Let’s be honest—technology bombards us with more information than ever before. Because of this, we’ve created many platforms and tech tools that help us stay organized, efficient, and profitable. The rise of technology in business, along with its future possibilities, makes this an exciting time for everyone. Technology can quickly retrieve vast amounts of data in seconds, allowing us to make decisions that are far better informed than in the past.
However, we should think of these technological capabilities as tools to help us make more informed decisions, not as mechanisms to make decisions for us. Although this advice can be applied in several domains, it’s no more relevant than in the world of people analytics.
So what is “People analytics”?
People analytics simply means using data to make decisions about employees and talent in a company. It helps shape HR strategies, hiring or firing decisions, and finding suitable candidates, among other things. Luckily, we now have technology that can evaluate and analyze certain factors to “predict” how successful an employee will be in their job. This can be achieved through basic correlation tables, more detailed regression models, or even advanced predictive techniques. No matter the analysis method, companies want to ensure they are hiring the right person for each role. They also seek to understand how to retain employees and what factors lead to longer employment or, conversely, higher turnover rates.
Organizations that use people analytics to inform hiring decisions have the ability to remove objective bias. McKinsey Quarterly’s article brilliantly sums this up with, “The important advantage of the new analytics techniques…is that they are predictive, rather than reactive, and they provide more objective information than the more qualitative findings of a one-on-one discussion.” When combining skilled HR hiring professionals with the proper analytics platform, organizations can reduce bias, increase accuracy in job placement, reduce the risk inherent to hiring new people, and decrease retention expenses in the long run (as evidenced by the aforementioned article’s examples). Although people analytics is helpful to the hiring process, the data can tell you more than just the best candidate for a job.
When organizations apply people analytics to their existing workforce, they gain insight into motivates them, what leaders should continue doing, and how they might improve. For example, Fecheyr-Lippens, Schaninger, and Tanner used people analytics in a study to understand employee retention. Their data indicated that “a lack of mentoring and coaching and of ‘affiliation’ with people who have similar interests” were leading drivers of those considered a “flight risk”. Additionally, the researchers point out how predictive analytics within the realm of human resources helped organizations understand what their employees value while reducing the costs associated with turnover.
Although people analytics and predictive modeling have become more advanced, we must remember the human element in all HR decisions. Our technological capabilities should do nothing more than provide decision-makers with the most accurate and relevant data possible so they can make an informed decision. There are several risks associated with “over-datafication” when people rely too much on data and technology, but that’s a topic for another day…