The Great Resignation: HR analytics can help predict who might be looking for another job

If you can identify a dissatisfied worker, you might be able to work to keep them before they head for greener pastures.

Keep workers from leaving by knowing who is unhappy with their jobs before they quit

TechRepublic's Karen Roby spoke with Kon Leong, CEO and founder of ZL Technologies, about HR analytics and the effect of the Great Resignation. The following is an edited transcript of their conversation.

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Karen Roby: Today we're focusing on HR analytics. The Great Resignation is upon us. I have a feeling we're going to get tired of using that term and some other terms that have been used, but there's no doubt there are problems companies are having with keeping good talent. And we're in an interesting pinch right now because of COVID it seems, would you agree?

Kon Leong: Absolutely. There has been various terms attached to this phenomenon. People being cooped up for a long periods and then reexamining their life, their purpose and so forth. And that's resulted in quite a phenomenon for HR managers. They call it by varying terms the turnover contagion, the Great Resignation, the mass attrition, and so forth. Although some have actually gone the other way and said, "Maybe this is the great realization," trying to put a positive spin to it. At any rate, the economic loss and the impact on morale and of course, the succeeding domino effect is making a lot of executives sit up and pay attention.

It's not just a direct loss of an employee, but it's also the morale and impact the signaling or the empathy effect on the surrounding people who may be asking, "Why am I still here?" or perhaps a more practical issues such as more work for the remaining staff. All of this has tremendous impact on the enterprise, especially with regard to the cost of replacement, the recruiter phase, the interview time by management and the onboarding costs. It just adds up on and on. It would be a lot simpler to attack the issue at its source, which is how do we, A, detect such a movement to leave the company, and B, what can we do to actually retain the ones we really want to.

Karen Roby: And Kon, when we look at those people that are vulnerable or at risk for leaving, how do we pinpoint them?

Kon Leong: Actually in this day and age of the digital era, we talk a lot about digital transformation, the underlying advantage is that everything is captured in digital form somewhere or the other. We are 24/7 on the handset, we have laptops, we have all sorts of things, we're very connected. And as such, the connections generate a tremendous amount of digital work product that try to some might say and buried in that mass of information, there's a whole lot of information about where the people are, what are they thinking and feeling and so forth. So, this is actually an untapped source of managerial information that can be used to great effect. And that's, I think the emerging trend to look at this information that no one had ever really looked at twice before and finding that it's really a gold mine to use to manage the enterprise in a far better fashion.

Karen Roby: Kon, just kind of give us an example of what the data would look like, what would it show or say about a particular employee, again, who may be at risk for leaving?

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Kon Leong: For example, if you wanted to know who might be at risk of leaving, most of the time people don't just wake up one morning and say, "I'm quitting." Usually it takes the recruiters say, about a six-month process by which they re-examine where they are, where they're going and so forth. And in that six month period, we leave breadcrumbs all over the place in terms of disengagement, in terms of lag time between emails or messages, in terms of number of projects outstanding, in terms of even a number of dental and doctor appointments racking up. All of these are signals. And if you can figure out that, "Hey, we've got a dissatisfied employee or unfulfilled employee," then you can actually head them off at the pass and say, "OK, let's sit down and see what we can do to improve your work life." That's a whole lot more productive than trying to do damage control after they leave.

Karen Roby: And Kon, do you think some HR departments, just companies in general would be surprised to know about the technology that is available, that these techniques are out there?

Kon Leong: I think so. In fact, it actually goes down to a very core issue and sometimes when they bring it out it causes people to pause and think, if we can store every bit of human work product and you've accumulated over time, it is essentially your corporate memory that has huge implications. For example, institutional memory is critical to figure out a whole lot of managerial issues, including the strengths and weaknesses, where you're headed and even practical things like who knows what about what, and when. The implications are huge, and it's basically the flip side of what has been going on in enterprise IT. For the last 70, 80 years, we've been focusing on structured data, ERP data, SAP data. We've neglected the other side, which is the human side. And now this opens up a new era of IT, focused on the human resources. We're pretty excited about the implications.

Karen Roby: It sounds like it. All right, Kon, looking ahead here, how does HR analytics, how does it look different, say, a year or two years down the road?

Kon Leong: I think it is an absolute godsend and a necessity because the COVID, even post-COVID has completely changed the work environment. We won't be going back to where we were. So, in other words, a lot of your workforce will be out of sight and hopefully not out of mind, but how does one manage someone you can't see because we've been used to the close proximity, and herein lies the key to that using technology to keep all of the players engaged and productive: that is an absolute necessity. And whether we like it or not, it will play a central role.

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