I'm Nikos Dimotakis and I am a professor in the department of management. Alright now, where are you from? Where did it all start? I'm originally from Crete, Greece. I came to the U.S. in 2003 where I got my MBA and Ph.D. at Michigan State University. Okay, what was the Ph.D. in? Organizational Behavior and Human Resources. I then worked at Georgia State, then the University of Nebraska for a bit, until I joined Spears in 2019. Okay, what courses have you taught since 2019? I have taught HR Analytics at the undergraduate level and I have taught advanced statistics at the Executive and Ph.D. programs.

Okay, so when it comes to HR Analytics, what is that? So, it's a way of looking at the world. Analytics is essentially the use of data that supports decisions and to understand our world a little bit better. In the class, what we do is we take some foundational approaches to staffing and talent management and compensation, and we intergrade them with a little bit of statistics and a little bit of data science and a little bit of quantitative approaches, to try and make little bit better sense of our world. It's the way to kind of summarize data, both graphically and quantitatively. It's a way to find patterns in life and specifically to organizations, it's a way to make sure we're making correct decisions. That the decisions have the impact we want and also importantly, that we're following the law, and to the best extent possible, running an ethical and law-abiding organization.

Who in the organization will look at this data? Who works with this the most? Well everybody really, so, there can be the analysts that are primarily responsible for producing this and analyzing it and creating all these ideas. But, it's also managers who need to be able to understand that data to make sure that they can follow what the processes were, how the decisions were made to produce certain results or not, and then to intergrade that data with different pieces of information to make decisions. Consultants will use the data to kind of understand what the context is and to promote decisions. The courts will use the data to figure out if an organization is violating the law or not. So it really behooves everybody to have at least a passing familiarity of some of this.

When it comes to analyzing this data and everything, do you mind walking me through the process it takes? Well, that's a long conversation, maybe you wanna take the class. But, basically the idea is that we are not so much into using particular programs, but more so understanding what the processes are behind it. So, we start with understanding what are their best guess is for something based on the data that we want. So then, we want to understand how uncertain that best guess might be. We can also use that data to compare let's say, one group or another, one year or another, or us with other competitors, or one employee to other employees, one applicant to other applicants. We can also use that data to find relationships. Is people's compensation associated with their performance? Are we using our money right? Are we getting the responses we want from the interventions that we have and the programs we run? And you know in a very very small nutshell, that would be kind of a first few steps. Then you have to present it in some form whether it's the text, whether it's the number format, whether it's producing graphs to do this. Somehow not only create these insights but also know how certain you are about these insights, and then communicate them to other people.

Are there certain industries that need HR analytics? All the industries need them. Every industry where people are employed, where people might be distinguishable from one another, where law is applied, everybody is gonna need some aspect of it. It's pretty universal.