Small Data Plays a Big Role in IT Recruiting

Job applicant tracking systems capture massive amounts of info on candidates. But all that data doesn't help if the best candidates aren't able or willing to complete the process. Going more simple and streamlined can make it easier to find talent.

HR professionals and recruiters continue to rely on big data to refine the application and hiring process. They are tapping data analytics to predict ROI, performance and likely behavior. However, with so much valuable data available, it's easy to gloss over one of the most important parts of the recruiting process: the human element.

Focusing on "small data" can not only improve the speed and efficiency of your hiring process and pinpoint obstacles in your organization, it can make it easier to find passive talent candidates.

[Related: How Little Debbie Used Predictive Analytics to Survive Snack Industry Shakeup]

"It's been so exciting over the last few years to see the number of data collection and analysis tools growing, and I have no problem with using those tools," says Jason Berkowitz, vice president of client services at Seven Step Recruiting Process Outsourcing (RPO.)

Big data and analysis tools are helping organizations refine their hiring process. For example, HR departments and recruiter can discover where candidates hit obstacles in the application process and which elements take candidates the longest to complete.

Data analytics also help businesses better understand how their overall attraction, hiring and retention process affects their ability to find and keep top talent.

However, focusing only on what job-seekers are doing throughout the process and how they are navigating that process is only part of the equation. You must also remember to focus on the why, Berkowitz says.

Don't Forget to Make It Personal

"I worry that what gets lost is the fact that -- when we are looking for and hiring talent -- were talking about people. Real, live, human beings who are more than a resume and an application. They have a whole, rich life other than their job, and those elements of their lives can often add depth and breadth to their marketability and their value as an employee," Berkowitz says.

[Related: How to Use Social Media to Improve Your IT Recruiting Strategy]

Remembering the human story behind the digital or paper-based appearance of a candidate is especially important for the younger generation of recruiters, Berkowitz says. Many are digital natives and sometimes get distracted by the volumes of information that big data analytics tools deliver about candidates.

"What we call 'small data' can teach us many things about human behavior, specifically behavior related to the hiring and application process," Berkowitz says. "You can intuit things about a potential employee's 'soft skills' like attention to detail, perseverance and creativity, for instance," he says.

Small data can also help businesses streamline and ease the recruiting and hiring process itself, based on the behavior of applicants, Berkowitz says.

[Related: Shortage of Project Managers Sends Businesses Scrambling]

Many companies believe that candidates who really want to work for them will do whatever it takes to complete the application process; if they don't, then they wouldn't be a good fit. But there are so many reasons a candidate might not finish an application process, and big data can only tell part of the story, he says.

[Related: Shortage of Project Managers Sends Businesses Scrambling]

Are You Driving the Best Candidates Away?

"There's a misconception I often hear that says, 'If they really want to work here, they'll go through my process, no matter what. If they don't want to do that, we don't want them.' But that mindset ignores passive candidates -- the best candidates may not even be aware they want to work for you," Berkowitz says.

Simplifying and streamlining the application and hiring process can make it easier for businesses to find talent. "By erecting barriers to the process, you may be turning them off to your opportunities," Berkowitz says.

"What big data can't tell us is 'why did a candidate drop out' of the application process? Why did they struggle with certain steps? What can we do to make it easier for applicants to get through this? You could be losing candidates who would be perfect for certain roles, but they are dropping out of the process before they even get to interview. So, I want to sit down and understand from that person what their individual experience was, and try to pinpoint whether or not there's a larger problem within the organization," Berkowitz says.

Sharon Florentine covers IT careers and data center topics for CIO.com. Follow Sharon on Twitter @MyShar0na. Email her at sflorentine@cio.com Follow everything from CIO.com on Twitter @CIOonline and on Facebook.

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