Filip Popov Plavsic (00:01)
Hello, everyone, and welcome to another episode of Espresso 4.0. Today, we have Michael Carroll, and it is a very big pleasure to have him on the episode. Mike, welcome to Espresso 4.0. Why don't you tell a little bit to the audience about who you are and what your background is?
Michael Carroll (00:20)
So, I'm the head of innovation for the operations group at Georgia-Pacific. I came to that organization somewhere around 15 years ago after having been retired and done a lot of other things. And so, we started in this effort to try to transform the company, which is a pulp and paper forest products, consumer products company, into the kind of this way of trying to be something different for the future, what we were making wouldn't change. Still, how we got that done, we believe, would change a lot. So, we saw a lot of demographic changes happening in the future. We saw technology changing the way we thought we would get that done, and we're just trying to figure it out. So, I came in to help us think about that, and we got a wonderful organization that helps pull that stuff off.
Filip Popov Plavsic (01:17)
Well, I did not know that they actually pulled you out of retirement. You tried to get out, but they pulled you back in.
Michael Carroll (01:23)
Yes, I had a good friend that called me and he made me an offer I couldn't refuse.
Filip Popov Plavsic (01:28)
There we go, okay, another reference. Just to have a question. Okay, so having said that can you describe your journey into the world of Industry 4.0? What initially attracted you to the intersection of manufacturing and digital transformation?
Michael Carroll (01:44)
I think what initially attracted us was not knowing kind of what was in store for us. And we kept asking the question, how do you go be more competitive in a world that you know is changing faster than the ability for you to change yourself? So what would you have to be like? And it's kind of this future-solving mentality where you say, if you have a future, right? What would have to be true for you to be more competitive in that future? And then you solve for that by saying, what am I in control of for these things that have to be true? Everything else that you're not in control of just kind of drops out as not being a priority, which is different from the way we solve an analytical problem; we typically look at the symptoms in evidence.
Filip Popov Plavsic (02:42)
Yeah.
Michael Carroll (02:42)
Right? And then what we do is we try and simplify that and hope that that gives us something we can go work on. But this future solving mentality that you try and use is you actually try and solve it by what you're in control of relative to what it is you try and be in the future. And what it looked like was that for technology, what we've been doing, because from 2010 on, what you begin to see was productivity in manufacturing had actually prior to that came up, but it had plateaued in 2010, and when you look at it it really started to go slightly negative and the question was what made that true? Well, we piled a lot of technology on, and it appeared that the technology maybe didn't help. Why would that be true except for COVID?
Filip Popov Plavsic (03:26)
Yeah.
Michael Carroll (03:38)
The interesting thing about COVID-19 is what started to give us some answers was that when COVID-19 hit, the one thing that every manufacturer did was it turned off all the badges, except for the people that had to be in the facilities. Productivity for everybody went up at the same time that more people were coming out of the system. So in 2010, what I didn't say that I should have said was in 2010, for the first time in history, attrition rates started to climb from about 16 and a half percent to about 25 percent, which was that demographic change we were all experiencing. And so everybody blamed it on knowledge loss. Right? So, we piled technology in to try and take care of knowledge loss. And that was the Industry 4.0 thing. Let's put technology in to help make us more effective. Right? And so, you would think that, that when more people came out in 20 that more people started retiring in 20 due to COVID that, that productivity would have went down. But that's not what happened. Productivity went up. And so, you had a spike, and then it started to come back down again. The question was, why was that true? And it turns out that it was focus that makes you more productive. So, this led us to this idea that maybe the way we've been applying technology has actually been additive and reduced focus rather than being complementary. And that was the eureka. The eureka was that you know, maybe let's go back and ask ourselves, have we been creating additive sickness in the application of technology? Technology has features that you can use to try and create a benefit that you want to shape a better outcome. And so, when maybe we've been piling technology in that's been reducing the focus of folks rather than complementing and increasing the focus on what it is they need to achieve. That was a watershed moment. It was a watershed moment that the approach to industry 4.0 had been about technology, not about focus and improving focus on what needs to get done. So, when we come back to this conversation about what it was really all about, we are probably not quite working on the problem the right way, right?
Filip Popov Plavsic (05:54)
Yeah.
Michael Carroll (06:05)
Which is a maturity of understanding that you need to come to by asking better questions.
Filip Popov Plavsic (06:11)
So, I do have a question. I think what you're saying is that technology was coming out on the market that is promising all these benefits and whatnot. And industrials were piling more and more solutions, ERP, MES, CRM, blah, blah, blah, this and that. Instead of utilizing them well, they happened to have ended up with a multitude of screens, and most of their bandwidth was then focused on navigating through all of those as opposed to focusing on the things that they're supposed to focus on. I think they used the correct perfect word for that is the focus or lack thereof. So, what are the steps companies should take to build better focus, to find their way throughout this, to the forest, to shed? I suppose some of those technologies that were piled on were superfluous, perhaps. In other cases, was just a matter of connectivity between them and integration between them. So, how do they shift their focus or readjust their focus, and what should they do to actually swim out of this muck?
Michael Carroll (07:21)
So, That is a fascinating question because it's what you have, what you have, and you can't undo it, right? It'd be way too costly to try to undo your MES, your ERP, and all that stuff. So, the approach we're thinking about is, well, let's go to where the work actually gets done. And so,
When you think about it from that perspective, you say, if you're actually trying to do the work and you're one of the folks that needs focus, what do you think about? What do you need to know? What do you need to do with it? And when do you need to do it? And when you look at the way that employment has shifted and that demographic change we used to have, an entire organization that was built in the enterprise, between the enterprise and, let's say, the asset level, that gave us control of servicing the customer. Right? And so, they've done all the transactional work that all this technology was put in place to facilitate. Over time, competitive pressures have caused us to reduce the amount of the organization to a bare minimum. Then, the demographic changes have reduced the amount of knowledge from, let's say, 25 to 35 years of experiential knowledge in that ability to control the enterprise, right, between the customer and the asset, the supply chain. That's been reduced to a much lower degree. That's now down to, let's say, 10 to 15. So, you've got part of your company turns over every two or three years, and part of your company wants to career with you.
And so, now people don't know as much anymore. So, now you've lost control in there and which made the technology not as meaningful from a perspective of losing focus. So, you went from having 35 year old drivers on the interstate and traffic in downtown Atlanta that made, let's use these traffic navigational apps like Google Maps or Waze, right?
It's really effective, so now you put that in the hands of 16-year-old drivers, right? And so, now you're much, much less effective, and you've lost control. So, now what do you need to go do? You can't touch the stuff you've put in. So, now you have to figure out how to be more instructive with the employees who are still trying to navigate this world of: "What do I need to know?"
What do I need to do, and when do I need to do it? So, you can get control back between what the customer needs and what the supply chain is actually trying to do. And that's a different world that you need to orchestrate relative to what your infrastructure is saying.
Filip Popov Plavsic (10:32)
So, you went bottom up basically, sort of auditing at the shop floor level, which is the main core of the business, and then building up the picture, right? The structure upwards to up all the way up to the customer basically.
Michael Carroll (10:34)
I think that bottom-up is really important because what you find is, and I'm glad you said that what you find is that there is much of that transactional debt that you build up in your company, right? Of stuff that people just have to do. And it takes some of these people 25 to 35 years, they can deal with it. But when somebody's got two years or less of experience, they don't have the wherewithal from an experiential perspective to deal with all that at the same time they're trying to be safe. And so when you look at the safety records in most of these companies, the safety records have really declined and gotten much worse as the demographics have changed because people have lost their adaptive capacity, right? Because of the transactional burden. So, it's like asking 16-year-old drivers to text and drive. When you add transactional load, where before, people used to be able to manage that because they had some automaticity.
Filip Popov Plavsic (11:56)
Okay. So, just so that I'm clear on that. Basically, you said: hey, we have these solutions, this tech stack, and architecture as is; we can't touch that. But what you did is you've trained the staff to better use it or to focus on the things that are only useful for them, as opposed to actually working on the tech stack itself, changing some components or customizing in some way, or finding different vendors. Did I get that right?
Michael Carroll (12:29)
Yeah, so what we've said is our infrastructure is our infrastructure. ERP is our ERP. And we got it because we're a company that is an accumulated company of purchasing different companies, we have a lot of ERPs, we have a lot of MESs, we have a lot of infrastructure that's different. And so, you can go out, and you can make, say I'm gonna have just one, you can go through this massive change, or you can say, I'm gonna re-architect myself.
Filip Popov Plavsic (12:44)
Yeah.
Michael Carroll (12:58)
And in that re-architecture, I'm going to go to the front line and say, what do you need? Now, everything goes to the front-line employee through one single pane of glass. And then the architecture says, I don't care what infrastructure is, I'm going to orchestrate out of an ecosystem where I'm the orchestrator of context and in that ecosystem, no matter whose smart application I use. And there are a bunch of smart application builders out there for safety, asset maintenance work processes, and asset health. There's a bunch of application builders that use analytics, you know, some their version of AI. I don't care which one I use. I just need to take those insights, orchestrate those insights for myself, and send them through one single pane of glass to the employee that also incorporates information from the infrastructure, right, which includes the asset, and then say, what do you need to know?
What do you need to do with it? And when do you need to do it? You look at your navigation app in the same way, right? So, your navigation app, basically at the top of it, tells you what you need to know. I need to turn right in half a mile, right? Which allows you to plan for that turn while it handles the complexity of the navigational calculus, right? Of you trusting that that's the right path to get you to the outcome that you need. And, of course, it tells you what your goal is at the time. And it gives you an awareness of what's going on around you through notifications. So, that kind of orchestration, you have to be the owner of as a company.
Filip Popov Plavsic (14:36)
Got you. Fair enough. As more and more things in production get more and more digitalized and to an extent automated in manufacturing, how do you think the role of the worker will change?
Michael Carroll (14:50)
I think the role of the worker becomes more important. There's this, it's interesting, we have a lot of conversations, and there's a lot of worry that, is AI, right, gonna replace workers, right? I can't imagine that's ever gonna be true. At some point, you can't automate everything. There are some functions where artificial intelligence and automation are perfectly suited to handle repetitive and complex things. Now, navigational calculus is a complex thing, right and so AI will be perfectly suited for that, but for executional stuff that requires judgment and hands-on stuff people will always need it, be needed to do the oversight and the auditing and the presence.
They will always be needed to do that kind of stuff. And so, people will be the auditors, the monitors, the contributors. They will be that part of the employment base always. And together there will be more.
Filip Popov Plavsic (16:03)
Gotcha. Okay. Yeah, I think we're aligned on it. I think we're, yeah, I think we're aligned on that. Now, you mentioned AI and recommendations. So, I have to ask anywhere in your production and your core business, right? Do you have any AI running in the production in the form of a set-point recommendation system? Are you making any efforts to work towards a closed-loop AI automated production today? And if not, why?
Michael Carroll (16:32)
So, we are learning how to do this as fast as possible. And so, we are trying to do guided instructional work and it's test and learn with employees. If anybody says they know how to do this in the world that we live in today, right? Well, you can guide people and tell them what to do next.
But in that space where you're always at an interchange between people, right? Because you're always giving people information, you're always gathering data in this exchange. We're still learning how to be more effective at that because you still have processes you're working through, right? We're still learning how to do that. So, we are doing that. We have also done where the risks are, we believe, appropriate.
We have done closed-loop operations across facilities, and we're trying to figure out where that's best suited, given the complexity and the expertise. So, we're trying to figure out what's the best thing to do given our expertise remotely. What's the best thing to do locally and learn by asking the questions, okay, how do I most effectively make the best use of the talent that is available in order to create this better competitive outcome? And the only way to do this is to try.
Filip Popov Plavsic (18:06)
Yeah, so the North Star there is when you say what's better is what's most profitable and efficient.
Michael Carroll (18:16)
That's right. That's right. And not all facilities are the same, even though they might make similar products, right? And they're not in the same place either.
Filip Popov Plavsic (18:27)
Yeah, well, you do have that added challenge, as you said, that you guys were buying different companies, which means different architecture, different hardware, different protocols, and, to an extent, a different mentality and culture, right? So, that's an added challenge that you guys have. Okay.
Michael Carroll (18:47)
I would say our experience, you say culture, in our experience, it's probably... it seems to be less about the people on the front line and more about our limitation from a leadership perspective of saying, hey, what do you need to be more successful? Instead of thinking, hey, you need this, we got much better faster when we said, what do you need to be more successful?
Filip Popov Plavsic (19:20)
Yeah, I 100% agree with that.
Michael Carroll (19:31)
Successful. And does this help or hurt? And listening to that, so you said bottom line or bottoms up right, so this front line mentality of saying what is it you need, how do you need to reshape so that you can be more focused on what you need in order to create, help us create this competitive advantage and you know we find these folks are really, really good if you take that approach.
Filip Popov Plavsic (20:02)
Yeah, yeah. So, I suspect that in this case, it's crucial to have either one figure or department running this initiative, you can't; they are solely dedicated to this internal auditing and so of sorts, whether we can call them head of digitalization, head of new technology, head of AI, head of industry 4.0, or that's your role.
Michael Carroll (20:32)
Yes. So, yeah, so we've evolved over time. My role is one of what we think the world will look like in five to six years. What do we think those challenges are? And how do we need to be thinking in order to meet those challenges in five years or more? And then, what capabilities do we think we might need?
And the way that typically plays out is if you can start having those conversations when that world becomes apparent in a way that you start to see these things become real, you're less reactive to it and more proactive to it than your competition. And so, you make decisions a little better, a little faster than your competition. We have these wonderful AI capabilities and analytics capabilities, and what you would call operational excellence capabilities already in place that you just operate through, which makes you way more effective when these things actually happen.
Filip Popov Plavsic (21:42)
So, you're saying something pretty cool, like that type of zero thinking for solving for problems that are still not, don't exist, right? How do people train that muscle? I know you said you read thousands of books, but is there any practical sort of resources or anything that you can propose for people so that they can, who are in your role or who looking for digital transformation to have that mindset?
Michael Carroll (22:12)
So, it doesn't take much work to actually look at; when you look at the executives and senior leaders in companies that excel, those senior leaders dedicate themselves to learning. And so you can ask yourself a couple of questions. Why is it true that no matter what scale you look at, even though it's available, that technology is not evenly distributed? You can look at a global scale; you can look at cities and towns. You can look inside companies. Why is it not evenly distributed even though it's available? Right? There has to be something driving that. And then ask yourself another question at the same time. Why is it the companies that excel? Why do their leaders read more than 30 books a year, the ones that are really good and up to about 100? Why is there some proportional difference between 30 and 100, where the companies whose leaders read 100 books a year do so much better than the ones that read 30, right? And you know, you think Elon Musk reads 100 books a year because he enjoys reading? Or do you think he understands that his learning rate has to exceed his company's need for growth?
The math says that your company's need for growth is compromised if your learning rate as an executive doesn't exceed it. And so, that's where we are. And one of the ways you see that manifest itself in a company is when somebody learns something; it infects their lexicon. Then, what happens is the rest of the company. When they start talking, the rest of the company starts changing their lexicon in order to create social coordination. And then, because their lexicon is infected, they later become more familiar with that learning. When the environment changes, they're in a better position to take advantage of the change because they've already thought of it.
Filip Popov Plavsic (24:19)
Yeah, You're, in a way, planting seeds and preparing your soil.
Michael Carroll (24:25)
Yeah, you're preparing the ground, right? So you just prepare the ground.
Filip Popov Plavsic (24:32)
Okay. I think you've actually covered it right now. I just had one last question, which was what advice would you give to a leader who looking to start companies digital transformation journey, especially in a traditional industry like paper manufacturing. But I think you cover that with learning is important if you want to, for leaders, right? If you want to stay ahead of the competition, and that is one of your cheapest and most valuable assets that you can do. Anything else?
Michael Carroll (25:04)
So, here's what I would say about this. And you can choose not to do this, but here's the consequence. The consequence is that your assets won't go away. Your people won't go away. They're just gonna get somebody else's name.
Filip Popov Plavsic (25:15)
Fair enough. Okay. That's what I guess happened with your companies before they became part of your group.
Michael Carroll (25:32)
That's what's gonna happen. Yeah, that's the way this works, right? Because the people who make decisions a little faster, a little better, win.
Filip Popov Plavsic (25:46)
Yeah. Yeah, I think that's very, very well put. I do have last two bonus questions, a little bit more lighthearted. First one being what's the technology or scientific innovation you're most excited about, industry 4.0 related or otherwise?
Michael Carroll (26:14)
So, it's a combination of the two. I think quantum changes humanity, quantum compute. And I think the big gap between what we're doing today and quantum is that we can't just solve the same old problems with quantum. Quantum solves different kinds of problems. The compute is different, the power is different. And if you look at controlling massive amounts of energy, the kind of energy and the kind of control and precise control that it takes to get us away from being slaves to this planet, it takes quantum compute to control that kind of energy and to get away from where we're slave to, which is this planet. So, quantum is a key to our future, right? And I'm excited to see where quantum goes.
Filip Popov Plavsic (27:16)
But when you say quantum, in what capacity? Commercially available, governments, companies, how does that... Everything. Okay. Yeah.
Michael Carroll (27:23)
Everything. I think Quantum is a paradigm that changes everything.
Filip Popov Plavsic (27:32)
You know, for sure. But how far do you think we are away? I feel like I'm talking to Michio Kaku right now. But how far do you think we are from that becoming our reality, I suppose?
Michael Carroll (27:46)
Less than a decade.
Filip Popov Plavsic (27:49)
Okay, well I'm excited then for the years to come. Let's see what kind of paradigm shift that's gonna bring. And if I called you on Sunday at 3 p.m., what would I be interrupting you from?
Michael Carroll (28:06)
Reading?
Filip Popov Plavsic (28:08)
Reading? Do you have a reading room?
Michael Carroll (28:09)
To read 100 books a year or more, you have to kind of learn to read everywhere and to take advantage of it. And so, you know, reading for me goes from, and it's just not books, right? It's all forms of digital media. It can be YouTube. It can be Audible. It can be a hardcover book.
Filip Popov Plavsic (28:13)
Or do you read everywhere? Anywhere?
Michael Carroll (28:40)
For me, it's everywhere that I can gather information from in order to think about what I can learn that forms some type of adjacency that I can then put perspective against that, at some point, I can apply context to. Because it takes all three, right? You have to take knowledge, put perspective with that knowledge, and then apply some context to it.
Filip Popov Plavsic (29:08)
I do have a millennial question for you. In an age where information is in surplus and abundance, how do you filter yours? How do you filter for the one that's most useful or beneficial to you?
Michael Carroll (29:27)
You know, I wish I knew the answer to that. Consuming so much information. For me, I just, whenever I see something that I'm working on, this information that I've read and gained just comes back and I don't know what the filter is. I really don't know what the filter is. I don't know what it is.
Filip Popov Plavsic (29:56)
Okay, fair enough. Fair enough, Mike. Thank you very much for coming and sharing your story with us and your experience. Hope that you will be going to be a returning guest in the future. Yeah, absolutely. Thank you. Thanks. Have a good one.
Michael Carroll (30:13)
I look forward to it. You guys are fabulous. I look forward to it. Thank you.