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A
You can't just jump right to AI and skip the data. 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 look 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.
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B
Welcome to Supply Chain now, the number.
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C
One voice of Supply chain.
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B
Join us as we share critical news, key insights and real supply chain leadership.
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C
From across the globe, one conversation at a time. 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 Kim, how you doing?
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D
I'm doing great. How are you?
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C
Doing wonderful, Doing wonderful. How's the weather up there in Virginia lately?
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D
I think just like everyone else in the United States, we're, we're kind of chilly coming up on Memorial Weekend. I think it's going to be a lot of bonfires for this Memorial weekend.
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C
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 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 going to 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. We're going to be walking through some of the common and unique challenges in 3 PL world. We're going to 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 Kim. Should be a great show, huh?
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D
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. 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.
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C
So true. In fact, some estimates have the 3 PL space here in just the US alone growing to $335 billion in terms of market space by 2029.
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A
How about that?
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C
And there's great opportunity to change how we do business. Not just supply chain, but certainly three pl. And we're Going to talk to that here today. And Kim, given your track record of success in supply chain leadership, look forward to gaining your insights as well. Time to get to work. We've got a great one, two punch we're bringing here today. I want to introduce Lindsay Billing, executive vice president of technology at National Logistics Services and Paul Booth, executive board advisor with OSA Commerce. Hey. Hey Lindsay. How you doing?
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A
Good afternoon.
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C
It is so good to see you. So good to see you. And Paul, how you doing today?
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A
Hey Scott. Doing well. Glad to be here.
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C
Welcome in, welcome in. Well, Ken, we've got a great show teed up but you know what? I'm going to start with my patented fun moment questions. Let's get a sense of who Paul and Lindsay are and Kim too. So let's do this. So fun. One question. Lindsay, 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 last time. We connected but what's been one of your favorite all time rounds of golf?
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B
Yeah, absolutely. And I mean golf's been a big part of my life right from being a, 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 Myrtle 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 and there is a trophy and we got our names on a plaque. It'd be a little chilly usually on in December and we would go every year and I still remember the last round that I played before I guess grew up and moved out. And it was a wonderful day and time with the family and I won the last plaque on the trophy is my name.
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C
That is awesome. So Lindsay, what was the name of the trophy? Do you remember?
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B
We didn't give it a name. It was the billing Christmas classic, I believe what was displayed on the trophy.
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C
So I like it. Special memory. We're going have to see some pictures but I appreciate you sharing that special part of your journey. Paul, a little different question for you now. We've 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?
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A
Wow, Scott, you have to go back a lot of years. 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 kind of when I was just out of college, you know, die hard Cowboys fan and they've made a change with the legendary coach Tom Landry and we were all skeptical what would happen, but the new ownership, he hasn't been that good in recent years, but brought Jimmy Hudson on board and 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, the first of three Super Bowls there during that run and Jimmy's in the locker room and said, how about them Cowboys? So that's procatchticks with me. That's a good memory.
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C
I'm with you, Paul. Jimmy Johnson, one of the greatest 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.
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A
Amazing.
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C
Well, Lindsay and Paul, I appreciate that. And Kim, you're not getting out of this question. I love hosting these shows with you. Now I know your busy travel schedule may not allow you to enjoy it yet, but. But is it oyster season up in beautiful Virginia yet?
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D
So interesting enough, we'll do a small history lesson here on oysters. 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. But nowadays you can buy oysters all year long and they are great for the hot big holiday weekends that are coming up for summer. Just throw them on the grill outside, easy peasy.
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C
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. So Lindsey, let's start there. Tell us briefly if you would about yourself and about your organization, nls.
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B
Absolutely. So myself I'm a computer engineer by trade. I've been in technology for my entire 25 plus year career. Moved right from being a coder to being the head of it. First 10 years was in consulting. I was a number of the big four and then I've been in industry for the last 15 years focused on retail in progressive roles all over the technology space. I like to think of myself as a business leader first who knows a two about tech. You know what I always strive for. I live in the gta. I have four kids, two in elementary school, two in post secondary school. So very busy household for me. National Logistics Services is Canada's premier logistics provider focused on the lifestyle space. Lifestyle being fashion, apparel, footwear, accessories, sporting goods, item for the home. You know a bunch of different areas there. We focus on omnichannel, wholesale retail delivery and E commerce. We have large global brands but also we'll talk a little bit about smaller brands in the heavy growth phase. We are growing that out of our business significantly. We focus on not just Canadian delivery, but we also 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.
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C
Love that Lindsey 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 culture is, you know a big part of this journey we're all on. So appreciate that context. Lindsay all right Paul, want to do the same thing I love. I've really enjoyed getting to know you better through some of the pre show sessions. So tell us briefly about yourself and what OSA does. Sure.
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A
Thanks Scott. I've got over 20 years of supply chain experience and most of that is primarily in the 3 PL and 4 PL space that we'll be discussing here today. I began my career with Ryder on the supply chain side and have escalating roles of responsibility. In 2016 I made a move over to XPO 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 and in 2022 we spun a Horrox level into a separately publicly traded corporation. So really just some really exciting kind of background and large 3pls 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. It's their delivery of AI in this three PL and in the shipper space. One of the things that OSA 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 osta we are really taking it to the next level. And just about me personally, my wife and I, I spent 50 years in Texas and five winners now in the Chicago suburbs. That's how I kind of count my 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 going to be going to Tennessee Chattanooga to continue college and then I'll have a senior next year in college as well. So a little bit about me on the personal front.
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C
Love that, Paul, and congrats to your daughter. That's exciting, exciting times. Appreciate that. Now, Kim, did you hear one of the things that Paul mentioned there? Paul had mentioned Unified Platform and that reminds me of Unit, a song by the famous Queen Latifah who is more known for her her acting than her rapping these days. But who'd have thunk she was a supply chain tech pioneer. But all of that aside, Kim, we got quite the panel between Paul and Lindsay, huh?
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A
We do.
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This is going to be great.
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C
So let's do this. Lindsey, as we get further and further in this conversation, I want to start with we're really in this golden age of supply chain tech. It's fascinating to see we got plenty and plenty of miles to go 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 Lindsay, what are some of your observations in that regard?
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B
So I think what I've seen in the supply chain space, several things. One is there's a lot of work that needs to be done in the tech 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 five years and more. 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, you know, to move goods you need heavy integration. And it's also a data rich industry. There is a wealth of data in this industry. Data underpins supply chain in terms of moving goods. And as we're going to talk about today, since AI is underpinned by Strong Data Foundation, I think there's unique opportunities in the supply chain space around data AI.
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C
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. Paul, your observations on how you're seeing AI leverage right now in global supply chain.
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A
Yeah, Scott, I think I would echo some of what Lindy just shared. You know, I think AI is still largely untapped as a tool in global supply chains. There was a Gartner survey last year that came out said 64% of supply chain leaders are either implementing or planning to implement generative AI over the next 12 months. But candidly, I think some of the uses that we see are very basic in how AI is being used in supply chain. And it's really just picking some low hanging fruits. It's one of the benefits of working with 3 PLs. I think 3 PLs are really a step ahead in this, ahead of shippers because they're able to be focused on that. But for the companies that are using AI, I think there's huge benefits there with cost reduction, decreased inventory levels and really just improved service levels. So it's something we're going to see continue to grow and grow. I think it's probably, you know, the popularity of the topic today.
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C
Well said, Paul. And before I get Kim to comment on what she's hearing, what she's seeing, I came across some research 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. 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. Kim, when you heard Lindsay and Paul's observations there, your thoughts?
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D
So everyone's talking about AI and supply chain. It's the latest, greatest. 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 opportunity is predictive consumer predictive behavior and consumer demand. I think that's the biggest opportunity right now we see in AI. 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, on the things that we know, we don't need to apply AI to those. It's the things that we have a hard time measuring like consumer behavior. 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 going to use AI on my supply chain, you need to be specific.
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C
Well said, well said. You got to preach it louder to the folks in the back. Now we're going to dial it more in on the 3 PL industry. Right. Kim and I both were talking about the sheer growth which is of course fueled, fueled by a number of different things from E commerce to the complexity of modern day consumer demands, cross border shipments, all that stuff. So speaking of challenges, Lindsay, when you think of challenges both common and unique within the 3PL space, what comes to your mind?
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B
Yeah, so I think on the 3 PL front, there are a number of challenges that we experience and we're experiencing today. But also in the past, economic uncertainty and also in the most recent weeks and months, tariff uncertainty and cross border shipment is a challenge that three PLs need to overcome. In particular, lifestyle products are usually wants, not needs. So we have to be in really tight partnership with our customers around forecasts, et cetera. When there is uncertainty, it produces cost margin pressure. So one of the things three PLs need to focus on is around costs, margins, etc. As well. One of the challenges for three PLs is, and this is where AI can help 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, we're not a commodity service we provide. We are a growth engine and partnership with our customers to enable them for success and help them grow. So and, and AI can, can help on all of those fronts. As we're going to talk about today. There's my thoughts on, on those challenges.
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C
I like it and I like your mantra. Don't, don't get commoditized folks. We do way too much, we create way too much value. Don't hall similar question for you. Challenges in 3 PL space, both common and unique.
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A
Yeah, I think one of the challenges is no two days are the same. We never know what we're going to walk into each day and 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 they are handled every day. Lyn just mentioned all the uncertainty right now with the macro, what's happening with tariffs and how that really things are fluctuating not even by the day, but sometimes just by the hour right now. So I think the uncertainty and just one of the challenges, both unique and then common, is just not knowing what you're going to face.
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C
Paul, that's excellent comment and Kim, it reminds me of the old saying if you don't like the weather in Georgia, wait for an hour. And it's kind of like if you don't like the current challenges or the current flavor of global supply chain, just wait maybe a minute. Kim, weigh in on the challenges with Lindsey and Paul shared so Lindsey touched.
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D
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. And Lindsey just hit the nail on the head in that if you leverage your 3 PLs and your supply chain partners correctly, they can become revenue generating partners.
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C
Well said. Excellent point there. Very true. Now I'm going to share some good news. We're going to talk about a few powerful AI use cases, right? 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 going to start with warehouse automation. So Lindsey, tell us more here.
- [19:16]
B
Absolutely. And I mean warehouse automation has gone through a journey over the last 20 years, right? It starts with robotic process automation, RPA progresses to machine learning and predictive analytics models, and now is getting into the generative AI and the large language models. But I think warehouse automation is all about increasing speed, accuracy, reliability, redeploying staff to new roles and exciting roles and value add roles. And warehouses are complex and often retrofitting AI into warehouses, as many supply chain organizations do, can be very challenging. So here at nls we're firing on all cylinders. Here first is a new 600,000 square foot warehouse that we are building fully automated 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 around the warehouse in an autonomous way. We also partnered with Six Rivers. We use their Chucks, which are these automated carts that move around the warehouse and increase picking accuracy. And we've been a First Canadian partner with Six Rivers. And then we're also currently helping and piloting and partnering with a company called the Rubik and a Freedom Pick. And this is basically a fully autonomous 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 in an autonomous way. All using AI. And warehouses are complex spaces and therefore automation can be a challenge. And AI can be a challenge as well. But AI thrives in that kind of space. Yes.
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C
Okay. Paul. My son's favorite superhero of all time is Batman. And he's got all the gadgets, all the automation. What Lindsay 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, what'd you hear there? And you could talk about warehouse automation now.
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A
A lot of the same things that Lindsey just touched on. You know, robotics is huge right now. I had a chance back in March to attend a conference here in Chicago, ProMat 2025, and I was just blown away by seeing all the automation that's happening in the warehouses. You know, Amazon employs over 750,000 robots in their DCs and fulfillment centers. And the robotics, just as Lindsey shared and how they're using an LLC are for a variety of different things. The use of drones is something that we're really seeing increasing for inventory management cycle counts that's really starting to gain traction. And there's multiple drone companies that I saw on displaying and they're growing and what's happening there. You know, I think what's important is that more than just the automation, replacing the work is the application and 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. We've already hit on this multiple times. But 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. Yeah, great.
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C
Like a stuff there, Paul and Promat, by the way, over 50,000 people at Promat 2025. Back in early March, Kim, Lindsay and Paul Both shared a lot of good stuff there. When it comes to the really cool, innovative ways where finding to automate warehouses here, what'd you hear there, Kim?
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D
So when we talk about AI and warehouses, you know, people get really excited and you know, they go to the drones, right? Like we want drones and you know, we want all the fancy lady 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 Borg made sense to me. Like that's all I could think. Why I was there was the Borg. I mean, they're wild looking. If you've been in an automated warehouse, it's incredible to be in one. You know, stacks that go all the way to the ceiling. 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, and Paul touched on this a little bit as well, is relocating fast moving items, seasonal items. When we look at, you know, companies that Lindsey works with, it's very seasonal. Something might be a hot buy. It ends up on Oprah's list, like you never know. But being able to predict when an inventory is going to be a hot seller and then relocating that to a high pick location. 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 stacked up here, which in this situation, our current terror situation, may not be a bad move. This is another area where inventory levels using AI. Another easy way to plug in the AI is managing inventory levels with predictive analytics.
- [24:59]
C
Well said, Kim. Inventory is cool again and absolutely critical, as you're pointing out. Okay, so where are we going next? That was the first kind of use case we're going to dive into here today, warehouse automation. The second one is kind of a big bucket. Lindsay. Demand forecasting. Predicting that outbound volume and of course data utilization is not good enough to have it. We got to utilize it. Your thoughts, Lindsey?
- [25:23]
B
So from a demand forecasting perspective. So this is a great opportunity for 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. 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 going to get tomorrow. Then I can staff my warehouse in an optimal manner that allows me to reduce costs which I can then help pass on to the customer. So labor planning is a big part of running a warehouse and being able to predict outbound volume. But for our customers we can use the same predictive model to predict inventory position, predict SKU trending, predict, you know, revenue projections. There's a number of things that we can do and we have been running AI machine learning models because you know, A3PL is a wealth of data. Every product that we have that a customer has shipped out or we have shipped out on their behalf to storage, we have it in our data ecosystem. So we are in a unique position to partner with customers. Using machine learning models to predict the future.
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C
Sounds like it. No wonder, such a great place to work. But it's very fulfilling, rewarding to really change how business is 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. The trend for years now is get out of solely reactive mode and truly be proactive. Kimberly's talking about reading your customers minds. I love that we're able to do that more now than ever before. Paul, your thoughts here?
- [27:13]
A
No, I breath being able to look in the future a little more of a crystal ball. I've tried to get AI to predict when the Cowboys are going to win the next super bowl and he hasn't done that for me yet. But no, 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 3pls, just like what Lindsay and NLS is doing bring an advantage because they have the data, they know how to use the data, they're able to help navigate it. And then for three PLs just like NLS, you have partners like what we do at OSA Commerce. We're able to take that, were 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. Some of the things that Lindsey mentioned, the historical sales patterns, you know, market trends, being able to understand what happens There, even weather patterns. You know, one of the things with my background in kind of last mile home delivery, big and bulky into a consumer home, social media sentiment is very important there. 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. He talked about, I love this, being able to use the data for dynamic labor management, kind of the resource allocation. And it reminds me of a quote, one of my mentors in the industry, Steve Sinsing. Steve is president of global supply chain at Rider. 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.
- [29:04]
C
Kim, so much to comment on there. But I'll pick up on Paul's last point. Again, it's not good enough just to have data. We got to 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 an imperative, I think, in doing global supply chain here in 2025. But your thoughts, Kim, what Lindsey and.
- [29:26]
D
Paul were sharing, I agree that everything that they have to say, I'm going to take a little further downstream, though, when you 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. 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 going to 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. No. So they didn't tell anybody. The warehouse gets completely overloaded. Now, the warehouse was able to pull it out. Right. But no trucks, not going to happen. Large portion of those orders actually ended up getting canceled because they weren't going to 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.
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A
All right.
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C
And taking a unified approach to prevent those gaps and how we plan, communicate and execute. I guess putting it simply, good stuff there, Kim.
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A
All right.
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C
We're about to hit the third AI use case. Technology use Case. So Lindsay, tell us what you are doing when it comes to customer service.
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B
You know, obviously customer service and the relationship between us and our customers is absolutely paramount. And I want to start on this one. Just talk a little bit in my, in the intro about national logistics services I talked about about how we have customers that are global established brands that we work with very large, but we also have in emerging, we call them emerging brands business, which is smaller brands that are on the growth pattern and the growth scale. And 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 warehouse management platform, this area of emerging brands, growth brands, is exactly where we partnered with OSA Commerce in terms of their lightweight warehouse management visibility platform. 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. You know, we could have 10, 20, 50, 100 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 for that level one support. And that is very exciting because again we talk about differentiation within the 3 PL space and individualized customer service 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 A3PL. And that's where AI can, can absolutely help. So I'm, I'm very excited about that aspect.
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C
Love that Lindsay. And quick comment. I kind of subscribe to the view that we're all in customer service and organizations. I kind of 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, I mean imagine the creative ways that they come up with the beautiful human element to serve and enhance that customer experience. Lindsay, I love what you are doing. Paul, what else are you seeing, customer service wise? Well, I think one of the things.
- [33:23]
A
Is just the power of kind of BI tools right now from a customer service perspective being able to just hand that to someone at their fingertips. I can think of a demo when I was at XPO Logistics With a managed trans team, we went into a large Fortune 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, called this whole team around the tablet and 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 are chatbots and virtual assistants. There's a lot of that and cinnamon is starting to change here. 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 make me talk to this machine.
- [34:19]
C
But the current generations that you're seeing.
- [34:22]
A
Of AI and how they're powering customer service are much more user friendly. The speed and the accuracy to assist us is great. And 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 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.
- [34:50]
C
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 bike. So there's pluses and minuses. Yeah, just happened yesterday, Kim. All right, so Kim, customer service, massive opportunities here. Your thoughts?
- [35:04]
D
First of all, we should have started with the customer. I'm just going to 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 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, while being the cheapest shipping 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 talked about, like where does it need to be located, where is it most likely to ship out of? Is it more likely to be paired with another item? 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.
- [36:03]
C
Love that. And, and yes, Kim, I love your passion for starting with the customer but a third is better than better than fifth. Right?
- [36:11]
D
We talked about them.
- [36:14]
C
So Lindsay, as we kind of wrap this section, I really appreciate the use cases you shared. You and Paul and Kim all spoke to. If you want to drill down or spike the football on one key benefit or outcome produced by successful measured targeted outcome producing AI deployment, especially for 3 PLs and their customers, what would that be? Lindsey?
- [36:35]
B
I think in terms of, you know, the most significant benefit for a 3 PL is being centered and focused around the customer and leveraging AI for that. And it's all about service level. It's all about, you know, especially the prediction aspect of it is huge. We never know what's going to happen tomorrow unless AI can help us. And I do want to underscore, especially in NLS's space we talked about a couple times handling peak seasons in the lifestyle space. For example, we see up to 7x or 8x volumes during peak and a lot of our customers will say their entire year comes down 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 going to happen in order to handle those peak seasons. Especially you know, if we have multiple customers with a similar peak profile. Any kind of AI that we can use to manage the peak season, that that's game time for 3ths in the years.
- [37:47]
C
Well said, well said, Lindsey. And you're going to need one of those super innovative Batman warehouses that you are building. Lindsey. For folks who have reach out to Lindsay for more details. I want to get a tour of that space when y' all open that up. Lindsay. Okay Paul, you know, same question. What's a final outcome? What's the so what here, Paul?
- [38:06]
A
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 Lindsay 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. Where is it actually going to 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 3PL or that 3PL can grow to really provide benefit within your supply chain. So I think that's kind of what comes to mind for me is, you know, we talked a lot about a lot of different areas. 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 left of 20 different things that I heard from Scott and the team. You know, figure out where can you, you make the biggest impact and just begin there.
- [39:03]
C
That's right. Absolutely. Hey, do a pulse check on the customer. Do a pulse check on your team members. See what their biggest pains are.
- [39:11]
A
Right.
- [39:11]
C
May not do it all 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. Kim, your quick comment here on what Lindsay and Paul were talking about.
- [39:25]
D
I've been working with supply chains for over 30 years and to this day, still the most unpredictable thing is the end consumer. And so using AI to predict what the customer is going to buy, where they're going to buy it and when they're going to buy it, will feed everything backwards. Y 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.
- [39:56]
C
Oh, I like that. I like that. So Kim, Paul and Lindsay I was talking with, we, in fact we featured Vin Dashishta. 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 there are big opportunities with data no matter what how you use it and what technologies use it, as long as you're using it. And that's really, really important. And that's what I want to get Lindsay 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. Lindsay, your comments here.
- [40:37]
B
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? 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 within nls. We partnered with Snowflake as our data ecosystem. We not only have 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. Because, you know, you, you get quick, much more quick to value 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 if you start from a, a strong data foundation versus not.
- [41:43]
C
Well said, Lindsay. Well said. Not just clean and data hygiene in mind. It's got to be connected. That's how we, it's one of the really big ways we harness and use all this data we have at our fingertips in this crazy age. Paul, your quick comments.
- [41:59]
A
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, you know, boardrooms with Fortune 500 companies where you have customer service, brings one set of data, maybe the ERP information. You've got the warehouse team bringing what's from a WMS transportation team bringing what's in a tms and there's really no integration and they all have different data points that they're trying to argue or use 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 to improve upon. 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 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 look 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.
- [43:10]
C
Paul, I like it. The single source of truth is not like the Loch Ness monster. It can really be a real thing. Kim, so we're hearing there's some good news there. Your quick comment, Kim, you have to.
- [43:21]
D
Have a single source of data. And then, and I worked with a company many years ago and this is going to floor you. But from product page to checkout, they hit six different tables. 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 going to screw up faster and faster and faster and faster and faster. You're just going to make a big mess faster.
- [43:54]
C
Well said Kim. So let's do this. Paul, you're just talking about OSA commerce. Let's make sure folks know how just how easy it is to get started working with OSA. Your thoughts there Paul?
- [44:06]
A
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. You can click right on that. There's a Contact Us page there. You know Lindsay found this. We're able to work with nls so we're easy to find and easy to work with.
- [44:26]
C
Love it and you're going to enjoy working. I don't go as far back with Paul but Padu and the team and then Paul, we're instant fan. You're instant second cousins now, right? That's Howard Spirit supply chain now. But you're going to love working with Paul and the OSA team. So check that out Kim, before we make sure folks know how to connect with Lindsay and Paul. And we're going to be sharing a great report here that I really enjoyed earlier. What is your patented one key takeaway from a great conversation here today? Kim?
- [44:54]
D
Data. As always, you got to 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.
- [45:08]
C
Don't get all crazy and go straight to 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 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?
- [45:39]
B
Yeah, absolutely. Well I'm very active on LinkedIn. There aren't very many people on LinkedIn with my exact name. So look me up. I'm there and happy to reply there. And for National Logistics Services, Hathi very happy to talk to any, anyone. Again it's NLS CA and there's a contact link in the top right. And that's, that's a couple great ways to get Me.
- [46:09]
C
Outstanding. Outstanding. We're making it even easier. Lindsay, we're dropping your LinkedIn profile. I bet we'll drop the NLS 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 want to talk Dallas Cowboys, the University of Texas Longhorns, or anything related to changing how we do supply chain, how can folks connect with you?
- [46:35]
A
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 grow network 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 shop. And Kim, maybe we can take our dogs and meet at the dog park sometimes.
- [46:59]
C
I'm so sorry about that.
- [47:01]
A
I love it.
- [47:02]
B
Right?
- [47:03]
D
I saw and now he's talking back.
- [47:05]
C
So, hey, we 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. Kim, one thing I want to first off, thank you for your time here. They always love co hosting with you. I want to make sure we get a plug in for the morning Mood, which is your new podcast. Folks got to check it out. They can get it wherever their podcasts are. And you've been having a great time with that series, huh?
- [47:36]
D
Yeah, it's been great. It's about supply chain leadership in life. I will warn you, it is unfiltered. So if you're sensitive to the logistics language, as I call it, be, you know, be warned. 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, who are, you know, architects of modern e commerce as we know it today. So looking forward to sharing more.
- [48:02]
C
Outstanding. Outstanding. Who knows, Lindsay and Paul may be making an appearance again soon. We'll see. But regardless, I want to thank everybody. Thanks. I know we couldn't hit everybody's comments. We got some of the best comments here on today's show. We're going to have to go back. We're gonna have to write a book on this great brilliance we get from our the smartest audience in all of global supply chain. So thanks to all of y' all for being here. Big thanks to Lindsay Billing with NLS thanks for being here, Lindsay.
- [48:26]
B
Thank you very much. It was a great hour. Thank you.
- [48:29]
C
It was. I feel like I got a certification. Paul Booth with osa. Great to see you here, Paul.
- [48:35]
A
Thanks, Scott. Great to be here. You bet.
- [48:37]
C
Kim Reuter, always a pleasure to connect with you folks. Gotta check out the morning mood, but Kim, great to have you here today.
- [48:43]
D
And Fanny says thank you too.
- [48:45]
C
Okay, Fanny, they'll make an appearance next again to our global audience. Really appreciate you being here. Thanks so much for the great comments and perspective from the cheap seats. Keep it coming. But here you got everybody's got homework. We had a very actionable conversation here today between Lindsay, Paul and Kim's perspective. They have tremendous opportunities to change how we do business. Again, delighting the customers, I said that first for Kim. But in my view, almost as important is making sure our team members can find success easier, taking some of the friction and pressure out of their day to day. So with that said, you got to take one thing that Lindsey, Paul or Kim shared here today. Put it in action. Deeds, not words. That's how we'll change industry. And with all that said, on behalf the entire supply Chain now team Scott Luden, challenge you do good, get forward, be the change that's needed. And we'll see you next time right back here on Supply Chain Now. Thanks everybody.
- [49:39]
B
Join the Supply Chain now community.
- [49:41]
C
For more supply chain perspectives, news and innovation, check out supply chain now.com subscribe.
- [49:46]
B
To Supply Chain now on YouTube and follow and listen to Supply Chain now wherever you get your podcasts.