HR Tech 2021 Series – HR Technology: Past, Present, and Future

Connect with Chris:

Connect with Dwight:

• 
• dwight.brown@salary.com

Connect with David:

• 
• 
• david.turetsky@salary.com

Resources:

• Deloitte
• HR Data Labs Season 2 Episode 24
• HR Data Labs Season 2 Episode 22

• “We have this opportunity to actually have the tech work for us and really stop working for the tech or [stop] making the tech the work.”
• “We did a really interesting study on the technology in [the digital workplace are], and one of the things that we were finding is … how do we leverage all of this data for true knowledge management, not just content management.”

David Turetsky: 0:02

Here’s an experiment for you. Take passionate experts in human resource technology. Invite cross industry experts from inside and outside HR. Mix in what’s happening in people analytics today. Give them the technology to connect, hit record, pour their discussions into a beaker, mix thoroughly. And voila, you get the HR data labs podcast, where we explore the impact of data and analytics to your business. We may get passionate and even irreverent, but count on each episode challenging and enhancing your understanding of the way people data can be used to solve real world problems. Now, here’s your host, David Turetsky. Hello, welcome to the HR data labs podcast. I’m your host, David Turetsky. Like always, we try and find people who are fascinating to talk to about the world of HR technology. I have today, two very good friends of mine, as always, we have Dwight Brown. And we have one of my true besties in life. Chris Havrilla, from Deloitte Consulting. First of all, I’m not only happy to have Chris on the podcast, I’m also happy that I can get to do this live. If you don’t know Chris Havrilla, I don’t know what you’re doing. You must be living under a rock somewhere. And I apologize if you are living under a rock somewhere. But Chris umbrella leads the HR sensing, sorry,

Chris Havrilla: 1:34

HR? Well, it’s actually technology, kind of Deloitte’s resident tech analyst in the space of human capital. So technology analytics that support work workforce workplace, so through research and advisory around that.

David Turetsky: 1:48

And this person is brilliant. And she’s done the work because I used to work with her at a former company, and she has the chops. And that’s why today what we’re going to be talking about is the past, present and future of HR technology. Chris, as you may remember, there’s one thing we have to do before we get to a top accolade. What’s one thing that no one knows about you?

Chris Havrilla: 2:11

Oh, my gosh, can I say last time?

David Turetsky: 2:14

That was last time.

Chris Havrilla: 2:15

That was last time. We need something like now? Yeah. I played water polo in college.

David Turetsky: 2:22

That’s the one you used last time.

Chris Havrilla: 2:23

Okay this is even better. So these are the two things right that most people find it surprising. But I actually was on a pitcrew when I was in high school and college.

David Turetsky: 2:35

And yeah. And you were doing timing, timing. And, you know, she told us these two things the last time.

Chris Havrilla: 2:42

No I did not tell you these two things. I just think you happen to be because we’re that good of friends. You happen to know that one podcast,

David Turetsky: 2:51

By the way, we only have 20 minutes on this one. So let’s let that slide.

Chris Havrilla: 2:54

Yeah, well let that slide.

David Turetsky: 2:55

So our topic for today is the trends in HR technology and Chris is very uniquely positioned to be able to talk to us about that. So let’s talk about the things that have happened in the past. HR technology was important this year, it was important last year, HR technology has been around for decades. Absolutely. And when I talk about trends in HR technology, there were lots of trends in the past, yes. What are some things that kind of reach out to you that things that we thought were the thing that was going to solve everything like employee engagement? What are the one things in HR technology that come to you as being lessons learned from the past?

Chris Havrilla: 3:38

You know, I think this is an easy one for me, because I think we’re still trying to solve for this a little bit, but we keep thinking the tech is the guide to solve the problem. But the the trend really has been that the Tech has become the work, right? So it has not been enabling the worker supporting the work. So, you know, I laughed when we hear people talking about kind of the robot apocalypse, and we’re gonna be working for the tech and I was like, we’ve been working for the tech pretty much since it’s came out here. And we’ve been feeding the beast, right, with just a ton of data, we automated a lot of manual processes, and we fed all this stuff and, and we’ve been maybe even data rich, but information poor and insights poor. And, and, and really, I think, you know, to bring it kind of into the present, is we have this opportunity to actually have the tech worked for us and and really stopped working for the tech or making the tech the work. But we you know, we keep adding tech into these tech stacks. We’ve got a new solution to a problem. And really, it’s just increased the complexity of the work. It has not made work better for people or people better at work. It has become the work. So I think the trend that I’m seeing now is that it’s always been possible for us to use tools in a different way to solve problems. people solve problems, not Tech, but, you know, we’d never got into a muscle set where we had the technology support what we do, or kind of unlock our potential, you know, we are seeing trends now that, you know, machines are coming into the workforce, as you know, for could come in as collaborators, or it could come in as substitute for transactional work, or we can start to use it as a collaborator even beyond augmentations. Right, but how do we bring them into the workforce and what they’re uniquely skilled at doing, and be a part of getting this work done. And I think that’s a trend that I’m seeing now. But we still have really highly complex tech stacks, that we’re all trying to navigate. And so some of the trends that I’m seeing into the future, are things like digital workplaces that kind of lay on top of all this tech, as we can kind of plug and play and simplify and consolidate and rationalize, do all the things that we need to do, but not make that on the part of the workers who are just trying to get work done.

David Turetsky: 6:01

So I think if you go down to the floor, one of the things that kind of jumps out at you, on almost every booth is like 202, word phrase, artificial intelligence, everyone’s using it to talk about what’s something unique they’re doing. And you talk about whether it’s the work trying to make us smarter, or better, or us trying to make the work smarter or better, right, because we’re feeding the beast, right, there exists, but we’ve talked about in the past is artificial intelligence should be able to help us with, as you say, those manual tasks that we’ve had to repeat over and over again, like fixing data. That makes our information, our data into information. Why hasn’t anybody? Or why haven’t we as HR thought, but it’s talking to our thought leaders? Why isn’t there a thought to basically trying to solve those problems first, to allow for AI to kind of fix the data and then move on and help us with things like that, instead of all the sexy stuff down there?

Chris Havrilla: 7:01

Right. You know, and I think it’s because people inherently don’t understand that the, it’s the data itself, that is driving these technologies, right? And so they’re so focused on this, you know, that quote, solution that it is that if we just implement this right, then then we’ll have all that we don’t, we can bypass this other stuff. Right? That seems hard, and unseemly, and but it’s actually what drives those algorithms. Unless somebody writes the algorithm for you, and then you’re tweaking it, you know, however you use it. But the, the real power is the fact that this technology can go through all of this data at speeds and capacities. And in that we could never dream of and find the patterns and trends and insights and things, recommendations and guidance that we might not see. Because we certainly aren’t going to take the time to go through it, it can’t possibly, but if that data doesn’t, and you know you can’t let perfect be the enemy of good here, right? But if you if you at least, are to focus on those things, and get better and better and better. And, and having data governance and accountability, right? For the people that are still putting, you know, giving information in there, and holding them accountable to doing it right. You know, because it’s important, and it’ll help make this technology work with us better, are still collaborators, we can bring machines into the workforce. But if you’re not giving them the right rules, or guidance, or training or auditing or managing or feedback, just like we would a humans, right, then how are they going to get any better when they’re actually much more explicit? In what they do. So, you know, it’s all it’s always been about, how do we make our workers better? Right? How do we unlock their potential? And that’s how we unlock the potential things like AI. Right.

Dwight Brown: 8:58

One of the things that you touched on that really resonates with me, the the idea of complexity. Yeah, you know, I think the old line has always been when we’re selling a system and and asking for the funding for that system, inherently, everybody goes to load, it can save us this much…

Chris Havrilla: 9:16

right, cost.

David Turetsky: 9:17

And the CFO,

Dwight Brown: 9:19

We haven’t altered the value equation, what I hear you saying is, we need to alter the way that we look at the value equation, it’s not really that we’re trying to save cost.

Chris Havrilla: 9:29

Right, that’s substitution. Right? That’s, that’s down here at the bottom of what this can do, right. But if we’re gonna just talk costs, and not meaning and value, and all of those three things, right, we’re, or we’re hindering ourselves for staying down here at the bottom of the quadrant, right. You know, but and that’s where substitution is. But when we really start to, you know, soar in into, you know, there’s efficiency, you know, go up the scale right up to actual…this is the impact that we’re making. It’s really how we bridge across cost, meaning and value to get to that, right. So when we are truly using machines as collaborators, we’ve kind of nicked that, that cost me and value Triumvirate that needs to happen. You know, we talk a lot about in human centered design and design thinking, which is the technology to solve complex problems, which is really, like, everybody’s always like, what are the skills HR people need these days? I’m like, you know, they if they could just learn, you know, human centered design design thinking, how do we solve complex business problems that don’t have necessarily an answer, but we have to find an answer to facilitate that. Data literacy, the ability to tell story with data, you know, those are really the skills that that people need to kind of start to do that. But we talk about, you know, in human centered design, you’re always trying to think about, okay, what’s desirable and that’s the world, right? We want all the magic and all this, but it’s also what’s actually feasible, what can we actually build? Right? What can we actually do? And what’s viable? Which is, what can we actually produce profitably, or such that we extract value, right to, you know, versus the cost that we’re doing, right, but not necessarily like this pure kind of ROI. But we’ll never get to a point where we are truly unlocking human potential, as long as we just focus on cost, that’s just substitution. It’s not augmentation. It’s not, you know, getting to that, you know, collaboration standpoint. And that’s where we’re really unlocking human potential and getting away from kind of input process output. And here’s our, here’s our steps and activities. And here’s the output that happens, which really isn’t even happening in the first place, why we have really cruddy data, right? Because this step process is not actually what might be happening. So the shortcuts in real work arounds, you know, that don’t necessarily get reflected in those systems. Right? But if we can get to a point where it’s really about who’s asking the best questions, because when we don’t have answers, in a world of no certainty, you just have probability, asking the right questions is really important. And understanding what outcomes you’re trying to get to and in between those questions and outcomes is flow, right? And it’s not necessarily, you know, it’s, it’s more fluid. It’s, you know, it can move and shift around. But it’s how we take actions and make decisions. And that’s what the tech and the data can do for us is help us do that. Because that may be different today than it is next week to get to those same outcomes.

David Turetsky: 12:44

Like what you hear so far, make sure you never miss a show by clicking the subscribe button. Now, this podcast is made possible by Turetsky consulting and listeners like you. Thank you for your support. Now, back to the show. Have you seen any industry or examples of companies that have been doing it better, that have learned lessons from the past and are targeting the future of employee engagement and empowerment and getting the data to actually help them learn?

Chris Havrilla: 13:13

Yeah, I mean, there are definitely a lot of cases, you know, would I say, on a maturity curve, you know, they’re way out there. But I do think people are really starting to understand that if this data that we capture, you know, we can start to do it in ways we haven’t done before, and are tinkering, on the edges of things like that. And some of the most exciting tech I’m seeing right now is in the digital workplace area. And even you know, we did a really interesting study on the technology in that space. And, and one of the things that we were finding is, even with things like AI, that even the vendors are talking in a different way, they’re marketing in a different way, instead of all the, you know, auto magical stuff, you know, they’re talking about it in a way, it’s like, how can we make this easier for people to find the answers. Regardless of the system, regardless of anything, you know, how do we leverage all of this data for True Knowledge Management, not just content management, you know, so that people can come in and out? And that the knowledge is, is there? Right? So we’re seeing different ways. And it could be around community, it could be around communication, it could be around workflow or task management, so people are using it and tinkering at the edges and then seeing, wow, we, you know, we’ve kind of laid this engagement platform, and all the ways that we can work with it on top of all this tech to extract value out of it, right. So that it’s not just, you know, okay, here’s more steps I’ve got to take to get to the end, and they’re tinkering on the edges of that and making work easier and better for people to make those decisions and take that action and then kind of it’s almost like land and expand, right? It’s like oh, you know, we have proof of concept here. We can do this. You Wow, maybe we can start taking this out here out here out of your out.

David Turetsky: 15:02

And that’s what’s exciting to me. Once you find good use cases, then those synapses get made in people’s minds, the connections get made. Now we can do this, Hey, can we do back? Can we try it?

Chris Havrilla: 15:13

And that’s when technology is starting to unlock human potential, because it’s like, oh, wait a minute, because somebody’s not telling me how to do it. I’m looking at that going, I could do that to do this. And that is the future of work, that’s flow. That’s flow, when we remove ourselves at this, you know, executive levels of telling people how to do everything. Tell them what to do, you know, what has to be done? Right? What’s the right? Why. So they’re connected to the work and get out of the way of the house? Right? Let them you know, find kind of like, use this technology to make decisions to take action.

David Turetsky: 15:52

But it’s that empowerment, that has always been almost a tug away from management and executives. Because there’s power

Chris Havrilla: 16:00

There’s power and control is one of our control. We talk a lot about the future of work, but not as much about the future of leadership and management, and the new role of what that looks like because that is a loss of power and control that is not comfortable for a lot of people, but you’re gonna see a lot more coming out of, you know some of the work I’m doing around that. So we can, what’s the other part of the equation and unlocking human potential is our role as a manager and a leader is to remove things out of their way so that they can do it. Do you have the information? Do you have the tools you need? What’s in your way? What challenges can help you ask the right questions? And exactly.

David Turetsky: 16:52

Chris, I know you have to run again. Thank you so much. We’d love you. You’re always welcome in the HR Data Labs podcast. Thank you do I thank you very much.

Dwight Brown: 17:02

Thank you. And thank you, Chris for being here.

David Turetsky: 17:05

Great. So thank you for listening. And if you enjoy it, please look at some of the other podcasts especially the one Chris Havrilla did before. It was brilliant. Brilliant. Please subscribe and tell your friends. And please stay tuned for our other HR Data Labs coming up at the HR Tech conference and stay safe. Take care. Bye.

Announcer: 17:25

That was HR data labs, please visit Turetsky consulting.com forward slash podcast to review the show. Add comments about this episode, or add new ideas about upcoming shows you’d like to hear. Feel free to be creative. But please be nice. Thank you for joining us this week on the HR data labs podcast and stay tuned for our next episode. Stay safe.