Sometimes, the issues that plague people in talent acquisition (TA) are unavoidable and really, really hard to solve.
But there’s one problem — one of the most common TA challenges of all — that we brought on ourselves. In fact, talent acquisition technology created the issue in the first place.
I’m talking about the ever-ballooning times to hire that most if not all TA pros face today. Keeping time to hire brief is a concern of every recruiter (and of ever job seeker, for that matter), yet the average time to hire is growing longer and longer, and we have nothing to blame for it but the sheer size of our technology stacks.
Time to hire hasn’t always been this long. I remember my early days of running a staffing firm, when one could recruit and hire candidates in no time. Why? Because when someone asked me who I knew for a job, I could rattle off a few names with ease. Every great recruiter could. The hard part was getting a candidate to accept a new job, but even that was easier than it is today, because recruiters had preexisting relationships with most of the candidates they were bringing to the table.
Today, the average time to hire is 23 days in the US, according to Glassdoor. In some positions, it takes much longer than that. For example, it takes 88 days to hire a patient examiner.
When Data Grows Out of Control
Most heads of talent at large organizations are in the same boat. Because of the sheer volume of candidates, teams are no longer able to manage their recruitment loads on their own. They need help. They can’t manage all the data.
Plenty of TA technologies have come along purporting to help recruiters manage candidate flows, but they often make the problem worse. Recruiters have so much disparate data within their various recruitment tools, and the platforms rarely communicate with one another. Recruitment teams don’t have the ability to filter, sort, and screen all the data efficiently for their needs.
TA pros are drowning under the heavy burden of all this inscrutable candidate information, from social profiles to employee data, salary ranges to competitive intelligence. It’s difficult to turn all of this into intelligible insight, much less use it to recruit better or faster.
How can we solve this problem? How do we make these huge piles of data easier to use and, subsequently, cut the average time to hire rather than drive it higher and higher?
We need to tackle the overabundance of data, because data is practically worthless without the ability to analyze it. By agreeing on what we need to measure (and when and how), we can reduce time to hire while, at the same time, reducing recruitment marketing spend. It’s crucial for TA teams to identify where they are spending time and money that is essentially going to waste.
It’s Supposed to Be a Human Process
Recruiting, after all, is fundamentally grounded in human interaction. TA technology’s primary purpose should be to end the busy work that keeps recruiters from interacting with their candidate pools.
The part of recruiting that really matters is selling a person on a new job or opportunity. Technology should have made it so that this was the only part left for us to do. Instead, it has buried us under piles of digital trash that slow our progress instead of hastening it.
Big data can be a means for better recruiting, but only if the data is relevant and only if the technology that tracks it also gives us the tools to effectively mine the data for insights. What TA teams truly need to understand is which job boards work best and at the best cost. They need to know which recruiters are the most efficient in a given medium. They need to know how well their referral programs work. This is the kind of data we can actually use to minimize time to hire.
That’s the goal: to move ever closer to the maybe-not-entirely-realistic destination of zero time to hire, where the biggest issue is not finding the perfect candidate but convincing them to take the job.
Time to hire may never be as short as we’d like, but as the economy transforms before our very eyes, it is worth analyzing our recruitment data (and there is a lot of it) to see where we can be better. We can’t simply keep building out the same old processes we’ve used for years.
A version of this article originally appeared on the Red Branch Media blog.