true predictors of job success. To be effective, job matching must involve the true predictors of job success, which include both sides of the hiring equation: skills, knowledge and experience on the one hand, and personality, motivation and culture fit on the other. This means that job matching has to go beyond what the résumé provides.
It’s mobile. Candidates are mobile, but their résumés are not. Successful job matching will address this new reality and make real-time job matching possible where a large percentage of hiring occurs in the U.S., which is in the retail and restaurant sectors.
Gets more valuable with scale. Job matching must improve with scale, rather than degrade. Otherwise, we’ll just end up in the same position the job aggregators and job marketplaces have taken us. Predictive analytics that utilize machine learning will have to generate a network effect, so that the marketplace becomes more valuable with each candidate and each job — instead of just more noisy. In other words, as the solution grows it must get easier and easier, not harder and harder, to pinpoint the right person and the right job.
I think about these challenges every day because I think we’re at the cusp of a revolution that’s been 30 years in the making — more money hits the market, but there’s been little innovation to date. Soon, we’ll see a world where it’s possible to have the right people in the right jobs, resulting in happier employees and more productive organizations.
Ben Baldwin is the founder of ClearFit, a job matching service used by thousands of companies who want an easy way to find and hire the right employees. He’s a patent holder, Wall Street Journal Startup Mentor, business advisor and speaker.