Big data is having a big recruiting impact
Data analytics is playing a major role in the recruiting revolution. Agencies, major corporations, and hiring managers across the globe are using Big Data to influence processes and make informed decisions:
Xerox estimated that it costs $5,000 to train each new call-center rep. After analyzing performance data on early hires, the company discovered that candidates with previous call centers experience cost more, but didn’t perform measurably better than those with no experience. More surprisingly: Workers who were active on up to four social networks had significantly lower turnover. As a result of their findings, Xerox cut attrition 20%.
Sears hires up to 160,000 new sales representatives each year from an applicant pool of over 6,000,000. To identify the right candidates, Sears started requiring applicants to complete a videogame-like test that includes simulated interactions with various customer types, from “overly demanding” to “indecisive.”
A few years ago, Wells Fargo was facing high turnover and turned to Big Data for an answer. By analyzing data on current workers and devising personality tests that aren’t easily manipulated, the bank discovered that tellers and other front-facing workers with accounting degrees were top performers, but didn’t stay long in their jobs, according to a widely circulated report.
These are just three recent and high-profile examples. Data can also be utilized every day in the recruiting process at organizations of all sizes.
Instead of data-mining through a stack of paper folders in a musty filing cabinet, recruiters today have access to an unlimited knowledge database via the internet. Social media recruiting (Twitter, Facebook, GitHub, etc.) is a primary candidate source among some industries, while others restrict themselves to LinkedIn and job-sites. Even if candidates are sourced in other traditional methods, social media provides an invaluable means of research, lead generation, and alternative means of contact.
“Expensive software and outsourced research are just numbers, without a human element to give Big Data meaning”
Data aggregation now happens in-house. Computers process the details packed into a company’s received resumes, applications, scanned business cards and proprietary HR databases. Semantic search gives companies the ability to retrieve applicant data based on concepts rather than just key words, making talent management systems more efficient and effective. That said, many ATS systems typically have adapted their legacy technology of fielded databases, which may not meet expectations for performance or handling of unstructured data. The most successful recruiting departments have found workarounds more the maximum utilization of information.
HR departments are deploying tests and games to analyze candidates, measure reactions and find answers for ideal patterns and skill sets. Sears was one example, but they are far from alone in using innovative new tools to collect data. For example, Shell recently used two video games developed by a Silicon Valley startup to analyze incoming candidates. These tools aided business leaders in assessing creativity and innovative thinking. Once the data is collected and processed, a targeted evaluation process makes sense of it all. The optimal result is an array of information sorted into patterns and matches, all thanks to keywords and scores that narrow the initial candidate pool to individuals who demonstrate a proclivity and background suitable to the open positions.
All this compiling and evaluation of data takes expertise and an appreciation of the full picture. Expensive software and outsourced research are just numbers, without a human element to give the data meaning. The use of Big Data must integrate with the broader goals of the company for maximum efficiency and big recruiting results.