This episode of Supply Chain Now dives into how Georgia-Pacific, a nearly 100-year-old company, embraces digital transformation. Listen in as hosts Scott Luton and Kevin L. Jackson welcome Roshan Shah, VP of Applied AI and Products at Georgia-Pacific, to discuss how they use machine learning and artificial intelligence to improve decision-making, reduce waste, and make their operations more sustainable.

Join us for this captivating conversation as Scott, Kevin, and Roshan highlight the importance of human-AI collaboration, how technology can empower people, not replace them, and also share valuable insights on leadership and navigating change management within a large organization.

Narrator [00:00:04]:

Welcome to Supply Chain Now. The voice of global supply chain. Supply Chain Now focuses on the best in the business for our worldwide audience, the people, the technologies, the best practices, and today’s critical issues, the challenges and opportunities. Stay tuned to hear from those making global business happen right here on Supply Chain Now.

Scott W. Luton [00:00:32]:

Hey, hey. Good morning, good afternoon, good evening, wherever you may be. Scott Lewton and the one only, Kevin L. Jackson here with you on Supply Chain Now. Welcome to Today’s show. Kevin, how you doing?

Kevin Jackson [00:00:41]:

Hey, I’m doing well. We just had another thunderstorm come through here in northern Virginia. That’s four days in a row. Right on time.

Scott W. Luton [00:00:51]:

I tell you what. Hey, welcome to May and June and weather across, it’s been something else. That’s right. Summer is. It’s hard to believe Summer’s already here, but you know, all that. Hey, Kevin, today we got a great show teed up. We’re going to be talking with a business leader that’s helping to lead digital transformation at a company that was founded almost 100 years ago in Augusta, Georgia. A company that offers a wide portfolio of products all powering its growth across some 150 plus locations all around the world.

Scott W. Luton [00:01:21]:

Stay tuned for an informative, enlightening and entertaining conversation. Kevin, should be good one, huh?

Kevin Jackson [00:01:27]:

Oh, yeah, absolutely. Think about the change that company, over 100 years old, have to deal with. Talk about change management.

Scott W. Luton [00:01:37]:

Kevin, I’m going to introduce our distinguished guests here today. Looking forward to learning from Roshan Shah, Vice President of Applied AI and Products at Georgia Pacific, where he’s worked for almost seven years. Now, in this role, he’s responsible for helping the organization create value through data and artificial intelligence. He’s got a background in applying machine learning across various industries over the last 15 years, and he brings all of that wealth of experience to his position here. Now, previously, Roshan spent several years working at CSX Transportation in the railroad industry. That’s a fascinating chapter of his journey. He also holds a bachelor’s degree in statistics from the University of Florida. Go, Gators.

Scott W. Luton [00:02:17]:

And an MBA from Duke University. Home to Blue Devils. Roshan, welcome, welcome. Great to see you here today.

Roshan Shah [00:02:23]:

Thanks, Scott. Thanks for having me here.

Kevin Jackson [00:02:25]:

I literally love your title. Applied AI. No theoretical stuff here. I’m making it work.

Roshan Shah [00:02:32]:

That’s right.

Scott W. Luton [00:02:33]:

No time for lip service. Right. But acting out. And we’re going to be getting into some of that today. Hey, before we get into a lot of all things AI and digital transformation, I got a couple of quick questions for you, Roshan. I got to start with collegiately. With collegiate sports. Do your allegiances lie with the Gators or do they lie with the Blue Devils?

Roshan Shah [00:02:54]:

That’s a hot topic in my household. You know, with the SEC and s acc. Part of family’s kind of coming together, but I stick with my Florida Gators.

Scott W. Luton [00:03:01]:

And then secondly, Kevin, we did a little due diligence, little homework on Roshan. And we have come to uncover that when he is not. So when he’s not doing big things across GP with digital transformation and when he’s not fathering his two kids, which I think are really young, under. Under four years old, I believe he likes to golf and woodwork. So, Kevin, question for Roshan. And then we’ll come to you, maybe, Roshan, what’s been one of your proudest accomplishments here recently? When it comes to golfing or woodworking.

Roshan Shah [00:03:34]:

That’S a tough one in the sense that there’s a lot of efforts in play. I’m not entirely sure that there’s a lot of results, but if I had to pick one, I would say, you know, a couple years ago, we had to take a couple of trees down in our backyard and there were white oak trees. So we took them down and we kind of let it dry. I actually took it to a kiln. And long story short, I ended up building a kind of a kitchen table out of the trees in the backyard.

Kevin Jackson [00:04:00]:

Oh, wow.

Roshan Shah [00:04:00]:

So that’s the. Yeah, and that’s the table that, you know, we kind of break bread on. Right. With my family and kids kind of jump on it. There’s generally things spilled, crayons, everything. And the table’s kind of held up for about 18 months. So pretty, though. Yeah.

Roshan Shah [00:04:14]:

So it’s just kind of seeing that life cycle, you know, off something go from my backyard and spending about six months worth of kind of time working on it and then a family get to enjoy it. It’s pretty awesome to see all that.

Scott W. Luton [00:04:27]:

Oh, Rosha and I love the character that your experiences at your table has enjoyed over the last 18 months. We have a very similar story in our family with my father in law, Fred Mitteke built us a table we’ve been eating on, breaking bread on for years now. So that really relates to our experience as well. Kevin. So wood woodworking, golfing, the how Roshan built the table that he and his family break bread on. What stood out to you? There’s.

Kevin Jackson [00:04:53]:

Well, first of all, that’s impressive, building that table because the high point of my woodworking experience is pine wood dairy cars with my son, like over 30 years ago. So I’m not a woodworker, so I’m going to sit with your golf because I also had great fun in golfing with both of my sons who are golfers. I’m just out there to go pick up the balls out of the woods.

Scott W. Luton [00:05:21]:

And have a few adult beverages if you’re in my office. Love that. Kevin. We got a lot to get into here today. Roshan and Kevin, a ton of stuff. Context is so important. We can’t get enough context in this world. And that’s where I want to start.

Scott W. Luton [00:05:35]:

For the handful of viewers out there across our global audience that may be unfamiliar with Georgia Pacific, tell us a little more about the company, including any details that you can around the supply chain, organization or footprint.

Roshan Shah [00:05:47]:

So, I mean, Georgia Pacific, privately owned company, a subsidiary of Koch Industries, primarily three distinct businesses that form Georgia Pacific. I think you mentioned early on it’s an organization that’s been around for a couple of decades now. And throughout time, we worked on creating value for the communities that we operate in and thereby earn an ability to coexist in that regard. You’ll see quite a few brands that are part of the Georgia Pacific family that are actually in everyday households. Right. So if you consider the fact that there’s about 65% of the american households that consume something coming out of our organization and there is 40% of our products. Right. Or 40% of the products that we make there in us businesses.

Roshan Shah [00:06:35]:

So it’s a household name, I think. And part of that you’d recognize. Brawny. Right. That’s the paper towel that you buy. Or Dixie quilted northern. Right. So those are some of our brands.

Roshan Shah [00:06:47]:

Angelsoft. Those are some of the retail brands. And we also have a lot of presence in private label side of the world in the CPG space. And if you think about our second business unit being building products, this is where you have gypsum wallboard. You’d also see a lot of plywood, lumber. OSB. Similarly, if you go over to our third business unit, packaging and cellulose, this is where you’d have a lot of the. The fluff pulp that goes into materials that end up soaking things.

Roshan Shah [00:07:13]:

Right. So whether that be family hygiene products or like diapers, container board, this is where we make the paper that goes into making boxes that you know. So if you buy something on, say, Amazon, for example, and when something shows up in that brown box, we make a lot of the paper that goes into making that box and the box itself, along with a whole host of products. But so long way of saying, you know, privately owned company, been around for quite some time. And we exist in quite a few households that you may or may not recognize. But you know, it’s certainly an household brand.

Scott W. Luton [00:07:47]:

I love that. And Kevin, I’ll tell you, I’ve got three kids of my own and I go through so much brawny because all they do is make mess and they’re home for the summer these days. We got stuff spilled all over our table, everywhere. So I’m a big consumer, a big customer of GP, at least one of your divisions. There’s Kevin, as you kind of heard him unpack, especially the CPG, the construction, packaging divisions. What comes to your mind there?

Kevin Jackson [00:08:12]:

Well, it really comes to the top of my mind is the contact with the consumer, right. I mean, their product are in the household, in every part of the household and touch every part of your body. Talk about being close, right. And you don’t even know where it comes from. It starts your huge part about why 65% of american households really, I mean, wow.

Scott W. Luton [00:08:42]:

To your point, Kevin, although globally, consumers learned a ton more about global supply chain and manufacturing and other different aspects that go into industry since the pandemic, we got a lot more to go to your point, because I think all of us, even if we’ve been an industry, don’t appreciate where things come from that we interact with or use every single day. So that’s a great point.

Kevin Jackson [00:09:05]:

Yeah, I know we’re going to talk more about this, but it’s also important to recognize that this company is a part of the global sustainability movement and they bear a big role.

Scott W. Luton [00:09:19]:

We’re going to be talking it in the second half of today’s conversation, including some outcomes that Roshan and his team are driving. But let’s do this again, more context. So, Roshan, let’s learn a little bit more about your role and what your team does as you’re powering gains and efficiencies and digital transformation across the enterprise.

Roshan Shah [00:09:36]:

Sure, in my role, I wear a couple of hats, but I have the privilege of working with some of the smartest group of folks that I’ve ever worked with. And these folks look at a lot of the data that our manufacturing plants produce, that our businesses produce. And we look for patterns, anomalies, things that we can analyze at large volume, at large scale that primarily helps us produce things cheaper, faster, easier, have less impact on the environment. And we do that through a very large scale. So on a day to day basis, we analyze about 2 trillion records of data that gets generated from about half a million sensors that are constantly sending us data. Now we apply machine learning models, artificial intelligence on top of that data to figure out what’s wrong, when is it going to go bad, how much time do we have and what should we do about it? And through collaboration with the engineering team, through the teams that we have, our corporate headquarters teams and at the facilities, of course, most importantly, working across the board to look at the output of that model and bring in the human element of, well, what should we do about it? And taking a risk based approach to figuring out what should we do so we can have the least amount of downtime, least amount of waste in the most optimal production quality and quantity as we can, given the kind of market conditions. And that’s at a high level kind of my role in helping make that successful. And we, as I mentioned, quite heavy reliance on data and knowledge that we can gain through the use of large language models and a lot of human element to this.

Scott W. Luton [00:11:14]:

Love that. So, Kevin, going back to the first part of Roshan’s response, there 2 trillion records from half a million sensors. And I think that was daily analysis. Roshan, if I got that right. So, you know, when I think about technology and human factor and how they compare each other, when I was an air force, Kevin, part of my role 20 some odd years ago was reviewing records, right? Looking for data integrity as we were performing a variety of actions on the fleet, right? So a good day for me was probably a couple hundred, as I recall, back as long time ago was probably a couple hundred records, right? As I had my to. I was going through my red pencil, a couple hundred records. And it just, it springs to mind as. And listen to Roshan explain that how we have to.

Scott W. Luton [00:12:03]:

It’s not even an option. We got to lean into innovative technology so we can get a lot more done every single day. 2 trillion records from half a million sensors. Your thoughts there, Kevin?

Kevin Jackson [00:12:14]:

The thing that really jumped out at me was they have to leverage the machine learning models and artificial intelligence to manage and review all of these records and more importantly, make important decisions based upon the marketplace, the goals of the organization and what the customers want. That’s 65% the marketplace. And I wonder, how do you do that? Because one of the key aspects of any business is governance. For a long time, companies have been trying to deal with governance of data, just the data by itself. But now you’re putting another layer on top of that, which is prep to not just governing and managing the data, but managing and the governance of the machine learning models and the artificial intelligence models. That you’re using to glean insight from that data. So how do you do that? You know, how do you apply this governance to this advanced technology?

Roshan Shah [00:13:34]:

And that’s a really good question, Kevin. You know, it’s a challenge, right? But the rewards worth the risk, right? Let me come at it this way. What we’ve noticed over the last five years that we’ve kind of been, you know, working in this area is when we are able to consume these massive amounts of data, apply models, and then put the output of the models in front of people. Right? Because I mean, at the end of the day, it’s all about how do you help somebody make a better decision? And when folks are able to make better decisions, that impacts them personally and professionally. I think there is a level of connectivity, a level of ownership that folks feel. So consider this. If you have a failure in the middle of the night while a plant is running, you might get a phone call or you might be repairing something that is kind of dark. It’s a little dangerous, right? But through the lens of data, AI and humans being in the loop there, if we are able to help avoid an unplanned event in the middle of the night that doesn’t require somebody to go and take an unnecessary risk, rather, then that kind of humanizes things, that drives adoption.

Roshan Shah [00:14:42]:

And that’s been something that we’ve noticed occurring consistently over the last couple of years. I can share that. If I looked back five years ago where our unplanned events were to where we are today, I mean, we have 30% less, at least less unflight events that we used to. So that comes through the lens of data and AI and helping our colleagues in the facilities appropriately assume the right risk. Then second piece to your question around the governance side of things. At the end of the day, we’re applying data and model against sensor data, right? So if you think about, there’s math that learns from it and there’s always somebody at the end of it to look at their output of that model and then do something with it. So governance is kind of inherently baked into that where people with good intentions and principal entrepreneurs, they’re going to make the right decisions, that they kind of demonstrate that over time. And what we’ve noticed is the output of these models, these data that, you know, facts that these things show that when folks are able to consume that it impacts them positively.

Roshan Shah [00:15:45]:

I think there is a large sense of ownership and pride in doing the right thing with what the model was doing. So very long winded way of saying kind of that governance is distributed in that regard to the end users, and it’s embedded in how they consume the output of things. And it’s been quite privileged from my standpoint to be able to see that organic and that natural adoption of the output. And that kind of. That governance just kind of gets baked in, so to speak.

Kevin Jackson [00:16:10]:

Wow, really like what you’re saying there. The machine learning models and the artificial intelligence is actually benefiting the humans not only in making things safer, but improving their work environment and improving their productivity. So they’re working together. It’s not this. No AI is going to take my job away. No AI is enhancing your job. You’re using humans for what they’re good for, and that’s their brain, their thinking, their fourth thing, their decision.

Roshan Shah [00:16:50]:

Absolutely. I’ll give you one example. Just in the last couple of days, I’ve been part of two phone calls where consumers of the output of these models, they picked up the phone and called us and said, hey, you guys missed x, Y and Z. And what’s really interesting is the things that we missed. And these folks are not bringing that to us through the lens of, well, you guys are not worth anything and you’re missing all these, but they’re kind of giving us this feedback that says, hey, you missed this. Can you go and tweak your model so we don’t miss it next time and we can all be in the same page? It’s just that level of ownership, like, we’re not pushing it, it kind of folks are pulling on it. That to me, sends a message that when folks know that this is kind of AI, there are a lot of folks who want to participate in it, want to own it and drive that for everybody’s betterment versus, to your point, purely looking at it as a threat.

Scott W. Luton [00:17:39]:

It’s many things, as I’m hearing Roshan describe it. But Kevin, I think you were alluding to kind of my main thought is the profound impact that Roshan and his team are having on the business is from decision making to the 30% less unplanned events. I can just hear friction and disruption coming out of the enterprise. But what’s most important to me, which is what you centered your response around, Russian, and that’s the quality of life for your team members and enabling them to find more success next go round and having their back to do that, that is a beautiful application of technology. So you’ve made our day here today, Roshan. Okay. I wish we had a couple more hours with you today, but I want to move along to a very specific area of impact on the business that you’re seeing, especially given some of your previous experience in demand planning. And then we’re going to get into some of the bigger picture key pillars of overall digital transformation at the organization.

Scott W. Luton [00:18:33]:

So let’s start with you spent at least a chapter of your journey involved in demand planning. How do you see analytics and AI transforming that long running component of global supply chain? Roshan?

Roshan Shah [00:18:46]:

You know, I think it’s key to it. From my seat on the bus, what I notice is there’s a lot of fluctuations, right. Whether that be from geopolitical standpoint, whether that be from weather standpoint, there’s a lot of fluctuations that if we are not able to notice that early on and react to it right as quickly as we can through the help of machine learning models, et cetera, then downstream that effect, by the time it reaches to the end consumers, it’s two x worse. Whether that comes through the lens of, well, there’s not enough products for everybody not in the right place, costs are going kind of out of control and all kinds of things. So it is extraordinarily important for us. We recognize the value in being able to make demand planning as predictable as possible. Now, that’s kind of easier said than done, of course, but we recognize that’s a very integral component of what we as an organization need to be good at.

Scott W. Luton [00:19:44]:

Yeah, and I bet a lot of gains there, too. You’re being pretty humble, but with all of what you’re analyzing every day and kind of feeding that like the Mississippi river into the demand planning processes, I can only imagine the gains you’ve made.

Kevin Jackson [00:19:57]:

Kevin, it really comes back to two way communication between the production line and the customers that are receiving those products. That sensitivity to, I guess, the butterfly effect across the manufacturing process, the value chain there. You’re right. If something small happens on the manufacturing floor, could be a big, huge impact to the end consumer. I really appreciate that attention to detail.

Scott W. Luton [00:20:30]:

Yeah, I’m with you. And I bet your response made me think of Kevin something also, which you spoke about earlier today is my hunch is, even though Russian didn’t say it directly, is that they’re able to be more customer centric and be able to listen to a lot more feedback and act on it based on how theyre leveraging technology here.

Kevin Jackson [00:20:48]:

Right. Right.

Scott W. Luton [00:20:49]:

All right, so lets go broader, Roshan and Kevin, when you think of the overall digital transformation strategy at Georgia Pacific, what are some of the key pillars? Roshan, you can share with us we.

Roshan Shah [00:21:00]:

Think of problems to be solved through the lens of transformation, right, ones that are not just from a profitability standpoint, but also we have the privilege of operating in the communities that we do, kind of bringing value to our customers. So we’ve got to think through the lens of what do they care about, right. And working back from that, whether that be from a value standpoint of on time, you know, in full, or whether that be through the lens of predictable outcome. As you know, we talked about, when I work back from those problems, the things that we care about is reducing our unplanned events, right. Helping our operators and kind of our colleagues in facilities have access to as updated and easy information as possible. This is where generative AI comes in quite heavily. A big priority for us is operating safely. I’ll give you a couple of examples.

Roshan Shah [00:21:55]:

In that regard, we’re working pretty hard to take all of the sensor data and all the data that we can get from machines that IoT sensor data to be able to apply machine learning model site and say, hey, are some of those trending in the wrong direction that would inherently expose somebody to an unnecessary risk. Right. So say if a temperature is going in a direction that we don’t want it to, we have the ability to see that and we do our level best to be able to predict that and then get ahead of that before it becomes something that somebody has to react to in a unsafe manner. Right. So those are kind of the use cases that we’re working on. As we think about that, it necessitates that we have a flexible and a cost efficient cloud strategy. This is where we partner very heavily with AWS. We also need to be able to compile all of that data into environment that we can easily manipulate.

Roshan Shah [00:22:52]:

This is where, again, AWS comes in very heavily with elastic cloud computing and other services that we get from these cloud providers. But all of that is like the data, the cloud, the computing, all of that are technology. But that has to come through the lens of, well, how is that improving? Making it easier for our teammates to be able to do something easier. Right. That’s where it really has to come to. Otherwise, transformation for transformation sake. If it’s not improving somebody’s life, then a, there is relatively less adoption, but b, I mean, whats the point? So we look at it through the lens of making it easier, faster, less waste. And thats been kind of our big priority and goal.

Scott W. Luton [00:23:34]:

I love it. Roshan. Kevin, ill give you a chance to respond to his answer there first.

Kevin Jackson [00:23:39]:

Yeah. So the way you brought in AWS as your partner in managing data. I think its critical, its important because its only through the use of cloud based technologies can you efficiently analyze all the data that comes from the sensors so that you can improve your own business processes. But at another level, maybe a more important level, Georgia Pacific is really a steward of our natural resources, you know, global natural resources, and you’re using the power of data, the power of the cloud to champion the preservation, efficient use of our natural resources. That link is actually not highlighted in a lot of arenas.

Scott W. Luton [00:24:39]:

Well said. And Kevin, I’m not sure if your nickname should be Mister Digital transformer or Mister Cloud, but we’ll debate that after today’s episode. Roshan, you know, you’ve kind of sprinkled in successes and real palpable outcomes from your digital transformation efforts at Georgia Pacific. From one of my favorites is what you were just talking about a second ago, applying in a predictive manner to lessen safety incidents and lessen non safe environments. I love that. Anything, you know, protecting the workforce, enabling and empowering the workforce. I love those applications. We talked about unplanned events.

Scott W. Luton [00:25:15]:

We’ve talked about decision making. Kevin touched on sustainability, which we’re going to touch on in a second. Anything else before we move on to maybe something that didn’t work out like you had it planned and maybe what you learned from that? Any other big success you want to highlight before we move forward? Rosh?

Roshan Shah [00:25:30]:

We’ve been fortunate that we work for a company that is leaning forward in terms of transforming, you know, thinking about the application of technology to help improve lives. I personally think I’m quite fortunate to have had that luxury in that regard. I could probably talk a couple different ones where it’s worked out pretty well for us. The one that I think that I’m pretty excited about as we dive into this new world of generative AI. Now, of course, that’s all the buzz these days and there’s a lot of hype around that for sure. But where I think we’ve been able to apply that, it’s early, but we’ve been able to apply our data, the documents, the numbers, the pictures, all what have you, in a manner that before a machine operator knows to ask a question, we’re able to predict what’s occurring on that machine and then be able to not just call an operator and say, hey, you got this problem. I think the last thing the operator needs to know is that, you know, they got 51 problems and now there’s a 52nd for us, the effort has been, how do we combine our data and all and power generative AI and everything and then be able to surface to this operator, right, or subject matter expert that says, hey, it seems that sensors are telling me this is a problem based on the generative AI output. I believe the causes and the solutions could be this.

Roshan Shah [00:26:54]:

And packaging all of that information along with the pictures and videos and just making it really easy for an operator to recognize this problem is about to incur. You may want to consider doing XYZ. Historically, someone else tried ABC and there’s a high probability that will work. In other words, you’ve kind of given somebody a lead time to react versus just reacting to a stimulus. I think that’s something that we’re pretty excited about and that’s we’re going to keep working on that to see how we can improve that.

Scott W. Luton [00:27:24]:

Love it. RoSHan and Kevin, for get your response. I love the cultural wind there because those operators, as folks out in the plant see you as allies. They don’t see you as looking over their shoulder. They see you as allies to help make them more successful every day and safer every day and give them a heightened quality of life. Kevin, what’d you hear there?

Kevin Jackson [00:27:44]:

What they make it an important aspect, packaging the data so that it is consumable by everyone that’s responsible. You know, don’t give me a huge spreadsheet with numbers that I have to manipulate. Give me a picture that I can see what’s happening, you know, relate it, make it relevant to what I do every day. So I think that’s important. And that also is part of the culture of the organization. I always say digital transformation is really more about communications and being able to communicate the value and insights of data to everyone that data touches. And I love how you are focused on that communication.

Scott W. Luton [00:28:39]:

Well said, Kevin. Well said, sir. Roshan, we’ve spoken a lot. The gains you all have made, we got to keep it real because my hunch is y’all value experimentation and every experiment doesn’t exactly work out like you had planned. That’s good, because we learn from those opportunities. Right? Is there anything you can share related to something that maybe didn’t work like you hoped it had and any lessons you applied from it?

Roshan Shah [00:29:06]:

Absolutely. And to be honest, that list is fairly long. Of all the mistakes, I’m not sure if we could even count them this point, to be honest with you. But there’s a theme early on as we jumped into this, is whenever we’ve had this notion of, oh, well, we have this opportunity, we’re going to go chase and we’re going to go into this with this grand plan of like, oh, we’re going to do this, this, and this. We end up recognizing that while we might have had success in the first step, the second thing, we just didn’t even consider our plan. And I’ll give you one very succinct example. So without naming any specific technology, we bought some technologies that we’re going to going to go apply and we did only to recognize that we made this all about technology without really connecting to, okay, well, how is the workflow coming together? How is somebody at the end of the value chain? How do they react with it? How do they connect with it? How is it impacting them? It’s so differently. I think we inadvertently were chasing technology for technology sake versus thinking about, okay, well, how is that changing and impacting somebody’s life? I think we all kind of intuitively know that is a.

Roshan Shah [00:30:11]:

We shouldn’t do that. That’s kind of silly. But I think it’s easy to get bogged down into the flow of things and we end up chasing technologies only to realize that technology, believe it or not, guys, is the easier part of the equation.

Kevin Jackson [00:30:24]:

Right.

Roshan Shah [00:30:24]:

The harder part of the equation is, okay, well, how does it get adopted? How is it impacting change process? How is it that somebody use it, wants to use it and pulling on it, so it’s focusing on those elements. Starting small, kind of experimental discovery versus grand plan. Right. That’s a bit of a mantra we’ve held. And it’s. Although we might have known that, we’ve heard that it’s taken a few stub toes for us to kind of embed that into our practice. And we still make some of those mistakes. But that’s been.

Roshan Shah [00:30:53]:

That’s probably been the largest theme I would share.

Scott W. Luton [00:30:56]:

Love it. Roshan, you know, I would just add, before I get Kevin’s response, I would submit to you that we’ve all chased technology for technology’s sake. But the differentiator are those that are aware of when they’ve made that mistake and those that are fooling themselves that they haven’t made that mistake. So I appreciate how you’ve been on, you know, very transparent with us because we’ve all done it. Kevin, your thoughts there.

Kevin Jackson [00:31:18]:

Fail fast, right? That’s the whole idea. If you fail fast, then you learn even faster. So it’s really important. And that, once again, part of the culture. And when you do digital transformation, don’t forget to bring the humans along.

Scott W. Luton [00:31:37]:

That’s right. That is right. Fail fast and know why you failed. Right.

Roshan Shah [00:31:43]:

Yeah.

Scott W. Luton [00:31:43]:

Knowing that is so, so powerful. Okay, so we have touched on this a little bit, but I really want to get you, Roshan, to kind of address it more in full here, at least with some examples, maybe. How do you see artificial intelligence in particular impacting a couple areas here? Let’s start with sustainability gains, whether it’s at GP or what you see out in the market, how do you see AI advancing real outcomes there?

Roshan Shah [00:32:08]:

We have a couple of examples from our own work, of course. But I think in general, the notion that adopting and applying AI is optional, I think my personal opinion, that’s flawed. Whether you do it or your competitor does it or somebody else does it, whoever adopts it is able to do all the right things with it is going to lead the way. The question is, do we want to be a laggard in that equation, or do we want to be experimenting and learning? Because the notion that you could just download this AI, AI is not so much as an app you download. Right. You kind of have to embed that into your practice. The saying that we kind of have is digital transformation is less about the technology, and it’s about changing the hearts and mind, and that takes time. Right.

Roshan Shah [00:33:00]:

So in that regard, I think AI is going to continue playing a pretty significant role, and it already has for us. And I can give you a couple of examples.

Scott W. Luton [00:33:09]:

Right.

Roshan Shah [00:33:10]:

So if you consider waste, we consume raw materials and we produce finished goods, but in that process, if we are not careful, we can inadvertently create a lot of waste. What weve been able to do through the lens of machine learning models and computer vision, and empowering our operators, our colleagues, to make better decisions, we can see things that would lead us to have more waste. We are able to see that machine learning models flag us. We can quickly analyze, well, what is it trying to tell us? How do you translate that anomalous output from a model to, oh, well, this is what it’s trying to tell me. And then you can implement that change almost in real time. To be able to avoid waste, that’s pretty powerful. You could think of that through the lens of sustainability. Right.

Roshan Shah [00:33:57]:

If we’re able to reduce waste, we consume less natural resources, we’re able to pass off cost savings to our consumers. So there’s a lot of value to be had from leveraging AI to help make better decisions completely free.

Scott W. Luton [00:34:10]:

And I would just add waste in all of its forms. I know you kind of focus your example around product waste or tangible waste, but I think it wasted time, wasted talented motion.

Roshan Shah [00:34:19]:

Yep.

Scott W. Luton [00:34:20]:

And how you’re gaining from all of that, including the type of waste that is by reducing it, is better for the planet. Kevin, your thoughts on some of the sustainability gains they’re empowering there?

Kevin Jackson [00:34:29]:

Yeah, I mean, sustainability actually helps you in many different ways. Less consumption of raw material, more product at the end of the manufacturing line, less resources that you have to leverage or use or expand in the production of product. So this insight that the machine learning models provide and artificial intelligence provide and that humans implement it, is critical to reaching sustainability goals. Net zero carbon and improving our entire environment.

Scott W. Luton [00:35:16]:

That’s right. That’s right. Meeting the demand of the markets, the consumers, the whole ecosystem. And I appreciate what both of you all spoke to there. Russian, I was going to ask you this question, and looking back, you’ve baked in, I think, an element of this to almost all of your responses. So I’m fearful of asking. It might sound redundant, but give you a chance to dot an I across the t in case there’s something that you haven’t mentioned that you want to. So, you know, it feels like to me that core to your approach as a leader and core to the approach of your digital transformation strategy at GP, humans are in the middle of that.

Scott W. Luton [00:35:52]:

They’re in the middle, and that’s the north star. So when you think of how AI empowers a human factor beyond all that you’ve already shared, is there anything else you want to add that’s really important that maybe we haven’t mentioned here today.

Roshan Shah [00:36:06]:

Maybe worth just double clicking on it? Is the fact that is AI here to kind of replace people and what, you know, our colleagues do, or is it here to augment, and I think I firmly believe it is here to augment what we do and make it easier. So it’s kind of the simplistic analogy, but if you consider the seat belts in your car or the fact that we have power brakes, right, they’re not just purely mechanical, there’s, you know, like hydraulic and electricity, but help makes it easier for you to brake. Right. It’s kind of like that thought process where the decisions that we as people make, you know, every day with all the information coming at us at all times, we view AI as making it. So either a lot of the simpler decisions that we may not have to make, or the volume of decisions get simplified, or we have better information so we can make better long term decisions that, again, improve the. Improve our lives, improve the communities that we operate in. I think AI is here to augment that. And worst case scenario, it frees us up to do some higher value things when you have to go and you might spend ten minutes googling something, right? Or looking it up on the Internet.

Roshan Shah [00:37:22]:

Well, you could go to chat GPT and ask a question and even if it’s not perfect answer, it gives you three quarters of the answer within 5 seconds. Well, that’s made you more efficient so you can actually do something with that information versus just compiling all of that together. So it’s kind of like that. Again, back to this notion that AI is here to augment what we do. And I firmly believe that.

Scott W. Luton [00:37:43]:

Good stuff. Hey, Kevin, speaking in one of the things that Roshan mentioned, I’m searching on Google and I’m seeing their chat GPT like responses as it starts to experiment. It’s been kind of cool having used Google for what, for 25 years, it’s kind of cool to see what they’re doing there. Kevin, what you hear though, and in the bigger picture when it comes to, again, empowering the human factor and some of what Roshan describes as core to how he views it, especially in terms of augmentation. What’d you hear there? Kevin?

Kevin Jackson [00:38:15]:

If you get assigned attack many times you have to start at zero before you can get to the end. You know, start at the beginning in order to accomplish your goal. But artificial intelligence, it augments you. So you don’t have to start at the beginning. You know, you use AI so that you can start 25, 30, 50% into the task. You can get finished faster or you can use less resources like time to accomplish the task or deliver the results much faster. So it’s great for everything. While wouldn’t you use AI in your job to write a paper or to do research? You just become better as a human, right?

Scott W. Luton [00:39:08]:

We could all use a head start for sure, no matter if we’re in supply chain or other element of a global trade. Before we start to wrap with Roshan. And I really enjoyed your perspective and responses and examples and how you view the world. I really have enjoyed this conversation with Roshan. I got to go back, Kevin, to his automotive example because in this day and age here, living down in the metro Atlanta area where we’ve got 115 degree days right around the corner, I’m glad that technology, our vehicles has come to the point of modern air conditioning. Because back in the day when I first started driving, my air conditioning started with rolling something down. Y’all are y’all with me?

Kevin Jackson [00:39:50]:

Natural.

Scott W. Luton [00:39:51]:

That’s right. Way before where we are now. All right. So let’s do this. Roshan, I want to talk leadership for a second. Right before we wrap, we’re going to make sure folks know how to connect with you here in just a second in case they want to talk shop or have you come in and speak their teams or you name it. So we have come, goodness gracious, a long way in the last few years. I think we’ve learned a ton.

Scott W. Luton [00:40:13]:

Not that we haven’t always learned, but these last few years, silver lining is, gosh, the powerful business, leadership and human lessons that we have all learned from going through the pandemic and coming out and seeing what’s sticking, fortunately and unfortunately, some of the things that aren’t sticking. So we have a short memory. But Roshan, as you think about that last few years, what’s one of the biggest lessons that you learned or maybe was reemphasized to you when it comes to real effective leadership?

Roshan Shah [00:40:43]:

The fact that it’s a privilege. Right. And you have to recognize that leadership, it’s easily misconstrued as position of authority or power. And you have to recognize you’re there to empower and help support the folks that you work with. And that kind of goes folks who organizationally would roll up under you or the folks that you roll up under. Right. I think it’s recognizing that it’s key. And again, in my own shoes, it’s early on, it’s easy to feel like you are in this position of power, that you have the ability to go do all of these things.

Roshan Shah [00:41:18]:

And you very quickly recognize that unless you have the ability to influence somebody for what they want to do and build that consensus, you can’t just, you know, go and do what you think you want to do versus leading the pack and part of the pack. Right. And that’s a privilege. That’s something you earn as we’ve gone through pandemic, coming out, working from home and all the turnover, etcetera. To me, that’s something that I’ve spent considerable amount of time thinking and practicing. And there are days that don’t always get it right. But that’s a consistent message for sure.

Scott W. Luton [00:41:48]:

I love it and it is a privilege. And I’ll just kind of contrast that here briefly. Kevin, you and I both spent time in the military where you had a very formal chain of command. That was a phrase I was trying to think of, but very formal, very strict. And Roshan, your response reminded me of some of the best people I worked for during the military that also viewed it not because of the stripes on their sleeve or the insignia on their collars that they were an officer, but because of how they viewed it as a privilege to lead the team that they were charged with. Kevin, your thoughts?

Kevin Jackson [00:42:19]:

Oh, yeah. Absolutely. It’s about being that servant leader. Right? Lift everyone up or around you. That upside down triangle vision. I love that. I love that.

Scott W. Luton [00:42:33]:

I agreed. All right, Roshan and Kevin, I knew this was going to become great conversation.

Kevin Jackson [00:42:38]:

This was fun.

Scott W. Luton [00:42:39]:

The pre show. I feel like I’ve gotten a bit of a certification learning from both of you all here today. A lot of good stuff. Hey, Roshan, for the folks out there listening that want to connect and learn more or compare notes, you name it, what’s the easiest way for folks to connect with you?

Roshan Shah [00:42:54]:

Probably the easiest one, I would say, is LinkedIn. Everybody’s kind of on it. It’s easy to interact, mostly free. Right? So I think that’s probably the preferred and easiest.

Scott W. Luton [00:43:02]:

Wonderful. Outstanding. Roshan Shah, Vice President of Applied AI. Applied AI, as Kevin put emphasis on and products. No doubt, no doubt. And I’m sure we’re just scraping the tip of the iceberg here today. But Roshan Shaw, Vice President of Applied AI and Products at Georgia Pacific. Thank you so much for being here, Roshan.

Roshan Shah [00:43:24]:

Thank you, guys. Appreciate the time and the conversation.

Scott W. Luton [00:43:26]:

You bet. But before we go, Kevin, before we go, we’ve got to make sure folks know how to connect with you and your popular series digital transformers, which folks can get wherever they get to promote podcast. How can folks connect with you, Kevin?

Kevin Jackson [00:43:39]:

Oh, yeah. You can always reach out to me on LinkedIn or on the x. Right? I’ve got a huge following on the x. You know, it looks like Instagram is really growing up there, so I like that. But the number one place is on digital Transformers, right? We put out a show periodically and we have a live stream the second Monday of every month. So join us on the stream on video transformers.

Scott W. Luton [00:44:11]:

That’s right. And you can find digital transformers wherever you get your podcast. There’s only one with the Kevin L. Jackson, so make sure you look at the right one.

Kevin Jackson [00:44:18]:

Thank you. Yes.

Scott W. Luton [00:44:19]:

All right, folks, what a great conversation here today. Hopefully you’ve enjoyed as much as we have. Once again, big thanks to our guest, Roshan Shaw with Georgia Pacific. Big thanks to Kevin. Always a pleasure. Knock out these episodes with you, Kevin.

Kevin Jackson [00:44:30]:

Yes, thank you very much.

Scott W. Luton [00:44:31]:

But most importantly, big thanks to our global audience out there. All of your support, all of your feedback as we go through this remarkable journey that we’re on. Appreciate. Keep it coming. It’s really helped us shape our programming. And we’ve got a big second half of the year. So here’s most importantly, you’ve got to take one thing, take one thing that Roshan or Kevin shared here today, put it into action, right? Your team will appreciate it. They’re ready to do business differently.

Scott W. Luton [00:44:59]:

And gosh, weren’t we all inspired by Roshan Shaw’s approach here today? But act on it. No more lip service, right? The owner selling you these not words. So with all that said on behalf of the entire team here at Supply Chain Now, Scott Ludon challenging you. Do good, give forward, be the change that’s needed. We’ll see you next time. Right back here at Supply Chain Now. Thanks, everybody.

Narrator [00:45:20]:

Thanks for being a part of our Supply Chain Now. Community, community. Check out all of our programming at supplychainnow.com and make sure you subscribe to Supply Chain Now anywhere you listen to podcasts and follow us on Facebook, LinkedIn, Twitter and Instagram. See you next time on Supply Chain Now.