Big Data’s Powerful Applications in HR
Big data, along with its three key features of volume, velocity, and variety, is considered the foundation of modern analytical systems. As of 2013, 91% of America’s top executives have been planning big data initiatives. And finance and marketing industries have already acknowledged (and leveraged) the power of machine learning algorithms to identify profitable stocks and customize catering to clients.
As far as HR purposes go, Google (a data-driven company) has developed a model that can predict promotions with 90% accuracy. Other managers, however, have not been able to use the big data/HR equation because people aren’t ready to hand over control to the computer.
So just how is big data affecting HR and how will it in the future? Let’s explore that!
Big Data for HR
If HR teams were to use a statistical model based on big data, that would mean “replacing presumptions with validation, hunches with data, and intuition with success ratio.” Talent scouts often face a significant challenge when structuring large quantities of different data that needs to be evaluated against a unitary scorecard. Big data offers a solution to that by employing methods specially designed for variety.
Taking it a few steps further, big data could provide some serious benefits in the HR sector. These benefits include
- Decreasing the cost of bad hires
- -Big data can help cut down on bad hires.
- -Wrongfully chosen employees can cost much more than just their salary and benefits:
- -Recruitment costs
- -Training expenditures
- -Productivity loss
- -Negative client reviews
- -A primary challenge of HR analytics is using big data to predict a match between candidate skills and personal beliefs against company needs and values.
- Increasing retention rates
- -Big data algorithms nominate individuals by studying employees’ online activity, profile updates, employment history, job performance, and payroll data
- -Employees that are red-flagged by the algorithm could be given a raise, a more challenging role, or more training in order to prevent resignations
- -Companies that already do this, including Xerox, Walmart, and Credit Suisse, have seen retention increase as much as 20% with these algorithms.
- Performance prediction
- -When you’re hiring, big data HR analytics models can help you find the best candidate profiles based on the job’s requirements and existing top performers.
- -They do this by using existing records of successful candidates to create high performer profiles which you can use as to create a targeted head-hunting tool to send personalized messages to the right talent.
- -Predictions are necessary to evaluate future job openings, promotions, and even layoffs, and aligning models to your business strategy can help you use big data to save time and money on recruitment.
- Improving benefits packages
- -Using big data similar to insurance companies, employers can gather health related data of their staff and candidates to create more attractive and useful packages.
- -Keep in mind that you should be transparent about collecting such data, stating your final goals, to avoid legal issues related to discrimination practices.
Legal and Ethical Issues
Although there aren’t any legal statements against using big data for HR analyses and evaluations, ethical concerns are still a factor to consider. Privacy is an important concern and many people are afraid that the numbers could work against them and even encourage discrimination.
Of course, stereotyping and unfair treatment of an individual outlier based on the general performance of a group is not acceptable in the business sector and is an unsolved problem that could result from using big data with HR. That’s why it’s important to keep in mind that algorithms do not have intuition and are unable to assess undocumented progress, which is where HR representatives come in.
So what do you think? Will you begin using big data to improve your HR department and the reliability and productivity of your employees? Do you use it already? We’d love to hear all about it – just leave us a comment below!