We find that sometimes, the issues that plague people in talent acquisition are really, really hard to solve. But there’s one problem that we brought on ourselves. In fact, technology is what created the issue in the first place, if you think about it. I’m talking about time to hire. Time to hire is a metric that concerns every recruiter (and jobseeker for that matter) yet it’s being stretched ever longer due to the sheer size of our technology stacks.
Time to hire hasn’t always been this long. In the early days of running a staffing firm, one could recruit and hire candidates in no time. Why? Because when someone asked me who I knew for a job, great recruiters (and networkers) could rattle off a few names easily. The hard part was getting them to accept the job, but even that was easier than today because 4 out of 5 of those names had a relationship behind them. Now, the average time to hire a software engineer is 21 days; 4 times longer for patent examiners at 88 days. That’s nearly 3 months! It’s an issue that I KNOW affects business leaders because one of them came to me about it.
THERE’S A PROBLEM
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 load on their own.
- They need help.
- They need to prove their value.
- They can’t manage all the data.
Recruiters had so much disparate data within their tools – and the platforms didn’t communicate with one another – the recruitment team didn’t have the ability to filter, sort and screen this data efficiently.
Many recruitment departments are drowning under the heavy burden of candidate information they can’t possibly sift through manually. From social profiles to employee data; salary ranges to competitive intelligence, it’s difficult to translate into something one can understand, MUCH LESS something you can use to recruit better or faster.
- Just one-third of HR managers describe their proficiency with data as “good” or “excellent”.
- 71% of companies see people analytics as a high priority in their organization, with 31% rating it very important.
- 3 out of 5 employees in leadership roles say a failure to adopt big data could lead to obsolescence.
Some vendors have realized the need for an aggregator of recruitment proportions.
- How can we solve the challenges with recruiting?
- How do we solve the time to hire problem?
- How do we make this huge pile of data easier to comb through?
Once we realized the need to tackle the abundance of data because data is worse than useless without the ability to analyze it. By analyzing the data and 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 to identify where we’re spending time and money that is essentially going to waste.
- The interview process takes an average of 22.9 days. (Source)
- It takes five to six weeks on average to get a job offer. (Source)
- 45% think hiring managers are in the best position to increase diversity. (Source)
- Recruiters take an average of 6 seconds to scan a resume. (Source)
- 41% of U.S. employers plan to use text messages to schedule job interviews. (Source)
- 56% of recruiters said they can’t make good hires because of lengthy hiring procedures. (Source)
IT’S A HUMAN PROCESS
Recruitment, after all, is fundamentally based on human interaction. That’s why technology will only help resolve the busy work that keeps them from interacting with their candidate pool. The part of recruiting that really matters is selling the person on a new job or opportunity.
TECHNOLOGY SHOULD HAVE MADE THAT THE ONLY PART LEFT FOR US TO DO.
Instead, we find ourselves faced with frustrating piles of digital trash that slows progress instead of hastening it.
Big data is a means for better recruiting, through number knowledge and practical application. Understanding which job boards work best and at the best cost, which recruiters are the most efficient in a given medium, even how well the referral program operates and the like, is crucial to minimizing the time to hire from an extraordinarily lengthy process back to the quick (but complex) human interaction it should be. After all, who’s to say your recruitment messaging isn’t getting lost in the noise?
- Only 23% of organizations (or companies) say they have a strategy for big data.
- There are 294 billion emails sent every day and over 1 billion Google searches every day.
- 2.5 quintillion bytes of data are produced every single day.
- Google stores 10 billion gigabytes of data every day.
That’s the goal, to move ever closer to the elusive, maybe not an entirely realistic goal of zero time to hire. Where the biggest issue is no longer finding the perfect candidate, but convincing them to move across the country or knowing just where she spends her time online so you can connect.
Time to hire may never be as short as we’d like, but as the economy continues to shift and the workforce continues to change, it’s worth analyzing our recruitment data (and there is a LOT of it) to see where we can BE better, and not just build out the same old processes we did years ago.
This blog was originally published here.
