Have you ever made a hiring mistake? If you are like most firms, hiring errors are among the most costly mistakes firms regularly make. Biases, human error, and unsophisticated tools to understand candidate-company fit are among some of the reasons people—and companies—continually make hiring mistakes.
Recently, I came across a firm called Pegged Software that is using “People Analytics” to significantly improve hiring outcomes. Applying sophisticated tools to very large databases aggregating candidate and employee information, Pegged Software has helped over 130 facilities in the healthcare space achieve an average decrease in turnover of 38% and improve organizational outcomes, such as employee satisfaction. To learn more about how people analytics can transform an important part of the firm (especially in labor-intensive industries such as retail, healthcare, etc.), I talked with the CEO of Pegged Software, Michael Rosenbaum. What follows are his thoughts on how people analytics is disrupting talent management.
Kimberly Whitler: What is “people analytics”?
Michael Rosenbaum: People analytics is based on the idea that there is a lot more information available on everyone in the world–and specifically employees and potential employees–than what we currently use to make hiring decisions. Employees interact with technology all of the time, and these interactions generate a lot of data that can be used in a variety of ways.
Marketers, for example, have really pioneered the use of this data and analytics to figure out a number of consumer-related issues, such as the likelihood that somebody would be interested in a product. Those same technologies and analytical tools can be applied to predicting whether somebody will be an exceptional performer in their job, helping predict his or her career trajectory. At Pegged, we collect data from the 3 million job applications a year we process, from the approximately 135 healthcare facilities where we are deployed. We have a lot of outcome data across institutions and can apply that to the new hire process. Our goal is to identify the right person for the job by using all of that data to predict who is most likely to perform exceptionally in each job. There are other companies which are focusing on predicting turnover. Our goal is to prevent turnover by identifying the right candidate up front.
Whitler: Is this a new or mature area of analytics?
Rosenbaum: It’s a pretty new space. We’ve been working on this awhile but there are just the beginning signs of a number of companies entering the field. The reason that the field is just emerging is because: 1) the technologies you need to have to run sophisticated analyses at high success rates have matured over the past couple of years, and 2) while the idea that you can use data to make decisions more effectively sometimes has been around, there is now a growing realization that you can apply this to a broader set of questions.
Whitler: Why does this matter for C-Level executives and more specifically, for CMOs?
Rosenbaum: All C-level executives should care about how to hire more effectively. Having the right talent in the right place at the right time impacts morale, individual and group performance, efficiency, and performance outcomes. Labor is often a significant cost for any company, and perhaps more significantly having exceptional talent critical for driving any organization forward. I have yet to find a CEO who says that s/he would not like to reduce turnover and improve performance. In fact, at the top of most lists that rank CEO challenges—you’ll find talent and human capital.
CMOs should care because they actually are the enterprise leaders whose area of expertise pioneered much of this technology, and as a result they are closest to understanding the technology and its potential. Marketers originally innovated and spawned this technology and so they are arguably in the best position to help a firm understand the value. As a result, CMOs can be an important source of knowledge and expertise for the entire executive team, when that team is discussing ways to apply these same processes to talent. This is an opportunity for the CMO to be a thought leader in the C-suite around about how these technologies work and why they are effective.