This month’s In the Spotlight features Dr. Jac Fitz-Enz, the founder of the Saratoga Institute and the author of a dozen books, including the award-winning The ROI of Human Capital. He was named by the Society for Human Resource Management as one of the 50 most influential people in human capital management. Here, he speaks about his most recent offering, The New HR Analytics, and whether we’re seeing a trend toward the use of quantitative analysis among human resource professionals.
Q: One of the contributors to The New HR Analytics, Professor David Ulrich, commented on how Michael Lewis’ book Moneyball (inspired by the research of Bill James) helped impact the decision-making of baseball’s front-office by “bringing discipline to intuitive thinking.” Still, it took decades to pierce the old-school style of talent assessment within the MLB. What are your thoughts as far as how quickly HR departments have taken to metrics?
A: I started doing seminars on this topic in 1978, and it was about a dozen years before we really had anything going. There were many resistances — one is that HR people are not interested in numbers. At least they weren’t in those days; they are a little more now. They’re more concerned about working with people than they are about improving the business, and thus didn’t see themselves as a real contributor to the business. There is also a built-in legacy going back to the beginning of HR as just an administrative expense center and the people who came to work there were comfortable with that. So when we tried to introduce the idea that you can begin to talk about the value that they create in terms of numbers — that simply didn’t work for them. They began to come up with lots of excuses: “I don’t know why we’re doing this.” “Nobody has asked me for [metrics] before and we were perfectly happy then.” “I’m afraid that if I put out some numbers, I’m going to get hurt with them.” “I’m too busy.” And on and on and on.
Q: Do you think that we will see a shift in terms of quantitative skills being demanded of professionals who enter the HR field, trickling down to the college level?
A: Yes, but it’s certainly not a groundswell. When we talk about the HR field or any other group, we’re talking about hundreds of thousands of people who practice this arcane art, and there’s a very small percentage in any population who are innovators or early adopters. So if you view those as maybe the top 25 percent to 30 percent of the population, that group is getting it. They’re much more interested in metrics and analytics than the other 70 percent, and that 70 percent will likely never get it. While you can’t talk about a population as though it’s a monolith, it’s fair to say that while there is a growing interest and belief that metrics are important and necessary, this view is prevalent only among the top 30 percent.
Q: Let’s discuss the unique problems facing companies that employ temporary staffing. Obviously, you’ve got a lot of turnover, and often workers have little or no chance at promotion. What are your thoughts as far as assessing the productivity of that segment of the workforce as compared to traditional, full-time employees?
A: Well, you have to break it up into professional and administrative segments — so let’s take a couple different passes at it. Let’s take the staffing function as an example. If you hire someone in the staffing department to simply process documents, then you can apply the same analytics to them that you would apply to anybody else who is processing documents. If you move it up to the professional level — let’s say you hire a contingent recruiter because you’ve got to hire a lot of people. If you bring in this person to do this work, you would measure his ir her work the same way you would measure that of a regular person. The status of the person really makes no difference when you talk about measuring effectiveness or productivity or efficiency. It just doesn’t apply; it’s a person doing a job. So you could be measuring them in terms of numbers of interviews that they conducted or whatever metrics you want to use.
Q: But there are different kinds of motivations involved? In the case of the latter, you can count the number of interviews a worker does, but you really don’t know how well they’re doing the job. How do you perform a quantitative analysis of processes that are subjective in nature?
A: You have to turn either the process steps or the outcome into something visible, because you can measure anything that is visible. What you can’t measure is a concept like leadership or engagement. So you hire me as a contingent interviewer. I come in and start going through these applications based on whatever the criteria are for a given job. Eventually I will turn over an applicant to a hiring manager, right? I say, “Here are three people who I think can do the job as you’ve described it” and the hiring manager goes ahead and interviews them. Then he comes back and says yes all three are good; none of them are good; whatever. And that is basically a form of a valuation of my work, because if I continually send in people who are marginal or not acceptable, then there’s something wrong somewhere. Either the specs on the requisition are wrong — and we could check that out — or I’m not doing a very good job of selecting for whatever reason.
The point is we’re going to measure in terms of the satisfaction of the hiring manager. That’s probably the first and best measure we’d have. Now, if we want a long-term measure, then we can look at the people I referred six months from now and ask, “how good are they?” So now we have a performance measure that we can use to assess the quality of the selection and referrals that I made.
There’s a confounding problem there though — let’s say that I do a good job. I’m sending someone that is a perfect match for the job, etc. And then they are hired and six months later they bomb out, and the reason may have absolutely nothing to do with them — the job may have changed, the supervisor may be a an idiot — there are all kinds of things that happen once someone goes into the snake pit called the organization. So there are these confounding things that make quantitative analysis in a professional situation more difficult than if you’re measuring something in physics where everything is fixed. It’s not a precise science, but you can make a pretty big jump in value.
Q: How about staffing companies themselves — have they also been slow to examine human capital in a quantitative way? Or have they typically been a little bit ahead of the curve when it comes to this?
A: No, they haven’t — at least as far as I know. Now, I haven’t run an HR department in 30 years, so I’m looking at it from the outside. I was very much associated with [a firm] down in Florida in the late 90s and early 2000s. They wanted to be able to use metrics to show that they were creating more value for their clients than other staffing companies. And as it worked out, the fact was that they weren’t, and they weren’t even trying, because this is was just something at the top of the organization that really wasn’t being utilized at the branch level. And I haven’t found any other staffing firms that do a very good job of quantitatively assessing the value of their work. It’s mostly feedback from the customer client or customer satisfaction. We send contingents into a company and then ask how the company feels about them? And the client says they were good, bad or indifferent. They give you some kind of qualitative feedback. I haven’t found any staffing company that really relies on much more than customer feedback.
KJ Fullam is a freelance writer based in Chicago.