Why Big Data is A Big Deal for Recruiting & Hiring

Big Data is a big deal these days. And for good reason. “Recruiting is becoming a science”, to use LinkedIn Talent Management VP Dan Shapiro’s words, as more and more companies are highly investing in the latest technologies. While we’re all interested in what the future holds for the use of Big Data in recruiting, here are my thoughts about its role in the hiring process and the greatest challenges it presents for recruiters.

How do you see the role of Big Data in the hiring process in the future?

The role of Big Data in the hiring process of the future, I think, is going to be an increase in what’s already the greatest source of external hire (referrals) and internal transfers/promotions (which accounts for a significant share of all jobs filled, particularly in enterprise organizations). This is due to technology that allows the employer greater access to data of a company’s existing employees and their networks which will ultimately lead to a faster hiring process of more qualified talent.

What do you think are the main benefits of the use of Big Data in the hiring process?

The main benefits of the use of Big Data in the hiring process is that employers will have much more visibility into their workforce and their skills which will allow them to make better recruiting decisions. Real-time feedback and performance management tools paired with social platforms, both internal and external, will increase predictive analysis. If the company is able to use people analytics in a more strategic and scientific fashion, hiring decisions will become more accurate and the success of matching open roles to people (internally and externally).

Employers will also benefit from Big data in the hiring process due to greater access to data of current employees and their networks. By tapping into employees’ existing networks and connections with behavioral targeting and referral incentives, employers will have the ability to proactively generate referrals. In the past, referrals presented the most effective predictor of quality of hire for externally sourced talent.

What do you think are the greatest challenges for recruiters when using Big Data for hiring?

The greatest challenges for recruiters when using Big Data for hiring is that their applicant tracking or human capital management systems are not built for unstructured data like social profiles and open web results, so they are forced to rely on structured data that’s defined by a legacy system.

Any final thoughts?

Big Data and systems that capture them are capable of measuring many metrics. It has to be kept in mind, that analytics give only part of the recruiting picture because they rely heavily on candidate self-reporting. Subsequently, automated prescreens will skew data significantly. That means that actually analyzing the data for anything meaningful will be the greatest challenge for every recruiter.

This post is an excerpt from a recent interview conducted with Mona Berberich at Better Weekdays. To learn more about Better Weekdays, visit them at http://www.betterweekdays.com.

While I’m obviously not an expert in pre-employment assessment (which generally comes in after my work on a search is winding up), they have a really cool, innovative tool which actually seems to give better feedback & insight into a potential employee’s personality, work styles/preferences and team dynamics than pretty much every other tool I’ve seen on the market. So make sure to check them out.

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