Intuition. Thats what most recruiters and hiring managers use to make their decisions on which applicants get offers. In a world that is moving toward more data and logic-driven decisions at every turn, recruiting is a surprising change of pace. Or is it? Big data has touched nearly every facet of business, and recruiting is no exception. Large companies have been using data to choose their new employees and decrease turnover for several years. But how much better is predictive analysis than the human intuition when it comes to recruiting?
Can Big Data Save Companies Money on Hiring?
It costs a lot to hire and train an employee. Figures vary widely based on the type of position, but some studies estimate that it costs 6-9 months of the new employees salary for onboarding and training. With costs like that, minimizing turnover is a key money-saving goal for any business.
Data points available from information about applicants online have helped hiring managers to devise new ways of evaluating potential employees, including complex personality tests that can help predict culture fit. But only when large data sets are used to predict specific outcomes, like retention rates, does big data come into recruiting.
For the big companies that have started using data in the recruiting process, minimizing turnover is based on predictions. These predictions can only be made with thousands upon thousands of data points, collected over time. Because recruiting using big data is still fairly new, theres no information about how recruiting using predictive analytics affects overall diversity in the workplace, or how effective the new employees are in their positions. Most companies are looking for specific metrics from the practice, not overall trends. However, companies are seeing benefit from big data recruitingJohn Sullivan, a talent management expert, estimates that big data is about 25% more effective than intuition when making hiring decisions.
There are also some drawbacks to big data in recruitingits easy to make assumptions about causality when it does not exist. Just because one person was successful in the position does not mean that all of the same traits will guarantee a good hire next time. Companies also need to be careful that their algorithms do not unconsciously promote bias and prevent diversity within an organization.
Big Data in Action
Many large companies have seen huge success in bringing big data into their HR and recruiting efforts. When Xerox started using big data to evaluate what made new employees stay with the company, they found that previous experience didnt make much of a differencebut their online personality did. New hires who were active on social media were more likely to stay on in their positions. By using this data, Xerox was able to cut their turnover rates by 20% in the call center.
Sears used the data collected for recruiting to refine the interview process. During their hiring process, applicants now have to complete a video simulation that has the prospective workers interact with virtual customers. This helps the organization find the applicants who are most likely to succeed from an enormous pool of potential workers.
These are just a few examples of how important big data in recruiting has become for large companies with overwhelming applicant pools and vacancies. In these situations, such as in industries like retail, healthcare, and tech, recruiters need all the help they can get to sift through the large number of applicants.
Should You Use Big Data in Recruiting?
Theres a big drawback to all of this for most hiring managers: its not always easy to implement the technology to collect the necessary information about which applicants are likely to do well, and someone needs to be able to interpret these data. For companies that already use predictive analytics to reach their business goals (and many do), big data in recruiting may make a lot of sense. For businesses that havent taken the first steps into the big data world yet, it may not be cost-effective or significant enough to start for the time being. Large companies have saved millions on recruiting analytics, but the big guys also have a great infrastructure in place and funding to put into these projects. As time goes on and big data tools become more accessible, recruiting using predictive analytics will only become more important in the hiring world.
