C.H. Robinson Worldwide, Inc. (CHRW) Earnings Call Transcript & Summary

Okay. Let's go ahead and get started with the next presentation. For those that don't know me, I'm associate analyst of Transportation here at Raymond James, David Hicks. And today, we have the pleasure -- this afternoon, I have the pleasure of having C.H. Robinson with us, the CEO, Dave Bozeman; and then CFO, Damon Lee, with us today. So I think a lot of people in the room know who C.H. Robinson is. But Dave, maybe just give us kind of a high-level overview of kind of the markets you play into what you guys do, just to kick us off.

Yes, sure. Thanks, David. Thanks for having us here. Just to start off, C.H. Robinson is one of the larger global logistics solution firms in the world, really driving in the 3PL space. For those of you who don't know that, it's a 2-sided marketplace space. And just to give you the numbers, first of all, we do 37 million shipments annually. We have about $23 billion of freight under management. And we play in this kind of 2-sided marketplace of carrier relationships on one side, that's capacity. On the other side would be shipper or customer, that's the demand side. And we have over 450,000 carrier relationships, 75,000 customers. We pick those 2 together, given the carriers access to a broad base of freight, and we give the shippers access to a broad network of carriers, giving them a good price advantage as well. Our goal is to play in 4 core modes: that's truckload, LTL, ocean and air. That's really where we focus ourselves as a company. And then when you think about our strategy, it's been pretty simple. It's been about really kind of growing, outgrowing the market or growing or taking market share while also expanding our margins overall. That's been kind of our strategy as a company in doing that, and we'll get into talking about that. We've been pretty successful at doing that and changing over the last 3 years or so in driving what we call Lean AI. It's our new lean operating model. But it's really combined with our logisticians, which are really some of the most experienced logisticians in the world. Our technology, which we'll talk about, which is AI technology as well as our operating model, those 3 kind of drive what we call Lean AI, and they work symbiotic as a relationship. And that has allowed us to really outpace, outperform the industry in the last several quarters, 8 to 11 quarters in outpacing the industry here, and we feel really good about that. It's early innings for us in this transformation. We're in the second inning or so and have a lot more to do, and we can get into that. But that's the company overall. This is Damon Lee, anything you add to that opening?

No, well said.

Great. Great overview, Dave. Maybe just to level set before we talk into your story. You have a lot going on in your story, but maybe just talk about what you're seeing in the freight markets right now? We've been in a freight recession 3.5 years, but the last 6 months, it looks like things are starting to kind of perk up mainly on the supply side, demand is still kind of languishing. But maybe just give us some thoughts on the market kind of before we dive into your story.

Yes, I'll start and Dave jump in if you want to add any color or context. But look, I'd say, start with demand, I think it is more of the same, right? I think there's certainly been a little bit of excitement around some macro indicators, but I think it's been yet to show up in freight demand yet, right? I mean, certainly, CA index was down minus 7% again for the month of January. So I think even though there's some talks or green shoots, I think those have yet to be seen. On the cost side, we have had disruptions from a cost perspective. If you go back to Q4, I think that's really where the cost curve started to elevate. Certainly between Thanksgiving and the end of December, that 5-week period of time, we did see a material increase in cost, right? I think certainly brought on by 3 winter storms that affected a large portion of the country. Those 3 winter storms were essentially on each other's tail, so they happened in sequence. You had your traditional capacity crunch during the holiday period. And then you had a stacking effect of the various regulatory enforcement actions. So I think all of that led to a heightened environment to drive cost higher. And certainly, as we say often, we're not immune to the market, but we do hold ourselves to a very high standard. And we think we performed extremely well in Q4, both from a gross margin perspective, an operating margin perspective and an outgrowth perspective in a very difficult cost environment. And what I would say is that cost environment continues into Q1, right? Certainly, we mentioned during our Q4 earnings call that, that cost pressure had continued into the month of January, and it has continued into the month of February as well. So certainly, the cost pressures realized in Q4 will certainly have a meaningful impact on Q1 from the industry perspective as well.

Yes, I think that's well said. And just to add a little bit of color on the demand side for those of you who are more generalist on this, we look at demand that would drives freight, and those are really 3 or 4 things that's manufacture, retail housing. You could break that out and really say automotive. I kind of can put that under manufacturing as well. But those components are really would drive freight. And if you -- why Damon said that, if you're thinking about those, the housing side to retail, to manufacturing, that's all been somewhat muted and not up and to the right yet, and we certainly are looking for that to happen as you start to drive an inflection. But just to give a little bit of color on that.

Okay. That sets the stage really well. Let's dive into the story. But before we get into that, Dave, I want to talk about culture. I think it's a very underappreciated aspect of your story. You're the first -- I believe you're the first outsider CEO at Robinson. And you have these lean operating principles that we've never seen in brokerage before. You bring in Damon 1.5 years ago. Can you just talk about kind of how that culture shift has happened when you came into the company a little under 3 years ago?

Yes. Thanks, David. The -- I know it was a lot -- it was different for a number of you. I've met you. It's been almost 3 years, a number of you in the room, and you've gotten to know me as well. And it was -- it's different for the industry, but lean is not different. Lean is transferable to any industry. And all we did was I've been doing lean for almost 30 years and just brought that into this company, a 120-year company and into an industry that it makes a market difference in doing that. And culturally, it was something that what we do at Robinson, we're radically transparent with our employees. Two, we do diagnosis like we did. And three, you have to solve problems. And what we found in our company is that we kind of admired problems more so than fixed problems, and that was something we were going to change. And so we no longer admire problems. We fix problems. And that's a key tenet of lean, problem identification and problem solving. And when you look at our culture now, it is one that's built on these lean principles and people who have been in industries for over 20 years have now learned tools that help drive this problem identification and problem solutioning. And that has ultimately driven our speed, our speed to development, our speed to creation. Now with technology, that has now supercharged what we're doing. And the culture is a culture that really likes winning again. They like getting their swagger back. It's a company that has grit and hustle, but it also likes to win. And I think lean and bringing in a lean operating model has tremendously helped our culture. And again, we're baby steps in this. I've seen this for a long time, and we are early on in the journey. So a lot to go, and I'm proud of how the team has accepted this transformation.

So that's a great overview. And before you got there, CH had really over-hired during the pandemic, brought on a lot of volumes, but also brought on a lot of people. I always like to frame for investors is that you came in through lean methodology. It was kind of like the Ozempic that you guys needed to really get back on track. And now you're layering in AI, kind of packing on the muscle, if you will. Can you maybe break down kind of -- you've increased productivity double digits the last couple of years, over 40%. Can you maybe just break down kind of what's been on the lean front and what's been on the AI front that have really driven the changes?

Yes, I'll start, and I'll have Damon jump in as well. Like we get that question, and I used to kind of reframe that question. Like we -- I would normally start, Dave, I really like you, right? And it's like -- I normally would say, I don't know, right, on doing that, but I want to give some context to that because we don't look at that as separate. These are not series. Like it's not like, hey, how much for technology and how much for lean? That's not really the way it works. It's symbiotic and they all work together, right? Our people, the operating model and technology all works together in driving that. I will say this, if you think -- I don't care what industry you're in, if you think you can just do like a technology by itself, we don't think that, that works, right? You have to have a conduit. And that conduit is an operating model that drives accountability, responsibility, visibility, speed and creation. And you're always ideating and driving velocity on doing that. That's -- we don't have enough time to kind of go into the depths of that, but it drives with our technology together. And so that productivity, we don't break it down. We say, hey, in the next few months, we'll have more productivity and that productivity is driven off of our operating reviews and what we do. And it happens to just be part of it. I don't know if you'd add anything?

I would just add a couple of things. I'd say, from a lean operating model perspective, I mean, the reason we are implementing agentic AI today as a step function improvement from GenAI in C.H. Robinson is based on something that was born out of the operating model, right? We were in an operating review, in a PD environment of policy deployment. This is really strategic initiatives, challenging our technology teams, challenging our business teams, how are you going to get to where we're performing today to where we need to perform tomorrow? They didn't have the answer, right? So they got a 48-hour request to go find answers and options to close the gap, right? And Mike Neal, our CTO, came back and said, look, it's early days, but there's an evolving AI technology called agentic. Now mind you, this was 15 months ago, right? I mean, agentic hadn't even made the headlines yet, right? Nobody was talking about agentic yet, a 120-year-old logistics company was already starting to experiment with it and operationalize it for our business. That would not have happened on the time scale that had happened, maybe never, if not for the operating model, right? The operating model, the lean principles drives you to get better every single day, every single week, every single month. And we truly believe the companies that are going to be successful in AI adoption and truly drive sustainable productivity benefits, sustainable revenue growth, sustainable margin expansion, we'll only be able to do that on the back of a conduit, like Dave said, like lean, right? We believe that's the magic sauce for doing AI right going forward is a combination of lean operating model and cutting-edge technology, which we've been deploying now for over 2 years. So we believe, as Dave mentioned, they're symbiotic. We get the question a lot to the decimal place, how much of your productivity is from the operating model versus tech? The answer is we truly don't know because you can't separate the impact of the 2 of those items within the company.

I'll just put a bow on that, too. I mean it's pretty cool to see people who have been in the industry like 20, 25 years, like there's a lot of people in the room that knows what that looks like. And you have folks who have -- they're walking in now and they're starting on meeting like, hey, I'm about to talk to you about my primary, secondary and tertiary Pareto charts on solving this problem. Like they can't unlearn that tool. And they're excited about it. They're pumped about it. And that's the operating model and what is driving because they know is every person every day, some small improvement, which is why we committed to single-digit productivity improvements in this company evergreen, no matter what. I don't care if it's a hot market inflection, we will commit to single-digit productivity improvement every year. There's going to be times when we run across like an agentic technology, where we'll have double-digit productivities like this year. We initially committed to single digit. Now we'll be double-digit productivity gain this year because things like that are going to happen along this journey. But that's the mentality, David, in driving that.

I'll just add one more thing. This is one of our favorite questions, so I have to opine a little bit on it. But I honestly don't know how a company would deploy AI the way we've deployed without the lean operating model, right? Because I think we call it Hobby AI spend, where you kind of spend on AI, it may be a shiny object. It may have a cool interface, but it doesn't actually drive business benefit. It doesn't drive revenue growth, doesn't drive margin expansion, doesn't drive productivity, right? That's what we call Hobby AI. Without an operating model that drives you to value stream analysis that says, here's my opportunity to remove waste and here's my opportunity to supercharge some revenue component of my business. Without a conduit that steers that type of behavior, I think you're shooting in the dark on how you implement AI. And that's why we're so -- we think it's so impactful to combine the operating model plus AI, what we call Lean AI because without the delivery mechanism, and we believe lean is the delivery mechanism, we think most companies will suboptimize the way they implement AI within their companies.

And I think great on the lean side, but maybe let's go to the AI side. I think one of the most amazing things that you've come out on the AI side is that you were only able to handle 65% of quotes and now you can handle 100% at 30 to 40x the speed. And that speed to market from, call it, 17 minutes down to 30-some-odd seconds has been a game changer. Can you maybe -- has that played out? Or is there still more room and that's going to continue to compound in the years ahead?

Yes. No, it's played out. And it's just but one example. I mean our quoting agent, we're really proud about that. And you're right, 17, 20 minutes down to 32 seconds, 31 seconds now, every second counts. But the key thing is this, in this industry, time is money. And when you're getting things in 24/7 like quotes come in, if you don't get to them, that's a lost opportunity. And so having this agent actually respond at 100% of the quotes, that is more opportunity. It allows us to win more freight. It allows us to have that option to do it. Now we could have gone and use examples of agents that we just launched, like the LTL, our reschedule agent, which was a pain in this industry about rescheduling. If anyone knows that pain, it's there. This agent has really now eliminated overnight 350 hours of work, manual work to go and do these kind of reschedules. I mean -- and we have appointment examples as well as a number of other agents that are working the order to cash process and taking that friction out. That's what this is about, is changing the workflow, taking the friction out of the workflow of order to cash, and that's where you drive that productivity.

Yes. And that one example that we led with, it's our agent that does our request for freight quoting. So AI typically gets lumped in with productivity. And I'd argue there's a few companies that are generating real productivity. But typically, AI gets associated with productivity. That one agent generates incremental revenue, expands our gross margin, so better pricing. So we optimize our price, optimize our cost to hire, and it drives productivity. And oh, by the way, the customer benefits on 3 levels, right? Before, 1/3 of the time they were reaching out to C.H. Robinson on the NAST side of the business, either they weren't getting a response or the response came too late. So that's not customer satisfaction. Today, they get a response 100% of the time. Okay. Second is our win rate has gone up because the sophistication level of our quote has gone up as well. So where a shipper wanted Robinson to carry their freight. And in the past, we probably gave them an unsophisticated quote because we didn't have time to give them a sophisticated quote. They went with somebody else because we couldn't meet the criteria of the quote, right? So there, again, customer satisfied because we are able to give them a sophisticated quote that more times now we win that freight than we would have before. But to me, the astonishing figure in that example is 1/3 of the universe of freight that was coming our way from a NAST perspective, we didn't have an opportunity to win. Today, we have an opportunity to win that 1/3 of freight, all that freight now 100% of that freight, right? To me, that's been a demonstrable impact on our business. But when you think about AI, it's just not limited to productivity. It can facilitate revenue growth, it can facilitate margin expansion, can facilitate productivity and it can drive customer satisfaction at the same time, if done correctly.

I think what makes you guys different is we have -- every company here is talking about AI. But can you maybe talk about what you're doing externally buying from a vendor, say, and versus building internally and kind of how important your data is as the largest freight broker in North America to kind of feeding those agents and feeding those models?

Yes. I think -- well, first of all, we talk about competitive moats. One of the competitive moats we have is our domain expertise. And that is we have internal engineers. We talk about 450 engineers, data scientists that actually build our technology. Now we sit on our hyperscaler is Microsoft with Azure, but our engineers build our technology, and we're able to use the various large language models that come out. The beauty of it is there's this question in the industry right now and it says who's benefiting from AI, from all of this investment that's up the stack that's driving these models, who's benefiting from that? Well, we would raise our hand up and say we're benefiting from it because the cost of those models continue to come down, and we're able to use all of those models. I don't care if it's Claude or OpenAI or whatever. The technology team has done a wonderful job of being able to do that. And in fact, we switched between those large language models based on cost and effectivity. And what we're doing, I just told somebody in a meeting here, I mean, we're doing some pretty cool stuff. We're not exactly doing genealogy. So the compute power that we need, I mean, we can use a 2-year-old model and be just fine. And our team monitors that all the time for the better economics. So we're doing that. We would not be able to do that if we were a buy culture, but we are a build culture. We built Navisphere, which is our internal TMS, and we built our overall bespoke solutions based on these large language models and the various agents that our engineers built and our engineers grew up in the business. So you're talking about engineers that know freight, that know global forwarding, and they're building agents and having a blast right now at building these agents because they actually know that. And if you were going to go and try to replicate this, it would really take you 15 to 20 things that you have to stitch together, get an integrator to help, pay by a drink. That's a lot of headwind on margins. So it's really kind of tough to do a lot of replication. Not that it can't happen, but we're just saying that internal capability is an advantage, we think, in a competitive moat.

Yes. We think build versus buy is a critical differentiator for Robinson versus the marketplace. Dave just mentioned, right, our team estimates you would have to partner with 15 to 20 different vendors to try to replicate the ecosystem that we built, right? Can you imagine that, right? 15 to 20 vendors. Then you'd have to hire somebody to orchestrate all those vendors. And even if you got that right, you're still paying for generic AI solutioning for very specific company problems. Today, we build our own agents, right? So we build agents that are custom to solve, custom solutions within Robinson, right? We're not trying to fit a generic solution set with a C.H. Robinson [indiscernible]. We build agents to solve our own problems, right? That is very difficult to get that same value if you're buying tech off the shelf. And then the cost curve, we believe, is a huge competitive advantage. Once we build an agent, the marginal cost of ownership for that agent, very close to 0. We're just playing for tokens. If you're buying an agent off the shelf, you're going to pay for that agent forever by the drink. And if you're stacking up agents that you're buying off the shelf, we truly believe that for most companies, an off-the-shelf approach to AI solution will actually be a cost adder versus a productivity benefit for the life of that company. So we truly believe build versus buy is a critical advantage for C.H. Robinson. And data is critically important for AI, but also is context, right? And we truly believe you'll never get the optimal context with an agent unless you build it, right? We truly believe that's a competitive advantage that we have at C.H. Robinson.

And David, you did say at the end about data. We do have the largest data set in the industry. That data set informs us, allows us to really drive fantastic pricing algorithms. And I always try to remind people that data is not just on things that you win, you get data on lows that you lose. And so over time, we have over 1 trillion data points that come in because we're able to use that to help inform and educate so.

Okay. So we've talked a lot of financial performance we've seen is in NAST on the productivity front, but you also have, call it, 20% of your business is in forwarding. How -- is there kind of a lag where you're taking those learnings from NAST into Forwarding? Kind of when are those kind of going to start to shine through the results?

Yes. I'd say, first of all, it was purposeful and very much an intent for us to focus on NAST from a technology perspective. The operating model itself goes across our entire company. So if you think about a Global Forwarding, which we love that business, it's not in the #1 position like NAST, but it punches above its weight. You think about last year, it grew each quarter while dropping expenses. That was on the back of the operating model. So it has some of the best quality that it has historically within that business. But now that we've had NAST on our focus, we're now going to focus on Global Forwarding with our technology stack to do some of the same things that we were doing for NAST. We're more excited, as Damon said earlier, that we're actually going to be bringing in agentic technology into Global Forwarding. Why? Because Global Forwarding is super complicated for most in the room, a lot of handoffs, a lot of things to really drive a quote within Global Forwarding. Because of time, I'll just kind of go to this. At the end of the day, you have agentic technology will allow us to get data off system, which is what you need in Global Forwarding. And we're really excited that building those agents that help us do that that's going to really drive some of the similar results that you saw in NAST, and we're super excited about it from quoting to a number of other things that we talked about.

Yes. And I would say we're still in the early innings of our tech realization in NAST, right? So I mean there's -- the entire universe of what we're looking to drive efficiency to is quote to cash. And we've only automated a fraction of thousands of processes that make up that universal business model, right? And so we're just getting started on NAST. We are starting to index that tech stack over to Global Forwarding, but both sides of C.H. Robinson, both of our large businesses have tremendous runway to go on tech optimization.

Okay. Great. And then we only have a few more minutes left. So let's maybe talk about capital allocation, Damon. You guys have a stellar balance sheet, net leverage below target. Haven't been that acquisitive on M&A. So highly generative free cash flow model, asset-light business. So where are you going to position that cash?

Yes. Good question. I'll clarify one thing. We may not have bought anyone at scale, but we're very inquisitive. I'd say we're more inquisitive today than we've probably been in the last 15 years, right? So we're kicking the tires on opportunities all the time, right? We're just not going to make a mistake, right? Our approach to M&A is going to be extremely disciplined. It will be the right company we buy. And it could be a traditional broker like ourselves or it could be a tuck-in that brings technology or capability that we think enhances our enterprise capabilities today. But we're very inquisitive today. Now from a capital allocation perspective, certainly, we have an investment-grade balance sheet, maintaining that balance sheet is critical importance to us. We're a dividend aristocrat, maintaining that status is critically important to us. And look, we have the benefit of having an extremely deep funnel of organic opportunities within the 4 walls of C.H. Robinson. So everything we've demonstrated the last 2 years is just getting started, right? We have a very robust funnel of organic opportunities that certainly get a priority from a capital allocation perspective from a funding perspective. And we don't turn away any good idea, right? We're almost in a 4-year freight recession. We've continued to fund all of our organic ideas throughout this challenging time for the industry. We've been an active buyer of our own stock, right? We think at current valuation levels, we think buying Robinson's stock at current levels is a great decision for capital allocation. We say often that we believe the next 2 years will be more exciting than the last 2 years have been for C.H. Robinson, and we're putting our capital where our words are. And then lastly, what I led with, which is when the right acquisition comes along, we won't pull the trigger. It's just -- we will be disciplined, we will be measured in our approach to M&A.

Okay. Okay. Great. I think that's a great point to end on. Thank you, Dave and Damon.

All right. Thank you.

Thank you.

Appreciate it, guys.