[00:00:00] Paul Boothe: You can't just jump right to AI and skip the data and, and again, if it's garbage in, garbage out. We've heard that for decades now. That same holds true there with data. So, you know, one of the things that we strive to do at Osa Commerce is bring that unified single by integrating all of those multiple systems that you may be using in your supply chain.

[00:00:21] Paul Boothe: It's a one source of truth that you can action upon.

[00:00:26] Narrator: Welcome to Supply Chain Now the number one voice of supply chain. Join us as we share critical news, key insights, and real supply chain leadership from across the globe. One conversation at a time.

[00:00:38] Scott W. Luton: Hey, good morning, good afternoon, good evening, wherever you may be, Scott Luton and the one and only Kim Reuter here with you on Supply Chain Now. Hey hey Kim, how you doing?

[00:00:50] Kimberly Reuter: I’m doing great.

[00:00:50] Scott W. Luton: How

[00:00:50] Kimberly Reuter: are you?

[00:00:51] Scott W. Luton: Doing wonderful. Doing wonderful. How's, how's the weather up there in Virginia lately?

[00:00:55] Kimberly Reuter: I think, uh, just like everyone else in the United States, we're uh, we're kind of chilly coming up on Memorial Weekend. I think it's gonna be a lot of bonfires for this memorial weekend.

[00:01:05] Scott W. Luton: I'm with you. You know, yesterday was such a pleasant day. It wasn't chilly here in metro Atlanta area. It was just gorgeous after the rains came through. So, uh, almost as nice though, Kim, almost as nice. As this great show we got coming up here today, really enjoyed the pre-show, we're gonna dial it in on not only how AI is delivering real impact and outcomes across global supply chain, but in particular in the third party logistics industry.

[00:01:29] Scott W. Luton: We're gonna be walking through some of the common and unique challenges in three PL world. We're gonna be sharing practical, meaningful, consequential use cases in terms of how AI and innovative leadership. Is addressing each of those challenges and a whole bunch more. And you know what? We've got a terrific, been there, done that panel to learn from here today.

[00:01:48] Scott W. Luton: Kim should be a great show, huh?

[00:01:50] Kimberly Reuter: Great show. As you know, three pls have been on the hockey stick for what, 10 years now with the growth of all these marketplaces. Three PL is a big part of logistics. You know, 15, 20 years ago it was kind of unheard of for you to sort completely outsource that, but now it is everybody's game.

[00:02:08] Scott W. Luton: So to in fact some estimates have the three PL space here in just the US alone growing to $335 billion in terms of, of market space by 2029. How about that? And there's a great opportunity to change how we do business, not just supply chain, but certainly three pl. And we're gonna talk to that here today.

[00:02:26] Scott W. Luton: Uh, and again, given your track record of success in supply chain leadership, look forward to gaining your insights as well. Time to get to work. We got a great, uh, one-two punch we're bringing in here today. I wanna introduce Lindsey Billing, executive Vice President of Technology at National Logistics Services, and Paul Booth, executive Board Advisor with Osa Commerce.

[00:02:48] Scott W. Luton: Hey. Hey Lindsey. How you doing? Good afternoon. It is so good to see you. So good to see you. And Paul, how you doing today? Hey Scott. Doing well. Glad to be here. Welcome in. Welcome in. Uh, well, Kim, we've got a great show teed up, but you know what, I'm gonna start with my patented fun warmup questions. Let's get a sense of who Paul and Lindsey are and Kim too.

[00:03:09] Scott W. Luton: Uh, so let's do this. So fun warmup question. Lindsey, I'm gonna start with you. I believe you call the wonderful city of Toronto home, and I'm pretty sure your golf clubs have been. Calling your name lately. So what's been, I think you said you've gotten out twice since, uh, last time we connected. What's been one of your favorite all time rounds of golf?

[00:03:30] Lindsey Billing: Yeah, absolutely. And I mean, golf's been a big part of my life, right? From being a, uh, a child. So I would say in golf, for me, believe it or not, is a lot about family. So my most memorable golf round that I played, so my parents used to winter in Merle Beach. And we would go down there a couple times a year and on Christmas day we would hold a family golf competition every year.

[00:03:55] Lindsey Billing: And there is a trophy and we got our names on a plaque. It'd be a little chilly usually on in December. Uh, and uh, we would go every year. And I still remember the last round, uh, that I played before, I guess grew up and moved out. And it was a wonderful day and time with the family. Uh, and, and I won the last plaque on, on the trophy.

[00:04:16] Lindsey Billing: Is, is my name. That is awesome. So Lindsey, what was the name of the trophy? Do you remember? Uh, we didn't give it a name. It was the billing, uh, Christmas Classic, I believe. Oh, I like kids. What was, uh, displayed on the trophy? I

[00:04:29] Scott W. Luton: like it. What special memory. We're gonna have to see some pictures, but I appreciate you sharing that, uh, special part of your journey.

[00:04:36] Scott W. Luton: Paul, a little different question for you. Uh, now we have learned Paul, about your passions for really good tacos for real country music and those Dallas Cowboys, how about them cowboys as folks say. So what's been one of your favorite all time cowboys fan experiences?

[00:04:56] Paul Boothe: Wow, Skype. You have to go back a lot of years.

[00:04:58] Paul Boothe: It's been some lean years for the Cowboys lately. We've had a lot of heartbreak. But you know, I think if I go back to uh, kind of when I was just outta college, you know, diehard Cowboys fan, and they made a change with the legendary coach Tom Landry, and we were all skeptical of what would happen, but the new ownership.

[00:05:17] Paul Boothe: He hasn't been that good in more recent years, but, uh, brought Jimmy Thompson on board and uh, Jimmy took us right to the Promised Land in two years. So in 1992, I think that famous quote that you just said, after we won the, uh, the first of of three Super Bowls there during that run, and Jimmy's in the locker rooms said, how out then cowboys, that's sticks with me.

[00:05:40] Paul Boothe: That's a good memory.

[00:05:41] Scott W. Luton: I'm with you Paul, Jimmy Johnson, one of the greatest, uh, sports personalities of our, of our generation, probably. And did you know he just retired from Fox and he was there 30 years. Where does Tom go? How could he possibly be at Fox Sports for 30 something years? That's crazy. Amazing.

[00:05:56] Scott W. Luton: Well, Lindsey and Paul, I appreciate that. And Kim, you're not getting outta this question. Uh, I love hosting these shows with you. Now, I know your busy travel schedule may not allow you to enjoy it yet, but is it, uh, oyster season up in beautiful Virginia yet?

[00:06:11] Kimberly Reuter: So interesting enough, we'll do a small history lesson here on oysters.

[00:06:15] Kimberly Reuter: So traditionally you only bought oysters in months that had an R in them. Okay, so May, June, July, August, no oysters, and that was really around refrigeration. And so they didn't typically pull up oysters during that time. It's also when the oysters start to get a little thin, because during the summer they don't eat as much as they do in the winter.

[00:06:33] Kimberly Reuter: But nowadays you can buy oysters all year long. They are great for the hot, big holiday weekends that are coming up for summer, just throw 'em on the grill outside. Easy peasy.

[00:06:44] Scott W. Luton: Oh, I love it. I love it. I love grilled oysters. So let's do this. I'm a big fan of gaining as much context as we can in this ever fast moving world.

[00:06:53] Scott W. Luton: So, Lindsey, uh, let's start there. Tell us briefly, if you would, about yourself and about your organization. NLS.

[00:07:00] Lindsey Billing: Absolutely. So, uh, myself, I'm a computer engineer by trade. I've been in technology for my entire 25 plus year career. Uh, moved right from, uh, being a coder to, uh, being the head of it. First 10 years was in consulting.

[00:07:19] Lindsey Billing: Uh, I was a, a number of the big four. And then I've been in, uh, industry for the last, uh, 15 years, uh, focused on retail. In progressive roles all over the technology space. I like to think of myself as a business leader first. Uh, who knows too about tech? You know what I always strive for? I. I live in the GTAI have four kids, two in elementary school, two in post-secondary school, so very busy household for me.

[00:07:49] Lindsey Billing: National Logistics Services is Canada's premier logistics provider, uh, focused on the lifestyle space, lifestyle being fashion, apparel, footwear accessories, sporting goods item for the home. Uh, you know, a bunch of different areas there. We focus on omnichannel, wholesale, uh, retail delivery, and e-commerce.

[00:08:08] Lindsey Billing: We have large global brands, but also we'll talk a little bit about smaller brands In the, in the heavy growth phase, we are growing that out of our business significantly. Uh, we focus on not just Canadian, uh, delivery, but we also, uh, focus on the US. And global reach for our customers From a supply chain perspective, you know, one of our key differentiators is understanding the Canadian market, so whether it be Canadian malls, Canadian geography, retail, and the unique needs of lifestyle brands.

[00:08:39] Scott W. Luton: Mm. Love that Lindsey. And, and congrats on all the growth there. NLS I think I saw also it's been awarded a great place to work, which I love seeing, uh, culture is, uh, you know, a big part of this, uh, uh, journey we're all on. So appreciate that, uh, context, Lindsey. Yeah. Uh, alright, Paul, uh, wanna do the same thing?

[00:08:56] Scott W. Luton: I love, I really enjoyed getting to know you better, uh, through some of the pre-show sessions. So tell us briefly about yourself and what Osa does.

[00:09:04] Paul Boothe: Sure. Thanks Scott. I've got over 20 years of supply chain experience, and most of that is primarily in the three PL and four PL space that we'll be discussing here today.

[00:09:14] Paul Boothe: I began my career with Ryder on the supply chain side and had escalating roles of responsibility. I. In 2016, I made a move over to SPO Logistics, who was really kind of in that growth phase. It just started in 2011 through a series of multiple acquisitions and moved over to an executive role with them, became part of the leadership team.

[00:09:35] Paul Boothe: And in 2022 we spun a heart. So we did a separately, uh, publicly traded corporations. So. Really just some really exciting kind of background and, and large three pls that I've worked with in the past. Just about a year ago, I joined Osa Commerce as a member of the executive board. And the reason I joined Osa is exactly what we're talking about today.

[00:09:57] Paul Boothe: It's, uh, their delivery of AI in this three PL and in the shipper space. And, you know, one of the things that OTA is we built an AI powered unified commerce platform that empowers shippers and brands and three pls. With that integrated data intelligence to manage their supply chain. So I think at Osto we are really taking it to the next level.

[00:10:19] Paul Boothe: And just about me personally, my wife and I, I spent 50 years in Texas, the and five winters now in the Chicago suburbs. That's how I kind of cal by Chicago time. But. We love it here. I have three kids, a son who graduated from Purdue, a daughter who last night, graduated from high school. She's gonna be going to, uh, Tennessee, Chattanooga to continue college, and then I'll have a senior next year in college as well.

[00:10:44] Paul Boothe: So, little bit about me on the personal front. I.

[00:10:46] Scott W. Luton: Love that Paul. And congrats to your daughter. Uh, that's exciting, exciting times. Uh, appreciate that. Uh, now Kim, did you hear one of the things that Paul mentioned there, Paul had mentioned unified platform, and that reminds me of you and ITY, the song. By the famous Queen Latifah, who is more known for her, uh, her acting than her rapping these days.

[00:11:08] Scott W. Luton: But who'd a thunk? She was a supply chain tech pioneer. But all of that aside, Kim, we got quite the panel between Paul and Lindsey. Huh?

[00:11:16] Kimberly Reuter: We do. This is gonna be great.

[00:11:18] Scott W. Luton: So let's do this, Lindsey. Uh, as we get further and further in this conversation, I wanna start with we're really in this golden age of supply chain techs.

[00:11:25] Scott W. Luton: Fascinating to see. Uh, then we got plenty and plenty of, of miles ago before we sleep, so to speak. But it's amazing to see what organizations are already doing with artificial intelligence and the role it's playing in modern day global supply chain. So, Lindsey, what are some of your observations in that regard?

[00:11:42] Lindsey Billing: So I think what I've seen in the supply chain space of several things. One is there's a lot of work that needs to be done in the technology side of supply chain. I think traditionally, you know, it hasn't been the most technology forward industry, but there's been great strides have been made over the last, uh, five years and, and more.

[00:11:59] Lindsey Billing: Um, supply chain is very technology dependent, so when you're moving goods from A to B, you are heavily dependent on technology to make it happen. It's also very heavy on integration, so integration between organizations, integration with geographies, uh, you know, to move goods, you, you need heavy integration.

[00:12:19] Lindsey Billing: Yeah. And the, it's also a data rich industry. There is a wealth of data in this industry. Data underpins, uh, supply chain, uh, in terms of moving goods. And as we're gonna talk about today, since AI is underpinned by strong data foundation, I think, you know, there's unique opportunities in the supply chain space around ai.

[00:12:41] Scott W. Luton: Lots and lots of opportunities. And partially to one of the great points you made we're such a data rich. Industry. And that really opens up so many opportunities we can, that we can use and leverage out there to change how supply chain's done, so to speak. Uh, Paul, your observations on how you're seeing AI leverage right now in global supply chain?

[00:13:01] Paul Boothe: Yeah, Scott, I think I would echo some of what, uh, Lindsey should share. You know, I think AI is still largely untapped. As a tool in global supply chains. There was a Gartner survey last year that, uh, came out that 64% of supply chain leaders are either implementing or planning to implement generative AI over the next 12 months.

[00:13:20] Paul Boothe: Uh, but candidly, I think some of the uses that we see are very basic in how AI is being used to the supply chain, and it's really just picking some low hanging fruits. It's one of the benefits of working with three pls, I think. Three pls are really, um, a step ahead in this, uh, head of shippers because they're able to be focused on that.

[00:13:40] Paul Boothe: Um, but for the companies that aren't using ai, I think there's huge benefits there with cost reduction, uh, decreased inventory levels, and really just to prove service levels. So it's something we're gonna see continue to grow and grow. I think it's probably, you know, the popularity of the topic today.

[00:13:55] Scott W. Luton: Well said, Paul. And, and before I get Kim to comment on what she's hearing, what she's seeing, uh, uh, I came across some research, uh, earlier this week from about 500 supply chain professionals and leaders across the globe, and it pointed to one of the common themes was a lot of organizations are finding it challenging to build a business case for AI deployment in supply chain.

[00:14:16] Scott W. Luton: It kind of runs counterintuitive, but at the same time I've talked with lots of folks that kind of are still looking for that, right. Targeted and measured gear. Mm-hmm. Kim? When you heard Lindsey and Paul's observations there, your thoughts.

[00:14:29] Kimberly Reuter: So everyone's talking about AI and supply chain. It's the latest, greatest.

[00:14:33] Kimberly Reuter: We kind of went through this with RFID and blockchain. All of a sudden, it's the greatest technology and everybody wants to use it. There are great use cases out there for AI and supply chain. There are also some not great. Use cases for supply chain and ai. I think the biggest, uh, opportunity is predictive consumer predictive behavior and consumer demand.

[00:14:55] Kimberly Reuter: I think that's the biggest opportunity right now we see in ai. Um, I've heard some other supply chain professionals echo probably what you've heard in that, you know, don't use a hammer when you can use a wrench. We don't need to predict those, you know, and the things that we know. We don't need to apply AI to those.

[00:15:14] Kimberly Reuter: It's the things that we have a hard time measuring, like consumer behavior. Um, and a little bit to what Paul said is once we can understand consumer behavior, we can understand demand, we can manage inventory better, we can do better placement and things like that. But just to go get AI to say, I'm gonna use ai, my supply chain, you need to be specific.

[00:15:32] Scott W. Luton: Well said, well said. Um, you gotta preach it louder to the folks in the back. Now we're gonna dial it more in on the three PL industry. Right. Uh, Kim and I both were talking about the, the sheer growth, uh, which is of course fuel fueled by a number of different things from e-commerce to the complexity of modern day consumer demands, cross border shipments, all that stuff.

[00:15:54] Scott W. Luton: So, speaking of challenges, Lindsey, when you think of challenges both common and unique within the three PL space, what comes to your mind?

[00:16:02] Lindsey Billing: Yeah. So I think on the three pl front, there are a number of challenges that we experience and we're experiencing today, but also in the past, uh, economic uncertainty and also in the most recent, uh, weeks and months.

[00:16:16] Lindsey Billing: Tariff uncertainty and cross-border shipment is a challenge that three pls need to overcome. Uh, in particular, you know, lifestyle products are usually wants, not needs. So, you know, we have to be in really tight partnership with our customers, uh, you know, around, uh, forecasts, uh, et cetera. When there is uncertainty, it produces costs, margin, pressure, you know, so one of the things three pls need to focus on is around costs, margins, et cetera.

[00:16:43] Lindsey Billing: Uh, as well, one of the challenges for three pls is, and this is where AI can help huge, in a huge way, is the risk of being seen as a commodity and not a growth engine. So at, at NLS we're really focused on, you know, we, we are, we are, we're not a commodity service. We provide a. We are a growth engine and partnership, uh, with our customers to enable them for success and help them grow.

[00:17:06] Lindsey Billing: So, and, and AI can, can help on all of those fronts as we're gonna talk about today. There's my thoughts on, on those challenges.

[00:17:15] Scott W. Luton: I like it and I like your mantra. Don't, don't get commoditized, folks. Uh, we do way too much. We create way too much value. Don't get commoditized. Hall, similar question for you.

[00:17:25] Scott W. Luton: Challenges in three PL space, both common and unique.

[00:17:28] Paul Boothe: Yeah, I think one of the challenges is, is no two days are the same. We never know what we're gonna walk into each day. And, uh, you know, that's part of the excitement of what we get to deal with as well in the three PL space because we're able to solve those challenges and we're able to bring unique solutions on how we, how they're handled every day.

[00:17:47] Paul Boothe: Uh, Lindsey just mentioned all the uncertainty right now with the macro, what's happening with tariffs and how that really, uh, things are fluctuating, not even by the day, but sometimes just by the hour right now. So I think the uncertainty and just, uh, one of the challenges I. Both unique and then common is just not knowing what

[00:18:07] Scott W. Luton: Paul, that's an excellent comment.

[00:18:08] Scott W. Luton: And Kim, it reminds me of the old saying, uh, if you don't like the weather in Georgia, uh, wait for an hour. Uh, and it's kind of like, if you don't like the current challenges or the current flavor of global supply chain, oh, just wait maybe a minute. Uh, Kim weigh in on the challenges with Lindsey and Paul shared.

[00:18:25] Kimberly Reuter: So Lindsey touched on something that you know, I'm very passionate about is, you know, supply chain is the customer experience. It is revenue generating, and it is always looked at as an expense. It's always at the bottom. It's never included in csat. Nobody talks about customer experience and supply chain.

[00:18:43] Kimberly Reuter: And Lindsey just hit the nail on the head in that if you leverage your three pls and your supply chain partners correctly, they can become revenue generating partners.

[00:18:53] Scott W. Luton: Well said. Excellent point there. Very true. Now I'm gonna share some good news. We're gonna talk about a few powerful AI use cases, right?

[00:19:03] Scott W. Luton: It allows us to change how, how things are done, delighting customers, and making life easier on our team members, right to, to find more success each and every day. So I think we're gonna start with warehouse automation. So, Lindsey, tell us more here.

[00:19:18] Lindsey Billing: Absolutely. And I mean, warehouse automation has gone through a journey, uh, you know, over the last 20 years, right?

[00:19:23] Lindsey Billing: You know, it starts with robotic process automation, RRPA, uh, progresses to, uh, machine learning and predictive analytics models. And, you know, now it's getting into the generative AI and the large language models. But I think warehouse automation is all about, you know, increasing speed, accuracy, reliability.

[00:19:44] Lindsey Billing: Redeploying staff to new roles and exciting roles and value add roles and warehouses are complex and, and often retrofitting. Uh, you know, AI into warehouses as many, uh, supply chain organizations do can be very, uh, challenging. So here at NLS, we're firing at all cylinders here. First is, you know, a new 600,000 square foot warehouse that we are, uh, building, um, fully automated.

[00:20:09] Lindsey Billing: Not only with conveyance and unit sortation, but also with Exotech goods to person, which is a great partner we've been working with that uses AI to help with that goods to person. We're also introducing autonomous maneuverable robots AMRs into the warehouse, which use AI to be able to shuttle goods, uh, around the warehouse, uh, in an autonomous way.

[00:20:30] Lindsey Billing: We also partnered with Six Rivers. We use their Chucks, which are, uh, these automated carts that move around the warehouse and increase peaking accuracy. Uh, and we've been a first Canadian partner with Six Rivers. I. Then we're also, uh, currently, uh, helping and piloting and partnering with a company called the Rubik and a Freedom Pick.

[00:20:51] Lindsey Billing: And this is basically a fully autonomous case, case pick and case removal robot that will 3D maps the entire warehouse and can literally dig out cartons and replace cartons within our warehouse and in autonomous. Way, uh, all using AI and warehouses are complex spaces and, and therefore, automation can be a challenge and AI can be a challenge as well, but AI thrives in, in, in that kind of space.

[00:21:22] Scott W. Luton: Yes. Mm-hmm. Okay. Paul, my son's favorite superhero of all time is Batman, and he's got all the gadgets, all the automation. What Lindsey describes to me at least, is if Batman were to build a warehouse, that would be the warehouse that would be built. I mean, goodness gracious, innovation everywhere. Paul, would you hear there, and you can talk about warehouse automation

[00:21:42] Paul Boothe: now, a lot of the same things that Lindsey just touched on.

[00:21:45] Paul Boothe: You know, robotics is huge right now. I had a chance, uh, back in March to attend a conference here in Chicago, proma 2025, and I was just blown away by seeing all the automation that's happening in the warehouses. You know, Amazon employees, over 750,000 robots in their dcs and fulfillment centers. And the robotics, just as Lindsey shared and how they're using an NLC are for a variety of different things.

[00:22:13] Paul Boothe: The use of drones is something that we're really seeing increasing for inventory management cycle counts. Uh, that's really starting to gain traction. And there's multiple drone companies that I saw displaying in their growing and what's happening there, you know, I think what's important is that more than just the automation replacing the work.

[00:22:32] Paul Boothe: Is the application of the machine learning that's happening through the robotics to improve the functions of the warehouse. You know, sometimes it may be changing the layout or the footprint of the warehouse to focus more on fast moving SKUs or providing predictive analytics to reduce the stockouts or overstocks.

[00:22:52] Paul Boothe: We've already hit on this multiple times. The power of the data from these machines and the decision making they employ, that's really the difference maker in what's happening here.

[00:23:02] Scott W. Luton: Yeah, great. A lot of good stuff there. Uh, Paul and Proma, by the way, over 50,000 people at Proma 2025 back in, um, early March.

[00:23:12] Scott W. Luton: Uh, Kim, Lindsey and Paul both shared a lot of good stuff there. When it comes to the really cool, innovative ways we're finding to automate warehouses here. What'd you hear there, Kim? I.

[00:23:23] Kimberly Reuter: So when we talk about AI and warehouses, you know, people get really excited and, you know, they go to the drones, right?

[00:23:28] Kimberly Reuter: Like, we want drones and you know, we want all the fancy, uh, lighty, gadgety stuff. And it is cool. A few years ago I had an opportunity to go to one of Walmart's newest facilities in Pennsylvania, and it was really like being on Star Trek. Like I felt like the board made sense to me. Like that's all I could think.

[00:23:43] Kimberly Reuter: Why I was there was the Borg. Um, I mean, they're wild looking. If you've been in an automated warehouse, they're, it's incredible to be in one, you know, stacks that go all the way to the ceiling. Like, that's incredible. But, you know, two easy ways to kind of get AI working in your warehouse without, you know, getting drones is one inventory placement.

[00:24:04] Kimberly Reuter: And Paul touched on this a little bit, um, as well is relocating fast moving items, seasonal items. When we look at, you know, companies that Lindsey works with, it's very seasonal. Uh, something might be a hot buy. It ends up on Oprah list, like you never know. But being able to predict when an inventory is gonna be a hot seller and then relocating that to a high pick location.

[00:24:26] Kimberly Reuter: The other thing is inventory levels. Everybody struggles with it. I hear horror stories all the time about companies that would be ashamed if I said their name, that you know, have 10 years of inventory in warehouses. Right? And you're like, what? You know, the buyers just keep buying and then all of a sudden we have 10 years worth of inventory stocked up here, which in this situation, our current JR situation may not be a bad move.

[00:24:52] Kimberly Reuter: This is another area where. Inventory levels using ai. Another easy way to plug into AI is managing inventory levels with predictive analytics.

[00:25:01] Scott W. Luton: Well said, Kim. Inventory's cool again, and absolutely critical as you're pointing out. Okay, so where are we going next? That was the first I. Kind of use case we're gonna dive into here today.

[00:25:12] Scott W. Luton: Warehouse automation. The second one is kind of a big bucket, Lindsey. Demand forecasting, predicting that outbound volume. And of course data utilization's not good enough to have it. We gotta utilize it. Your thoughts, Lindsey?

[00:25:24] Lindsey Billing: So from a demand forecasting perspective, so this is a great opportunity for, uh, NLS and our customers to partner together on initiative, on an initiative because we both gain value from predicting outbound volume and predicting the warehouse.

[00:25:39] Lindsey Billing: So within NLS, for example, if we can predict volume, if I know how many cartons are going to, how many outbound. Pick tickets we're gonna get tomorrow. Then I can staff my warehouse in an optimal manner that allows me to reduce costs, which I can then, uh, help pass on to the customer. So labor planning, uh, is a big part of running a warehouse and being able to predict outbound volume.

[00:26:04] Lindsey Billing: I. But for our customers, we can use the same predictive model to predict inventory, position, predict, skew trending, predict, you know, revenue projections. There's a number of things that we can do, and we have been, uh, running AI machine learning models, uh, because, you know, a three PL is a wealth of data.

[00:26:23] Lindsey Billing: Every product that we have, uh, that a customer has shipped out, uh, or we have shipped out on their behalf to storage, we have it in our. Data, uh, ecosystem. So we are in a unique position to partner with customers, uh, using machine learning models to, to predict the future.

[00:26:41] Scott W. Luton: Sounds like it. No, no wonder. Such a great place to work.

[00:26:43] Scott W. Luton: I bet it's a very fulfilling, rewarding to really change how business has done. And Paul, one of the things you touched on there, as I come to you for your comments that I love and I see every day. Evidence of every day is how modern technology to include ai, of course, is helping us to truly predict the future so much better and see around corners.

[00:27:02] Scott W. Luton: The trend for years now is get out of solely reactive mode and truly be proactive. Kimberly talking about reading your customer's minds, I love that we're able to do that more now. The never before. Paul, your thoughts here?

[00:27:14] Paul Boothe: No, I agree. Being able to look in the future a little more of a crystal ball. I'm trying to get AI to predict when the cowboys are gonna win the next Super Bowl, and it hasn't done that for me yet, but.

[00:27:24] Paul Boothe: Now I do think, Scott, this is one of the biggest areas of opportunity within supply chains. You know, we've talked about the data and the use of the data, but most shippers, one, they just don't have good access to that data. This is where I think three pls, just like what, uh, Lindsey and NLS is doing, bringing in advantage because they have the data.

[00:27:43] Paul Boothe: They know how to use the data, they're able to, uh, help navigate it. And then for three pls, just like uh, NLS, you have partners like what we do at Osa Commerce. We're able to take that, we're able to simplify the comprehensive data integration and then allow tools that can crunch that into the visibility into the predictive analytics that we just talked about.

[00:28:06] Paul Boothe: Some of the things that Lindsey mentioned, their historical sales patterns. I. You know, market trends, being able to understand what happens there, even weather patterns. You know, one of the things with my background in, uh, kind of last mile home delivery, big and bulky into a consumer home social media sentiment is very important there.

[00:28:24] Paul Boothe: You're able to put AI really to understand. That's something you wouldn't even thought about 20 years ago is what's the impact of social media? AI now is able to do that, be able to react and respond quickly to any trends and things that are happening there. So, you know, he talked about, I love this, being able to use the data for dynamic labor management kind of resource allocation.

[00:28:47] Paul Boothe: And it reminds me of a quote, one of my mentors in the industry, Steve sensing. Steve is president of Global Supply Chain at Ryder, and I remember probably 15 years ago. Steve had the quote, he who holds the data wins. And I've never forgotten hearing him say that for the very first time. And there's truth in that.

[00:29:06] Scott W. Luton: Kim, so much to comment on there, but I'll, I'll pick up on Paul's last point. Um, again, it's not good enough just to have data. We've gotta be able to harness it and control it and, and leverage it and get returns with it, right? And serve the customer better and serve our teams better. So it's really, uh, an imperative, I think, in doing global supply chain here in 2025.

[00:29:26] Scott W. Luton: But your thoughts, Kim, what Lindsey and Paul were sharing.

[00:29:29] Kimberly Reuter: I agree that everything that they have to say, um, I'm gonna take a little further downstream though, when we talk about predictive analytics, consumer buying, warehouse management, labor management, all very important. But this also gives us an opportunity to do something else, which is contract negotiations with your carriers.

[00:29:46] Kimberly Reuter: So I can't tell you how many stories I have about, you know, coming into Christmas. The merchants decide we need a little extra sales, we're gonna mark everything down, you know, on December 20th, and as you guys know, there's a lot of capacity at December 20th. Right. Just planes laying around, trucks on the side of the road.

[00:30:07] Kimberly Reuter: No. So they didn't tell anybody. Uh, the warehouse gets completely overloaded. Now the warehouse was able to pull it out. Right. But. No trucks not gonna happen. Large portion of those orders actually ended up getting canceled because they weren't gonna make it by Christmas. So that's a great example of where we can use AI to try to predict that we may need more trucks than we thought we might.

[00:30:31] Scott W. Luton: Right? And taking a unified approach to prevent those gaps in how we plan, communicate and execute. I guess. Put it simply. Good stuff there, Kim. Um, alright, uh, we're about to hit the third. AI use case, technology use case. So, Lindsey, tell us what you're doing when it comes to customer service.

[00:30:49] Lindsey Billing: You know, obviously customer service, uh, and the relationship between us and our customers is absolutely paramount.

[00:30:56] Lindsey Billing: And I wanna start on this one, just talk a little bit in my, uh, in the intro about National Logistics Services. I talked about how we have, uh, customers that are global. Established brands that we work with very large. Um, but we also have an emerging, we call them emerging brands, uh, business, which is, uh, smaller brands that are on the growth pattern and the growth scale.

[00:31:20] Lindsey Billing: And uh, I want to talk about that. You know, in the case of. Customer service specifically in the area of emerging brands. And I should point out that from a, a warehouse management platform, uh, this area of emerging brands, growth brands is exactly where we partnered with OA commerce, uh, in terms of their lightweight, uh, warehouse management and visibility platform.

[00:31:39] Lindsey Billing: But customer service or these large global established brands versus the smaller emerging growth brands looks quite a bit different. So for larger established brands. We often have dedicated customer teams supporting and interacting with those brands and providing the great service that we do. But for the emerging the smaller brands, we have to look at a different customer service model.

[00:32:03] Lindsey Billing: You know, we could have 10, 20, 50, a hundred of these brands. How do we give them? The best service possible, and that's where we are looking at AI in terms of automated level one support. So if we can connect AI to the right data sources, then each of those emerging brands, each of those smaller growth oriented companies can feel like they have individualized customer service.

[00:32:29] Lindsey Billing: For that level one support. And that is very exciting because again, we talk about differentiation within the three PL space and individualized customer service, uh, and having the right answers and questions and be able to take the right actions for even the smallest of brands is a true differentiation for a three pl and that's where AI can, can absolutely help.

[00:32:51] Lindsey Billing: So I'm, I'm very excited about that aspect. I

[00:32:54] Scott W. Luton: love that Lindsey. And quick comment, I kind of subscribe to the view that we're all in customer service and organizations. I kinda like that, but from a formal standpoint, those customer service teams that touch our customers, you know, every hour, if we can free use technology to free up their time.

[00:33:10] Scott W. Luton: I mean, imagine that the creative ways that they come up with the beautiful human element to serve and enhance that customer experience. Uh, Lindsey, I love what y'all are doing, Paul. Uh, what else are you seeing customer service wise?

[00:33:23] Paul Boothe: Well, I think one of the things that, just the power of, of kind of BI tools right now, from a customer service perspective, being able to just hand that to someone at their fingertips.

[00:33:33] Paul Boothe: I can think of a demo. When I was at XPO logistics with a managed trans team. We went into a large fortune. I. 500 shipper and had preloaded some data just for this demo for them, some of their actual data into a tool, showed it to them on the tablet, and their senior VP of supply chain just stopped down the entire meeting to work through the BI tool.

[00:33:55] Paul Boothe: Called this whole theme around the tablet, said, look at this. I told you this location has been over cost for us, and they have the data showing that right here. Another area, I think with customer service that we see, your chat bots and virtual assistants, there's a lot of that and sentiment is starting to change here.

[00:34:12] Paul Boothe: You know, I used to be incredibly anti-bot for customer service. I would call into a number and I would try and punch to talk to someone. Don't let me talk to this machine. The current generations that you're seeing of AI and uh, how they're powering customer service are much more user friendly. The speed and the accuracy to assist us is great.

[00:34:31] Paul Boothe: Then this is a big, but there are definitely still some sensitive areas where customers want that human interaction. So I think there has to be a balance. As we look to generate ai, we look to replace some of maybe the manual work that's being done. You have to have the right balance of where it fits and where you still need that, that kind of human touch.

[00:34:51] Scott W. Luton: So true Paul. And you know what? The last time I was hung up on in a customer service call was with a human, not a bot. So up here's pluses and minuses. Yeah, just happened yesterday, Kim. Uh, alright. So Kim, customer service, massive opportunity to share your thoughts.

[00:35:06] Kimberly Reuter: First of all, we should have started with the customer.

[00:35:08] Kimberly Reuter: I'm just gonna say that, you know, we touch on two things and you know, with my customer, I came out of e-commerce. Obviously working at Amazon and, and being an architect for Amazon, I always think of the customer as being the end customer, the consumer. So when I think about AI and how we can help the consumer is having the inventory available, having it where they can get it in a location that they can get it the fastest way possible.

[00:35:30] Kimberly Reuter: While being the cheapest shipping, uh, method available. Those are the opportunities that I see at AI can make customer experience better. And that goes into predictive AI and, and all the things we've talked about, like where does it need to be located? Where's it most likely to ship out of? Is it more likely to be paired with another item?

[00:35:47] Kimberly Reuter: Do we have them both in an fc you can get it together. There's all of these aspects that. You know, when we talk about supply chain and direct to consumer, it's a million little tiny decisions that are made on almost every single order. And AI can help make that better, cheaper for the company, and a better customer experience.

[00:36:04] Scott W. Luton: Love that. Uh, and, and yes, Kim, I love your passion for starting with the customer. Uh, uh, but, uh, hey, third is better than, better than fifth, right? It's,

[00:36:13] Kimberly Reuter: we talked about him

[00:36:16] Scott W. Luton: so. Lindsey, as we kinda wrap this section, I really appreciate the use cases you shared. You and Paul and Kim all spoke to. If you wanted to drill down or spike the football on one key benefit or outcome produced by successful, measured, targeted, uh, outcome producing AI deployment, especially for three pls and and their customers, what would that be?

[00:36:36] Scott W. Luton: Lindsey?

[00:36:37] Lindsey Billing: I think, uh, terms of, you know, the most significant benefit for a three pl uh, is being centered and focused around the customer and leveraging ai, uh, for that. And it's all about service level. It's all about, you know, especially the prediction, uh, aspect of it is huge. We never know what's gonna happen tomorrow.

[00:36:59] Lindsey Billing: Unless AI can help us, and I do wanna underscore, especially in NL S'S space, uh, we talked about a couple times handling peak seasons in the lifestyle space. For example, we see, you know, up to seven x or eight x volumes during peak. And you know, a lot of our customers will say their entire year comes down.

[00:37:23] Lindsey Billing: To two or three weeks in the later part of the year. And being able to beat and exceed SLAs, being able to predict what is gonna happen in order to handle those peak seasons. Especially, you know, if we have multiple customers with a similar peak profile, any kind of, uh, AI that we can use to manage the peak season, that that's game time or for three pls in the year, it's.

[00:37:49] Scott W. Luton: Well said, well said Lindsey. And you're gonna need one of those super innovative Batman warehouses that you're building, uh, Lindsey for folks you have, reach out to Lindsey for more details. I wanna get a tour of that space when y'all open that up, Lindsey. Um, okay. Paul, uh, you know, same question. What's a final outcome?

[00:38:06] Scott W. Luton: What's the, so what here, Paul?

[00:38:08] Paul Boothe: I think for me, for three pls, it's, let's not try and boil the ocean. Going back to exactly what Kim said, the customer, what Lindsey just mentioned. You know, build a SWOT analysis and say, where can our focus be right now? You know, let's not just throw AI in so that we have this shiny new tool that we can show off.

[00:38:27] Paul Boothe: Where is it actually going? Provide benefit and value and start there. You know, if it's something that you're not doing today or you're just doing a little bit, let's figure out where. You can partner with your three pl or that three PL can grow to really provide benefit within your supply chain. So, uh, I think that's kind of what comes to mind for me is, you know, we talked a lot about it, a lot of different areas.

[00:38:50] Paul Boothe: You know, don't rush to your leadership based off this call today and say, oh my gosh, we can do all these, that's list of 20 different things that I heard, um, from Scott and the team. You know, figure out where can you, you make the biggest, uh, impact and, and just begin there. That's right. Absolutely.

[00:39:07] Scott W. Luton: Hey, do a pulse check on the customer, do a pulse check on your team members.

[00:39:10] Scott W. Luton: See what their biggest pains are. Right. Might not do it all. And, and to Paul's point, not, you know, overnight, but hey, taking one big step and making life easier one step at a time. There's real power there. Uh, Kim, your quick comment here on what Lindsey and Paul were talking about.

[00:39:27] Kimberly Reuter: I've been working with supply chains for over 30 years, and to this day, still the most unpredictable thing is the end consumer.

[00:39:35] Kimberly Reuter: And so using AI to predict what the customer is gonna buy, where they're gonna buy it, and when they're gonna buy it will feed everything backwards. Yep. Inventory levels, where you put it, how much you buy, when does it ship, blah, blah, blah, blah. But what is so interesting is, in my opinion, everything else in supply chain is pretty predictable and controllable except the customer.

[00:39:58] Scott W. Luton: Ooh. I like that. I like that. Uh, so Kim, Paul and Lindsey I was talking with, we had, in fact, we featured Vinta. He is, he was AI before AI was cool. He's, he's a truly a guru when it comes to artificial intelligence, and he made a great comment one time to me. So many organizations will jump to ai. But they jump over data and their big opportunities with data no matter what, how you use it and what technologies you use it as long as you're using it.

[00:40:26] Scott W. Luton: And that's really, really important and that's wanna get, want to get Lindsey and Paul to weigh in here the value, the immense value of the data, but not just data. The importance of clean and connected data. Lindsey, your comments here? Yes.

[00:40:39] Lindsey Billing: When I joined NLS over four years ago. We had work we needed to do on the data front because clean connected data, you know, human intelligence feeds on data, right?

[00:40:49] Lindsey Billing: Artificial intelligence is no different. You can have so much more power in AI if you have clean, connected data. So, you know, we have and have implemented robust data strategy. Uh, within NLS we, we partnered with Snowflake. Uh, as our data ecosystem, um, we not only have, uh, a lot of our data in Snowflake, but we also work on harmonizing and connecting with other data sources so we can present a unified view to the ai.

[00:41:19] Lindsey Billing: Uh, because, you know, you, you get quick, much more quick to value. Uh, in the AI space with clean, connected data, and you know, now we're working not only with Snowflake from a underlying data, but also the AI offerings and the other capabilities. And it's amazing how easy it is to implement and realize value from ai.

[00:41:39] Lindsey Billing: Uh, if you start from a, a strong data foundation. Uh, versus not.

[00:41:45] Scott W. Luton: Well said, Lindsey. Well said. Not just clean and data hygiene in mind. It's gotta be connected. That's how we, that's one of the really big ways we harness and use all this data we have in our fingertips in this crazy age. Uh, Paul, your quick comments.

[00:41:59] Scott W. Luton: I.

[00:42:00] Paul Boothe: No, I agree. I think having that unified source, one source of truth that you can count on for the data. You know, I've been in, uh, you know, boardrooms with Fortune 500 companies, where you have customer service brings one set of data, maybe the ERP or information. You've got the warehouse team bringing what's from a WMS transportation team bringing what's in the TMS and there's really no integration.

[00:42:24] Paul Boothe: And they all have different data points that they're trying to argue. Or used to support. You know, when you have a company like Osa Commerce that can integrate all of those different systems into one platform and give you that unified source of truth, the one source of truth for data, then that really gives you the basis to action, uh, to improve upon.

[00:42:44] Paul Boothe: You can build the AI upon that, but I love what you said, Scott. You can't just jump right to ai. And skip the data and, and again, if it's garbage in, garbage out, we've heard that for decades now. That same holds true there with data. So, you know, one of the things that we strive to do at Osa Commerce is bring that unified single load by integrating all of those multiple systems that you may be using in your supply chain into one source of truth that you can action upon.

[00:43:12] Scott W. Luton: Paul, I like it. The single source of truth is not like the lochness monster. It can really be a real thing. Uh, Kim, it's what we're hearing. There some good news there. Your quick comment, Kim.

[00:43:22] Kimberly Reuter: You have to have a single source of data and then, and I worked with a company many years ago, and this is gonna floor you, but from product page to checkout, they hit six different tables.

[00:43:34] Kimberly Reuter: None of them were the master data. Each one claimed they were the master data. Three of them were around inventory. We had a 16% cancel rate. They weren't integrated, they weren't real time. So if you take that situation and you put AI on top. You're just gonna screw up faster and faster and faster and faster and faster.

[00:43:54] Kimberly Reuter: You're just gonna make a big mess faster.

[00:43:56] Scott W. Luton: Well said Kim. So let's do this. Uh, Paul, you were just talking about Osa commerce. Uh, let's make sure folks know how, just how easy it is to get started working with Osa. Uh, your thoughts there, Paul? I.

[00:44:07] Paul Boothe: Super easy. Osacommerce.com. Osacommerce.com. If you go to that website, you know, you'll see right at the top a request demo button.

[00:44:18] Paul Boothe: You can click right on that. There's a contact us page there. You know, Lindsey found us, we're able to work with NLS. So, uh, we're easy to find and, uh, easy to work with.

[00:44:28] Scott W. Luton: Love it and you're gonna enjoy working. Uh, I don't go as far back with Paul, but du and the team and then Paul we're instant fan. You're instant second cousins now, right?

[00:44:37] Scott W. Luton: That's how it works here at Supply Chain Now. But you're gonna love working with Paul and the Osa team, so check that out, Kim, before we make sure folks know how to connect with Lindsey and Paul, and we're gonna be sharing a great report here that I really enjoyed earlier. Um, what is your patented one key takeaway from a great conversation here today, Kim?

[00:44:56] Kimberly Reuter: Data. As always, you gotta start with good data and then go through AI slowly, find a couple places that you think that you can apply it, and then test and learn. Don't get all crazy and go straight for the drones, I.

[00:45:09] Scott W. Luton: Mm. Don't get all crazy and go straight to the drones. There is so much opportunity, especially, again, I hate to keep pounding, but in this golden age of supply chain tech, it really allows us to harness control and weaponize in a good sense.

[00:45:24] Scott W. Luton: Mm-hmm. That all the data that we have within our organizations these days. Okay. Lindsey billing. Executive Vice President of technology at National Logistics Services, the award-winning NLS organization. How can folks connect with you on anything you shared here today, Lindsey?

[00:45:41] Lindsey Billing: Yeah, absolutely. Well, I'm very active on LinkedIn.

[00:45:45] Lindsey Billing: There are very many people on LinkedIn with my exact name, so look me up, I'm there and, uh, happy to reply there. Uh, and for national logistics services, HAF, be very happy to talk, uh, uh, to any, uh, anyone. Uh, again, it's nls.ca and there's a contact, uh, link in the top right. And, uh, uh, that's, uh, that's a couple great ways to get me.

[00:46:10] Scott W. Luton: Outstanding. Outstanding. We're making it even easier. Uh, Lindsey, we're dropping your LinkedIn profile. I bet we'll drop the NLS uh, URL right there, folks. You're one click away from connecting with Lindsey Paul, same question for you. Executive board advisor with Osa Commerce, if folks wanna talk Dallas Cowboys, uh, the u uh, university of Texas Longhorns or anything related to changing how we do supply chain, how can folks connect with you?

[00:46:37] Paul Boothe: Hey, same for me. LinkedIn is always a great way. I'm really active on LinkedIn, have a ton of connections, but I'm always looking to gain more as we great, as we grow network, uh, professionally in that area. Hey, if anyone's in Chicago and coming through Chicago, I'm out in the western suburbs. I'd love to meet for a coffee and be able to talk to shop and, uh, Kim, maybe we can take our dogs and meet at the dog park sometime.

[00:47:04] Kimberly Reuter: I saw Culver and as he's talking back, so

[00:47:09] Scott W. Luton: hey, we'll keep it real around here. We keep it real and I would just add to Paul's invitation there. I bet he's got the spot to go for delicious tacos in Chicago. So take him up on that. Uh, Kim. One thing I want to, uh, first off, thank you for your time here today.

[00:47:24] Scott W. Luton: I always love co-hosting with you. I wanna make sure we get a plugin for the morning mood, which is your new podcast. Folks. Gotta check it out. They can get it wherever, uh, their podcasts are, and you've been having a great time, uh, with that series. Huh?

[00:47:37] Kimberly Reuter: Yeah, it's been great. Um, it's about supply chain leadership in life.

[00:47:42] Kimberly Reuter: Um, I will warn you, it is unfiltered. Uh, so if you're sensitive to the logistics language as I call it, um, be, you know, be warned. Uh, but yeah, it's been really fun. It's been a creative, great creative outlet and I've had a lot of people who are really excited to be on it, uh, who are, you know, architects of, uh, modern e-commerce as we know it today.

[00:48:01] Kimberly Reuter: So, looking forward to sharing more.

[00:48:03] Scott W. Luton: Outstanding. Outstanding. Who knows? Uh, Lindsey and Paul May, may, may be making an appearance again soon. We'll see. Uh, but regardless, I wanna thank everybody and thanks. I know we could hit everybody's comments. We got some of the best comments here on today's show. We're gonna have to go back.

[00:48:17] Scott W. Luton: We're gonna have to write a book on this great brilliance we get from our, uh, the smartest audience and all of global supply chains. So thanks to all of y'all for being here. Uh, big thanks to Lindsey Billing with NLS. Thanks for being here, Lindsey.

[00:48:28] Lindsey Billing: Thank you very much. It was a great hour.

[00:48:31] Scott W. Luton: Thank you. It was, I feel like I got a certification.

[00:48:33] Scott W. Luton: Paul Boothe with Osa. Great to see you here, Paul. Thanks Scott. Great to be here. You bet. Kim Reuter always a pleasure to connect with you, uh, folks. Scott, check out the morning mood. Uh, but Kim, great to have you here today.

[00:48:45] Kimberly Reuter: And Fanny says, thank you too.

[00:48:47] Scott W. Luton: Okay, fan Fanny. Uh, they'll make an appearance next, uh, again, to our global audience.

[00:48:52] Scott W. Luton: Really appreciate you being here. Thanks so much for the great comments and perspective from the cheap seats. Keep it coming. Uh, but here you got, everybody's got homework. I. We had a very actionable conversation here today between Lindsey, Paul and Kim's perspective. They have tremendous opportunities to change how we do business.

[00:49:09] Scott W. Luton: Uh, again, delighting the customers. I said that first for Kim, but, but in my view, almost as important as making sure our and team members can find success easier, taking some of the friction and pressure out of their day to day. So with that said, you gotta take one thing that Lindsey, Paul, or Kim shared here today.

[00:49:27] Scott W. Luton: Put it in action. Deeds, not words. That's how we'll change industry. And with all that said, don't buy out the entire Supply Chain Now. Team Scott Luton challenge you do good, give forward, be the change that's needed, and we'll see you next time. Right back here on Supply Chain Now. Thanks everybody.

[00:49:41] Narrator: Join the Supply Chain Now community.

[00:49:42] Narrator: For more supply chain perspectives, news and innovation, check out supplychainnow.com. Subscribe to Supply Chain Now on YouTube and follow and listen to Supply Chain Now wherever you get your podcasts.