Greg Miller’s career has been focused on one of his greatest passions—tackling significant socioeconomic challenges like the digital skills gap. After starting his career at Oracle, Greg worked in senior leadership roles at leading tech companies such as PeopleSoft and, most recently, SAP where he was Chief Operating Officer. After his tenure at SAP, he raised social venture capital to enable youth STEM innovation and grow the next generation of digital skills in Australia.
In 2017, Greg co-founded Faethm—an AI-powered SaaS platform that provides organizations with information on how automation will impact every job. In September 2021, Faethm was acquired by British workforce education giant, Pearson, and Greg became the SVP Customer, Workforce Skills at Pearson.
In this episode, Greg talks about socially responsible automation and how implementing a people-first strategy can protect social equity in the age of AI.
[0:00 - 4:11] Introduction
[5:41 - 8:18] What is socially responsible automation?
[8:30 - 21:09] How do emerging technologies disproportionately impact certain workers and job roles?
[21:18 - 27:00] How can HR help business leaders make more socially responsible decision when tasked with introducing new technologies?
[27:09 - 31:08] Final Thoughts & Closing
Connect with Greg Miller:
Connect with Dwight:
Connect with David:
Announcer 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.
David Turetsky 0:46
Hello, and welcome to the HR Data Labs podcast. I'm your host, David Turetsky. Like always, we try and find really fascinating people to talk to inside and outside the world of human resources to bring you the latest on what's happening in HR data, analytics and technology. Today, we have with us Greg Miller, who's the SVP of customer at Pearson Workforce Skills, and the co founder of Feathm. Hey, Greg, how you doing?
Greg Miller 1:11
Good, David. Thanks. Good to be here.
David Turetsky 1:13
Goot to have you. And as always, we have our trusted co host and friend, and baritone Dwight Brown. Hey, Dwight.
Dwight Brown 1:21
Hey, David, how you doing? Greg, good to have you here.
Greg Miller 1:26
Thanks. It's not every day I get called fascinating. So I do appreciate it.
David Turetsky 1:29
Well, you are and why don't you tell us a little bit about your background? Because then everybody will think you're as fascinating as I do.
Greg Miller 1:37
So yeah, I grew up in the US, but about 21 years ago, left California and came to Australia where I have lived the last 21 years and have loved every minute of it, been in the IT industry, I guess you could say pretty much my whole career bunch of multinationals, but finally found my happy place and left that world to start up our own tech business about five years ago here in Sydney, but took it around the world and really, what I mean, when I say I found my happy place, I really mean it's been a great run. Great.
David Turetsky 2:10
So tell us what is Feathm?
Greg Miller 2:13
So Feathm is an AI platform. And I guess we hear that a lot these days. But yeah, maybe the realities of that is not all AI is AI, but our team, thank goodness, not me, our team of data scientists have done the real work and created something unique and true deep learning and machine learning that goes on in this platform, which has been built to look into the future, understand, hey, in the next three years, five years, or longer for governments, but understand what the impact of external forces are going to be on, that might be AI, what's that going to do to my job that might be robotics, might be climate change, you name it, but it's been built to look in the future understand what impacts so that I can then as a business leader, or government leader take action. That's that's what it's all about. So we can move to that stage of action and preparing people for that future.
David Turetsky 3:03
Outstanding. So Greg, like we asked most people, or actually all of our guests, what's one fun thing that no one knows about you?
Greg Miller 3:13
Right on, obviously, you'd let me know this was coming and I had thought would'd be a work thing or a personal thing. But I've opted for a personal thing that truly no one knows. Many years ago, and I need to preface this but in case my mother watches this, I don't know if she really cares about what I do, but just in case my mother watches this. I apologize now, Linda, but this is where she would call me Gregory not Greg because I'd be in trouble. But Baba Murphy, who was my next door neighbor and who I had a bit of a crush on, she had a convertible bug. And one day a hole showed up in that convertible. And no one knew who did it. Or why or how. It was me. I mean, this is I was like 13
David Turetsky 3:58
Oh, okay, I was thinking maybe this was a couple of years ago. Okay.
Greg Miller 4:04
All right. Yeah, I was like 13 she was 18, one of those things so but in a moment of anger I threw a rock the rock went through the convertible and I never owned up to it until this particular moment in time.
David Turetsky 4:17
Now of course she could be listening.
Greg Miller 4:20
That seems highly unlikely. My mom, even my mom will be pretty unlikely.
Dwight Brown 4:26
Wow, well, so that that's how you profess your love?
Greg Miller 4:32
I was 13 Don't ask me why this you know, just know that
Dwight Brown 4:37
You're like I've got the crush for you. I'm gonna put a hole in your convertible.
David Turetsky 4:42
You know there does have attention seeking behavior written all over it.
Greg Miller 4:49
I'm not sure I've gotten any better over the last forty years.
David Turetsky 4:52
And I'm not gonna give you relationship advice either dude. So sorry.
Greg Miller 4:57
Good, good.
David Turetsky 4:58
But if we do hear that Bubba got in touch with you, it would be really great to follow up the podcast with another another....
Greg Miller 5:05
100%, when when we get to Dwight and David's relationship advice, we'll come back to Bubba.
David Turetsky 5:10
That's the next podcast we're gonna do. Well, today, we have a really awesome and fascinating topic, which I think really kind of speaks to where we would, do need those platforms like Feathm to tell us what will be coming, which is socially responsible automation, and implementing a people first strategy to protect Social Equity in the age of AI.
So Greg, I have to ask, what is it, that so, what do you mean by socially responsible automation?
Greg Miller 5:47
Yeah, it's an important opening question, because it's not a common thing out there. It's something that we've honed, I guess, as a topic over the last five years of doing this, and meeting with business leaders, government leaders on the topic. And, yeah, I guess a way to think of it is, if I'm going to build a strategy that's socially responsible, and when it comes to automation, then I'm going to plan and understand that for, to implement this type of technology, want to understand what the impact on my people will be? And if I know that, then I can organize myself to say, well, over that two or three year horizon of implementing this big digital transformation, let's call it, rather than firing those people are impacted by these technologies and using that as my cost saving yay, and displacing these workers. No, no, I'm gonna actually say, Hey, I have a bunch of future jobs, I need to add to my organization. I've got two years, three years maybe, to get these folks reskilled and upskilled, to go fill those future jobs. So that's, that's really my strategy, I should see it coming, prepare for and make sure my responsibility, I suppose to as an employer is to keep my people working. Over the course of his time, we've seen many companies who are simply firing until the folks that technology displaces and not having this strategy. But one of my favorite moments of this journey was actually from Ikea, when they said to us, our strategy is to keep 85% of our employees employable. And I was like, that was the opening gambit to their HR Strategic Workforce Planning Initiative. I was like, that's incredible. Like, that's such a great message to your people and to society, I think as a whole.
David Turetsky 7:30
It is, and one might say, Well, why not the 100. But it's just shooting for 85 is is actually really pretty good, isn't it?
Greg Miller 7:39
Definitely. And, and like, every No, no industry is alive, I guess. So some industries are going to see much higher rates of displacement. And therefore, I would agree that I would say that there's no way you can find in a bank, a home for everyone that's being displaced. So you need to say use the same strategy and thinking to say, well, those folks who are leaving my bank, I'm gonna give them the same opportunity to be reskilled and upskilled into maybe another industry, maybe in healthcare or something adjacent. So but that's about getting that real data lead view to know where I can move them next, that's the best and better opportunity for them to keep them in the workforce.
Announcer 8:19
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David Turetsky 8:30
So that brings up another question, which is, if we're talking about these emerging technologies, which jobs and which roles happen to be disproportionately impacted, typically within an organization?
Greg Miller 8:43
Yeah, again, I'd say, first of all, this is no industry is alike and you're going to see different levels and different jobs, your general rule that we would see in the data and what it tells us well, those jobs with routine types of tasks and mundane types of tasks, repetitive tasks, obviously, they're the kind of the first to be impacted. But that is changing dramatically, because technology is advancing so quickly, you know, we had interesting scenario where data science was one of the key new jobs as we all talked about, you know, move into data science, how do we give you pathways? And then what's what pops up when that huge demand for data science exists, but there's a low supply, what happens? The next hot startup is hay I've created a way to automate data science. We were telling all these people to go become data scientists, you know, now, right? So, so it's a constantly evolving and changing kind of landscape of tech. But I think, you know, what we learned through this process again, was all the media tells us about automation. And they're missing two significant ramifications to this one is augmentation. And that this is not all about job displacement, you know, Are we we need to augment nurses, for example, with technology so they can become the power to when it comes to patient care. Alright, so that is a real positive, creates capacity within any workforce, but also addition. So what new jobs do I need to add in this future state as I continue, so that, again, is a real positive, but we don't often see or hear about those two positive ramifications. We just hear oh, my God, you know, the robots are taking our jobs. And it's the automation. And you got to bring in all that.
David Turetsky 10:29
Yeah, I don't know if you had heard, but especially around here, we found it very difficult to hire like servers. And so some organization some, well, some restaurants were actually hiring and employing robots to deliver food to tables, in order so that the waitstaff could take on the more complex roles, and not worry about the serving aspects of the, you know, the food, food service, but also being able to then help be able to, you know, get get the more, as I said, more complex roles completed. And there were some that were highlighted on television. And it was remarkable, because you do think about, okay, well, this is a really hard job for for humans, probably not too hard for a robot, but it's a rather demanding job. So what how do you service that robot? How do you keep it, you know, charged? How do you keep it, it's also a very messy role, too. How do you keep it clean? And how do you keep it? Well, oiled?
Greg Miller 11:28
Yes. You know, just exactly what you've just described, well, that creates new jobs. For those some of those people who have to do that work, or it's an advanced type of work as well, for more highly skilled or challenged has always been great. How do I prepare the server that was server and now to give them opportunities for some of these new jobs that maybe require some stem related skills that they don't have? And am I going to invest in the training that's needed? Or am I going to fire that role and go hire these folks in robotics, which is our historical way. And, you know, for all HR people out there, don't take it the wrong way. But for decades, this is how we operate HR. This was our processes that we had in place. And and I think another maybe lesson we've learned along this journey that we got to blow those up. We got to erase the last three decades of that and think in a new paradigm as we go forward.
David Turetsky 12:20
Well, I think that brings up another question, which is the role of data, and how we can use data to help make better decisions around these emerging areas, and enable people to be able to harness the data to make better decisions. I would imagine there's some upskilling needed to be done there too, especially in HR.
Greg Miller 12:38
Oh, you bet. I think the number one question I get when I present to folks in HR is like, can you pull me up in in Feathm? Can you show me what's happening to my job. It is a very human show response to this topic, I think, you know, and maybe I've had experience in my own life, or my parents, whomever. So I think what about me, I think what about my kids? So yes, I think there is a transformative, of course, what I tell everyone in HR, and if you're listening out there, I say Don't fret, we don't have enough of you to deal with the people ramifications of this topic. We actually see more opportunity for the HR function. Yes, we need to upskill, isn't about tech displacing but upskill HR, we need more data capability. Now, I don't need you to be able to code or you know, create AI. But hey, HR, I do need you to understand those technologies and how to use them and apply them what the impacts are going to be on your people so you can be more effective in your job. So yes, there is a transformation of the HR function. We've seen an explosion of, you know, people analytics teams, within HR, some organizations still sit in the CAOs office, others moved it out. But that's been a yeah, when I look at like, say, our customers and who's more successful than others, it's those who have made that decision, built that team and then are taking their rather static HR data sitting in their HR system, actually turning it into dynamic, useful, insightful information to drive action. So yeah, I think data is the ultimate, maybe equalizer, right? We can use it to kind of propel HR to the senior leadership table, but also use it to remove biases that are naturally created.
David Turetsky 14:17
We've seen a lot of reticence, Greg because HR people tend to be more of the support people and have done a lot more administrative roles rather than being more advanced in the mathematics and statistics. And I like it between the difference between an HR generalist and a comp person where a calm person has typically had a lot of years of doing statistical analysis, especially around pay equity. Whereas an HR generalist has had to deal with a lot of management issues, a lot of support issues that kind of keep them out of the statistical realm. And I think that that's the group that probably needs it more, right?
Greg Miller 14:54
Yes, although, I find and again, if we pull this back to the data much of the gaps that we're seeing are in the soft skills, what we've called soft skills, you know, for a long time, the ability to tell the story interpret the data, what does it mean? How do I take action. And that's, that is a skill in itself, and sometimes a difficult one. So, but you look at this data and say, well, actually, people in HR tend to have a good kind of allocation of those types of skills. They're not far away from where we need to be on those soft skills. So that's a that's a bonus. Now where they have gaps in data and digital literacies. And again, reinforcing. You remember, this as well as I you know, what, five years ago, though the world every MP, and every senator stood on a podium and said, We're going to teach everyone to code. You know, like that was the silver bullet is going to solve all our problems, right? Was BS, right? That would happen? And it's not the silver bullet. So now we go, actually, no, you just need to understand these things. So yes, there's some STEM skills you need. But it's not to code. It's not to write AI, to understand the AI, how does it impact work? One of my favorite stories, I got too many favorite stories, but was a big bank we worked with and their CAO case, HR said, Hey, I'm implementing voice AI, my call center agents, you know, are gonna see some displacements and disruption. So we wanted to look into that. But she said, I also need to hire a new role. It's a conversation engineer. And HR said, What the heck is that? I've never heard that we don't have that job in my catalog. What are you talking about? No problem, you know, CAO says, I get it. Well, what they need to be able to do is, you know, they need to have creative writing skills. So creativity is critical. But they also need some STEM skills, they need to understand AI and how it works and how it would impact a call center agent. And again, HR is going, What are you talking about? Where do I find those because I've never had to go and source for that. So back to this HR having to kind of blow up the way they've done things to come up with a new horizon, because this job effectively was having to understand the call center agents job. So they can come out of that job, which is good. But then they have to learn tech well enough so they can teach the AI how to talk to us. So when I call that, you know, call center, the the AI knows how to pause appropriately, and respond to me in a way that I'm going to like and understand. So that's a new job that didn't exist before. Now, unfortunately, you don't need, you know, 1000 of those where you might have 1000, your call center. So there's our dilemma again, and we need to find a path for those call center workers to other jobs, maybe other industries.
David Turetsky 17:39
I can liken that. Or it seems like that was very similar to when the internet was blowing up. And we needed a new type of role for being able to deal with new things on the internet. Like, for example, we needed new people who knew how to derive internet advertising, which is very different than the world of advertising in newspapers or on television.
Dwight Brown 18:03
I think of the, you know, one of the things that being in a leadership role I learned the hard way over the years was that whenever I was looking to, to buy something, or get something that would help with our help with our processes, early on in my career, I started saying okay, you we can save this many FTE if we implement this system. And what I what I learned very quickly was that there was no FTE savings, because there was always something else to be done. And there was always a new skill set that was needed in order to backfill what we what we were ultimately automating, per se. And I think that's, you know, you look at this, since the industrial revolution started, we've been trying to replace people with automation. And yeah, we've automated a lot of tasks, like you said at the beginning, Greg talking about some of the routine tasks, the repetitive tasks, and yep, we've automated that. But as you pointed out, we continue to need new skill sets that we that we build. And so basically, we're shifting is is what ultimately ends up happening. And it's a matter of how strategic you are about making those shifts.
Greg Miller 19:23
Yeah, and I think that some of these decisions flow on social ramifications, just in San Diego, and a couple weeks ago, we're talking about the energy transition. And one of the ramifications as we shift to clean and green energy is that we effectively shut down a lot of those brown energy sources and that displaces masses of workers, but they tend to be in like, you know, I mean, here in Australia or I mean, we have talking to the next Governor of Colorado at the time and you know, it's in very remote parts of The State, though if two or 3000, workers suddenly lose their job in a remote part of your state, you are in real strife, right? And so we can come back full circle to your question about data and say, Well, if I can start with this at a data layer and a data conversation to say that's coming, what do we do? How do we re deploy those workers, I can then drive a policy change that says, You know what, I'm not going to be able to redeploy them all in that geographic location, I need to offer a kind of mobility package for some folks, and help them move to either another part of my state or often what we're finding is, you know, if that was Colorado, and Texas is going big in hydrogen and wind and solar, hey, let's help them redeploy into and maybe work with the state of Texas, who, by the way, is looking for skills to do that, you know, as they look to mobilize, and Colorado looks to shut down brown, hey, great, let's give him that pathway. And either at a state level, or heaven forbid, a federal level to help that happen, because we know it's coming. Right? We see it right. Don't wait for it to happen. We know it's coming, use the data to tell us that and get the decisions made now to prepare for that future.
David Turetsky 21:18
So that kind of brings us to question three, because I think you're onto something right there, which is, how can HR use those examples to influence business leaders, and actually help them make what could be extremely socially responsible, good decisions for the company good decisions for their employees, when you're introducing some kind of new technology?
Greg Miller 21:38
Yeah, I spent a lot of time thinking about this talking about this. And I think one thing we're promoting a lot now is that this is it needs to be because it's not a board, kind of governed, managed item. You know, not long ago, no board talked about diversity, equity inclusion. Not long ago, no board talked about carbon footprint, right, their sustainability from that perspective. But now they are. And I think this has that level of impact. It was actually the chair of the Australian Stock Exchange, Yasmin Allen, who, who first raised this with me, and she was on our board at Feathm. And that was amazing to have someone of her caliber on our board. But she was the first to say, Hey, I'm meet with other board members of some of the biggest companies, not just in Australia, but in the world on a regular basis. And I can tell you, they don't understand this issue. They don't see it coming. They don't have visibility to it, but they need to because the people ramifications, the societal ramifications are a mess. So yeah, she was kind of the first that that, put that in my my mind. So that got me thinking about how do we do that? And back to your question, well, I think number one, we need to arm HR with meaningful data that elevates them and with not every HR leader at the executive table has the same voice, right? Some right, have an equal voice, some get handed the action, rather than coming to the table with the action. So this is an opportunity to empower the Chief People Officer Leader at that Expo to be there with a point of view, I understand the impact of tech and these other forces on our people. And we need to act and take action to resolve this now. One way we can do that is by the CAO and the CHRO actually, you know, meeting, talking, planning, aligning their strategies, which is not a common thing. This is not surmising here. We have seen this firsthand for five and a half years plus, maybe the 10 years prior in my career and other tech companies. It's just not a common connection point. But I feel like data can bring be the bridge that brings those two together to say, Oh, by tech strategy, material strategy actually are colliding here. You know, how do I prepare for these social ramifications or things like gender diversity? You know, I mean, the CAO's roadmap and every bank in America and the world is going to destroy diversity, equity inclusion. We've got the data, we're seeing it firsthand, but we're not acting upon that to say, well, let's get those minority groups that are disproportionately being automated and get them into the reskilling programs for future jobs first, to make sure we don't blow up that that key....
David Turetsky 24:24
Greg, why aren't we talking about this with CHROs in a more proactive stance then, so that it's not after an action happens or after the automation happens, but either prior to and make it a policy or make it something that's done in conjunction whether it's through strategic workforce planning, or during the investment process, when you're bringing in that new technology that at that same time, you're also looking at those socially responsible ways of being able to reskill and upskill
Greg Miller 24:57
I wish I knew, the million dollar question.
Dwight Brown 25:04
That crystal ball. Yeah,
Greg Miller 25:07
That would be great for my business. If I could figure that out. I mean, look, fair enough, obviously, I'm, I'm kind of, maybe I don't know if I'm taking a negative view of this. I'm trying to create urgency here, because we don't see enough of the good stuff. But absolutely, there are good things happening. I mentioned IKEA, Zurich Insurance was another great example where they came out publicly and said, Yes, we are going to automate. Yes, that's going to impact people. But here's the million pound investment we're putting aside for the our team in the UK that's being impacted to reskill and upskill them and keep them employable. That was like, you know, they went out. Not only were they doing it, but they went out and put a information agent article out telling people they were doing it, which is tremendous, because what a great recruiting tool. Do you want to go work for Zurich? You know, who takes care of that people like that? Or do you want to go work for this company that just front page news is automation agenda displaces 3000 workers? Yeah, no. So I think there are definitely good examples of it. It's still unfortunately, seemingly rare, where you see those stories versus the front page news of jobs being lost because of automation strategy. So but there are there are definitely good examples of it. I mean, Rio Tinto is another great example, global mining companies, you go to a mine site, and it's like, Oh, crap, you know, what happened? Was he Well, they, they actually say, hey, we employ more people now than we did before we automated, they're just not here. You know, they're in our ops center in the city somewhere. So wow, that's a better life, is it not for those very those workers if they provide them the skilling to get those other jobs? So there are definitely good examples. I don't feel like it's fast enough, which is why, you know, we espouse that this become a board issue, that then has to be driven down into the organizations and they are made aware, when the CAO is about to displace workers and go hang on, have we not connected that to a people strategy and reskilling and upskilling plan?
David Turetsky 27:09
So Greg, we've now talked about socially responsible automation and how to implement a people first strategy. And we also know what it is, because it's such a new thing. It's something that we hadn't heard of before. So thank you for that. We've also talked about what is socially responsible automation, in terms of what technologies are actually displacing, and who, what workforce is disproportionately being displaced. And then we talked about some examples of how we can get in front of this and how HR can use data to be in front of it. What else did we not cover? What else would you like to close with?
Greg Miller 27:48
One of the maybe misconceptions in this whole topic, you know, whether it's the future of work, or however you tag it, the fourth industrial revolution is, is sometimes it's a bit big for organizations and fit for HR, you know, that this issue is too big, and how do I start, and so you know, a message we were constantly bringing is, number one, if you can get the data, you need to make the decisions, you can start small, you know, take take that first action, that's the important part of this, don't feel like you're gonna have to solve this thing, because it's such a new way of doing HR in every realm ongoing, because this Tech Impacts not going to just stop or it suddenly done is going to keep evolving. So think of it as a new way of doing recruiting new way of doing development plans, l&d strategic workforce planning, you know, so that's one thing. The other is it's not the future. This is yesterday. So, you know, sometimes we say it's now whatever, but it's been going on now for a year. So you got to act now. The next senator is not going to solve this, the next CEO is going to solve this. Yeah, as much as you might like that to be the case. It's you, you're the team coming to save us, right? So you've got to act immediately. If you're not already on that path. And then go, you know, one of the last big lessons we've learned, you know, CHROs are often saying to me, how do I get the business case approved for this? And it's not again, it's, it's not a CAOs are good at buying stuff. Yeah. CHROs aro not always. So you know, learning how to get the business case approved. And, you know, that comes to tying these people issues to the business strategy. Again, not a common activity. But, you know, I had the chief caregiver officer for the head of HR for Cleveland Clinic say to me, Well, my number one objective is to grow revenues. I said, That's strange. I don't hear that often from HR and they said, We, here's the deal to grow revenues, I need to open up more centers, and hospitals. To do that I need more nurses, only to get more nurses when kids aren't going to get their nursing credential. You need to bring in technology to augment nurses and make nurses the power too then I can grow revenue. Yeah. nailed that. There you go. Tell every CHRO that story connects your people planning to your business strategy. And you'll get that that approval
David Turetsky 30:06
Drop the mic, Greg, you can walk out on that one right there. Greg, thank you so much. I can truly tell you this is one podcast where I've learned a tremendous amount in a very short period of time. So thank you very much.
Greg Miller 30:20
You bet now, it's really good to speak with you both.
David Turetsky 30:23
Dwight, thank you very much.
Dwight Brown 30:24
Thanks, David. Thanks so much for being with us, Greg. It's been awesome.
Greg Miller 30:28
You bet.
David Turetsky 30:29
Thank you very much for listening. And if you found value in this, please hit subscribe. And if you know somebody who might like the episode, please send it their way. Thank you very much. Take care and please stay safe.
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