Why Lane-Based Pricing is Costing Carriers Money

While lanes are one of the most accepted ideas in trucking, they're also one of the most limiting.

In this episode of The Margin Equation, Kara Brown sits down with Matt Cartwright, CEO of Magnus Technologies, to break down why the A-to-B lane model is an outdated way to think about pricing, planning, and network efficiency -- and what carriers should be thinking about instead.

In this episode:

1. Why lanes are a vestigial way of thinking -- and what circuit planning actually looks like in practice
2. How freight density within your network matters more than any single lane
3. Why your revenue per mile headline number is probably telling you an incomplete story
4. What it looks like when data replaces the guy who had every rate memorized
5. How to be human in the loop without being afraid of what the data shows
6. Why a 1-3% mindset shift can produce a 10-12% change in your economics

If you've ever said "I have a lane imbalance," this episode is for you.

Find Magnus Technologies: Magnustech.com

Transcript

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SPEAKER_01 0:05

Welcome back to the margin equation. I'm Kara Brown, CEO of Lead Coverage, and your host with Matt Cartwright here, CEO of Magnus Technologies. Matt, tell us a little bit about Magnus.

SPEAKER_00 0:17

Sure. So Magnus is a SaaS-based application, highly interoperable with all the systems that are that are required for the full ecosystem and really is designed to be capable of handling the full order lifecycle for our customers, kind of from quote to cash, every aspect of their business in a single platform.

SPEAKER_01 0:40

And these are really specifically for carriers and brokers.

SPEAKER_00 0:43

For sure. Yeah, yeah. So most of our customers are going to be asset-based, though we handle brokerage as well as many of our customers to do both.

SPEAKER_01 0:53

So you have a really specific and interesting perspective on lane-based pricing and why you just don't think it's the right model for most of your clients. Can you give me a little bit on your lane-based pricing perspective?

SPEAKER_00 1:09

Yeah. So kind of the whole idea of a lane to me is a little bit misconstrued. It used to be like an A to B, B, back to A. And that's a bit of a antiquated perspective, right? So how many times did I go from there to there and back to there? And the truth is that's just not how the industry works. It really works kind of what we call more like circuits, where I have an A to B, B to C, C to D, and I have a kind of a multi-point route that really needs to be contemplated when I'm doing RFPs, when I'm doing spot pricing, those kinds of things. How are my assets going to move through really the network versus back and forth in a lane? And how do I go how am I going to price that to contemplate what's how full are my truck's trailers going to be throughout the evolution of them moving through the real network versus moving back and forth from a lane?

SPEAKER_01 2:13

So you talked uh before about this high this kind of network or circuit planning. How is it different than lane-based planning? Like what are some of the operational differences between a carrier who is doing circuit or network planning and someone who's a little bit stuck in the A to B lane planning world?

SPEAKER_00 2:35

Yeah. So the reality is operationally, most people don't have the option of lane A to B. That's kind of a vestigial consideration of how they think about it. And often it's a a little bit of the industry saying, you know, from this origin, you're going to go to this destination. And there's an assumption that, okay, now I'm just going to come back and pick up my next piece of freight, or I'm going to find freight out of that destination to get me back to there. The truth is you have really more of a collection of lanes, if you will, that fill out your network. And freight density within your network is way more critical than just a lane. But you have to be aware of how do my lanes link together to create a profitable circuit. So how long are trucks going to, trucks, trailers, drivers going to be out in this network? How often am I going to have empty miles versus paid freight miles along those lines? And it's not as simple as an A to B, B to A. And so there's a multitude of factors that people need to contemplate. And I think it can be difficult for people to think in those terms, especially when you're thinking about pricing or this specific load or whatever the case is.

SPEAKER_01 4:20

Technology is coming fast every day, all day, right? Is it a is it a is it a business imperative that this sort of thinking change long term? Like are you seeing it as something that carriers really need to get a handle on?

SPEAKER_00 4:36

Yeah. Yeah, I I think it is. You know, we all know that you don't get paid to ship air.

SPEAKER_01 4:41

Yeah.

SPEAKER_00 4:42

Um, and just a baseline assumption or an acceptance of the industry is 30% deadhead or whatever the case is, it's it's just not sufficient for how we should approach the business. Uh there is a complexity that most of the carriers don't have the tools to be able to understand what do their circuits look like in real time, what are the seasonal nuances associated with it and those kind of things. But I I think it's critical that people have to they'll often understand that these circuits exist. The challenge is how do they they understand them and visualize them and take advantage of their data to have empirical knowledge of what their circuits are. But I think it's absolutely critical to continue to make operational improvement that takes advantage of the notion that lanes are pretty antiquated in concept and they don't give you the ability to maximize your your laden revenue per mile.

SPEAKER_01 5:47

And when you say latent revenue per mile, you're including in that deadhead miles, right? You're including in the circuit the opportunity that is just within a normal cost of doing business as a carrier, which is deadheaded miles.

SPEAKER_00 6:01

Yeah. I mean, so your laden miles are how many, how much of the time in the circuit do I have freight, right? So yeah, when you when you contemplate your total efficiency, you know, it's both laden and unladen. So how does it work within, you know, within my freight network, within how I'm pursuing additional contract freight, spot um buys, those kinds of things that go into their driver satisfaction, right? Asset utilization, all the things that come into play. It's it's really kind of a holistic approach to how do I think about what my trucks, drivers, trailers, what are they doing every day. They're not going A to B primarily. You know, it's it's a bit antiquated. They're really going a little bit further, whether it's going home, whether it's uh doing fuel or taking their truck to maintenance, those kinds of things. It's a multi-stop consideration. You think about your Google Maps, right? And you say, hey, I want to find a fuel stop along this route. It doesn't just say, well, hey, it has to be perfect. It can deviate slightly, but it contemplates all that. And that's kind of how they have to think about that as well is how do I contemplate the entire running miles and maximize my laden or paid miles.

SPEAKER_01 7:20

And the you've talked about this before the the miles that aren't just the shipment, right? Like that also has an impact to the carrier. Sure. And not really understanding the total cost to serve your customer because maybe you didn't have to stop for gas or you, I don't know, got lost. Like, I don't know why you would get lost in 2026, but it used to happen, right? We used to sit on the phone with drivers and get them to the DC, right? And so there are things that come up that are beyond just the point to point. Yeah. And the late the old way of kind of doing it and thinking about it doesn't take into account all of the cost to serve the customer. And so are you finding that when a carrier gets access to all this data in one place, that it helps them make better decisions?

SPEAKER_00 8:20

For sure. So I think there's there's some old ideas of, hey, if I get six bucks revenue per mile, that's great.

SPEAKER_01 8:29

Yeah.

SPEAKER_00 8:30

You know, the first stratification is is it a long haul or short, right? And then the other big question is, how do I get my assets to pick up that freight? And once they deliver it, what am I going to do with them then? So headline number, six bucks per laden mile, maybe great. The underlying story though is you got to get somebody there to pick it up. And then what do you do when you deliver it? And I think those um kind of pieces often get lost. So with us being able to draw better circles and highlight information of you don't naturally get to this origin, but you may naturally get to this destination. So you've you've developed your network to service that. So six bucks may be maybe great, right? Sometimes, though, it's the opposite. Three bucks per mile may be great because you're running that same uh geography typically unloaded or empty, right? So so there's a number of factors that our customers now can use to understand what does it take to get the asset to the origin? And then when it finishes, what what are they going to do afterwards? So I think um you know the the old consideration, this kind of goes back to Lane from A to B, there's some headline numbers that people can can consider, but it's really kind of how is that across full-time continuum? How am I making sure that those assets are making money the entire time, not on this single shipment, uh, just because there's there's a precursor and there's an after that that most people have a hard time really understanding.

SPEAKER_01 10:16

So one of the ways to solve that problem, right, must be just the volume of data that a carrier has, either in a legacy TMS or in Magnus, et cetera, and applying a mathematical model, otherwise known as AI, right? And I'll let you give us your difference between is it just is it just math, is it machine learning? Like you must be using advanced algorithms to pull this density together and then give this information back to a Magnus customer. I mean, I'm I'm making a big assumption here, but yeah. I hope you can share with us the like the way that Magnus is doing it for carriers.

SPEAKER_00 10:57

Yeah. So I think the the biggest thing that we do is we actually using math, plot the geography really. So probably the easiest way to explain it is you know, person one says, hey, it's Chicago area. Person two says, Yeah, I understand Chicago area. Person three says, Yeah, I understand Chicago area. The problem is in their mind, one person maybe say in Chicago city limits, one person's got a little spike out this way, and the other person, you know, drags it all the way to Indiana. Trevor Burrus, Jr.

SPEAKER_01 11:30

As a Chicagoan myself, Aurora is not Chicago. Well, there you go, right?

SPEAKER_00 11:36

So for us, we take all of the actual shipments, which are actually a point in the world, and we dynamically generate what Chicago really is to you. It may be that most of your shipments are in Evanston, right? Well, if you've if you've cordoned that off and somebody says, hey, can you get freight out of Chicago? If you don't really think about what are my what's the reality of what this label on this geography means, it's hard for you to really share across multiple people what's the impact of that. So our systems are going through and uh geocoding all of the actual shipments and building the heat maps dynamically, not based on I've been doing this for 30 years and this is how I think about Chicago. This is really empirical heat map of what if you want to call it Chicago, that's fine. What does Chicago really mean? It may be, you know, kind of a big star-looking shape, but you've got density there that we can prove empirically versus just this is how you think about Chicago. So, and that's a hard thing to do, um, especially dynamically, and that's why we're using AI tools as well as machine learning and math to overload those things together. The other big thing about geography is it's different if it's an origin and different if it's a destination. How many times you operate in an area is an insufficient question. You have to know how many times am I picking up freight versus how many times am I delivering freight in those geographies, right? And then of course you've got time in there and seasonality considerations. So I think those things for the human mind become almost impossible to manage all those variables, which is why our solutions are uh dynamically doing it off of real data with kind of empirical evidence-based solutions, so that when we say Chicago, do you mean when you're picking up freight there or freight's originating there, or when you're delivering? So they can be totally different answers, uh, even though the geography is similar.

SPEAKER_01 13:48

Have you seen this materially change someone's business? I would imagine, you know, I grew up on the floor of a brokerage. There was a guy three, you know, seats down from me who could give you the rate per mile, like an encycloped in encyclopedia, right? And these guys still exist.

SPEAKER_00 14:06

Yeah, yeah, for sure.

SPEAKER_01 14:07

And I would imagine that a new customer coming on Magnus, they've, you know, maybe they're coming from a legacy TMS, maybe they've been using spreadsheets for a long time, or maybe the guy who has the rates in his head just finally retired and they're moving to a real data-based decision-making process. Has it like materially changed some businesses? That must be an incredible feeling. I know getting a little feelings here on you. Yeah, but just like having the opportunity to like really change someone's business and and like, hey, mathematically, this is where you have density. I know you think it might be in Aurora, but it's actually in Evanston, and those are two very different places, that must be really, I don't know, impactful for you.

SPEAKER_00 14:55

Yeah, I it it is. I think the hardest part is people being willing to almost re reject their existing reality and go, hey, I I don't I'm not saying you're wrong or right. I'm just saying here's exactly what the data show. And so your idea, not wrong, but it's not always perfectly supported. And then the other challenge is you got the second person, third person. So if they're if they're coming from a true uh consideration that's data based, it's a lot easier. So the old idea of what's the revenue per mile from here to here, well, the the one big one that that I see is oh, the city is Evanston. So it doesn't get the rate per mile if it's Chicago to Kansas City. Well, the truth is, based on your actual freight patterns, Evanston actually is super easy to service, so it should get the the rate here. Or it may be that, yeah, it's generally close, but you've got to you've got to move assets 30 miles away. It's really difficult. You don't have density truly in that area, so you need to increase your your revenue per mile. Um, and I think the other thing is just kind of people being willing to accept the data is just the data. It's not my opinion, it's not your opinion, and it's not a slight on your opinion. You're you're directionally correct, but I'm gonna give you 3, 4, 5% change that results in a 3, 4, 5, 10, 12% change in your economics. And in our world, even 1, 2% is huge, right? We're we're generally thin margin. You know, nobody's handing us a bunch of a bunch of money, right? So getting a 1, 2, 3% change just with a slight willingness to contemplate the data actually is the data, uh, is a is a big win for them. But it is, it is a challenge, right? You you almost have to reject a little bit of your own reality that you've built up for years, decades, and just go, I'll okay, I'll listen. And and that's once they get over that fact and they're willing to listen, it's it becomes pretty self-evident, like, gosh, I never really thought about that, right? And part of it was there weren't tools in the past to um really materialize what was the reality. It was my brain still rules, right? Now we've got, you know, AI and other models that go in and say, I don't need to necessarily rely on your only on your knowledge. I can rely on the data. And then I want to make sure those are complementary of each other, right?

SPEAKER_01 17:54

I can imagine there's someone listening to this podcast or watching this webinar who is thinking what you just said, right? I've been doing this for 30 years. Sure. No AI model can tell me better than I know my business, my space, my customers, right? You and I have both experienced this. Is there a moment where where it clicks? Is there in your experience as you're implementing new customers, as you're as you're exposing business owners to new forms of data? And have you seen a change lately?

SPEAKER_00 18:34

Um I don't know that there's any single moment that's the the aha moment. And I think it's because you have a a lot of your knowledge in realities that it's not one thing where you go, oh, okay, now I'm a full believer. It's kind of an evolutionary consideration where they go, okay, yeah, I could take this, take this, take this, and yeah, this is getting better and better and better. So it's it's it's kind of a building of knowledge and trust in the system that it actually is doing things smartly versus just a one moment where I go, okay, I'm gonna take have total faith in the technology, which I think is important. You always you always need to be mindful that your experience, your knowledge is highly valuable, right? We're trying to augment that, not just fully replace it. Over time, the augmentation of your model just gets better. It's not wrong. You definitely know what you're doing. You definitely understand the industry. All we're saying is we can take in a lot more variables because our AI or ML or just computers' capacity to take in the other 70 variables is more significant than any one person. So it is really kind of an evolutionary versus a revolutionary consideration. Uh and so I think it just it it takes kind of tearing down some of those walls in individual capacity of this is slightly better now, this is slightly better now, this is slightly better. And over time, building that trust with them.

SPEAKER_01 20:16

Are you you're still can we call it human in the loop, right? The idea that I really like this idea that, hey, that the data is there, the data is correct, right? Like directionally. I like the idea of directionally correct. What's your advice maybe to business owners that are thinking about, you know, as a business owner myself, there's like this cloud of AI coming for me, right? And how I invest, I am sure that your, that your, your carrier and broker customers and prospects are are thinking deeply about where am I going to invest. And I don't want to give up the control to the machine. What is your, what is your kind of advice as you've been going through this? And you're really a technologist at heart, you Matt, on on where the human in the loop needs to stay, where the human component is still really important as you integrate and invest in these new tools like Magnus.

SPEAKER_00 21:15

Yeah. So I think the the most significant is the humans can handle exceptions way better, right? There's a lot of things that we can automate ensure a fully autonomous scenario would be great. But the reality is that's way down the line, if ever. So I think, you know, when we think about how we approach it and how they need to think about it, number one, just be willing to be critical of your own process. Don't even conflate it with technology or whatever the case is. Why do you do this? Why, why does this process exist? All those things, right? When you start to look at that. And then for the technology part, when we say, we want to automate this, we want To assimilate this into this path. Don't be defensive simply because this is how you've done it. Be willing to go, hey, does it create value? And that's kind of our perspective, too, is we're going to question everything you do, not because it's right or wrong. It's because we want to understand is their value, number one. And number two, is their opportunity to take cost out, right? So I think the the first thing is they they have to be willing to go, we're okay with questioning things, right? Not with a right or wrong, just question why do we do and how does it create value. And so I think for for them, that's that's going to be the big consideration that that we look at, and then from there being able to then sensitize just to exception management. The way they say that 20% of the problems is 80% of your effort. So how do I go, okay, one, I can get that down to 10% problems and now 90% of your effort, because those small tweaks that humans still have the capacity to really solve in a unique manner, and those exceptions require that uniqueness, are where the value really gets gets high for them. And if I can take a lot of the kind of drudgery and other things out of their uh workflow through some of our automation and AI tools, then they can really focus on how can I deliver high value in the exceptional situations. And that's their primary intent.

SPEAKER_01 23:35

It's interesting. We at Lee Coverage talk to a lot of carriers and brokers all the time. And a lot of them talk about service as a differentiating factor. And I hadn't connected the dots until you just said that. But if you have 90% of your effort on 10% of the loads that are problem loads, imagine how much how I shouldn't say that, imagine how well you can service those exceptions, which is really what service is all about. For sure. You don't need to have a human being tracking every load from Chicago to Arkansas. Like it, it's gonna go, right? But the exceptions are where, and so if you had 90% of your firepower on the 10% of the of the loads that are a problem, how you can just absolutely create raving fans out of customers.

SPEAKER_00 24:26

For sure. Your customers are happy, you're finding things before they become a problem, you're handling before you just go, well, I'm gonna accept a service failure. But I'll tell you one of the things that that we find is people will focus on the 90% and be like, hey, I want to look at all these loads, you know, that are you know within my appointment windows. And I go, the general assumption is you're gonna hit that. And if you're not, we should be able to surface that automatically versus you just going, okay, I want to look at these, look at these, look at these. So they have a natural tendency to look at that 90% that's happening. I think there is a little bit of human nature in that you want to see the positive versus just look at the negative. Just show me where I'm green. Yeah, so you go, okay, I feel good about having green, right? Yeah, I've got some red, but I get that that kind of reaffirmation of my green too, right? Yeah. And I go, okay, well, let's put a big green over here, but don't look at any of it, right? We'll just give you that and make you feel good. And here's really your work cue, and you can make a difference in these from red back to green, right? And so uh there is there is a challenge where I think people a believing these are the exceptions or the impending exceptions and shifting from, you know, I do stuff right 90% of the time. Why do I need to continue to monitor my 90% effort? I don't. I just need to accept that and then trust that I can spend my time on what can I get back to green? And what can I not get back to green, but handle better, right? To maybe get it back to a yellow or at least manage expectations of customers. Most of the, most of their customers are they're okay if the the expectations are correct. If you fail and fail and fail and you never reached out ahead of time, it's a problem. Right. So I think um just shifting that mindset into realizing that most people do things right most of the time. And let that go, right? It doesn't need to be in your work stream. Here's the areas where if you could spend all of your time, you would make a significantly higher impact, both financially and you know, in service expectations, those things.

SPEAKER_01 26:44

It's a a little bit of you've been talking a lot about kind of um change management. Thinking that way is a hard way to think. It is, right? As a leader, like, hey, we're doing great. I don't need to pay attention to the good stuff, just give me the hard stuff, right? I think it was Elon Musk who said um being an entrepreneur is like chewing glass. Like he only gets the worst problems, right? Like and if all you're doing is focusing on the on the 10% that's broken, it can feel like you're not doing anything right. But I think that's really good advice.

SPEAKER_00 27:15

Yeah, yeah. And it it's hard to, it's hard to give that up, right? You need that affirmation sometimes. Yeah. But the reality is your impact is is really on making improvements.

SPEAKER_01 27:25

Yeah, and you've talked a lot about value in our time together. And I think the value you can drive is by turning those 10 or 20 percent of exceptions into raving fans.

SPEAKER_00 27:34

For sure.

SPEAKER_01 27:35

So I'm this was such a good conversation. We started at the beginning of our chat talking about lane versus circuit planning. We went sort of a different direction, but I don't hate it. Can you connect it all back for me? Can you connect the the change in mindset from lane planning to circuit planning to thinking about it from a data perspective and then change management in the business? Yeah.

SPEAKER_00 27:59

Yeah. So I it kind of all hinges on the idea of we have our realities of what the world is, right? And lanes is a great one. I hear, I hear people say, hey, I have a lane imbalance. I have this, this, and this. And I'm like, man, I need you to abandon that idea, but I'm not rejecting your reality. I've got to do something different all the way to what we're kind of talking about of exception management. So if you think about lanes, it's just a great illustration of these are generally accepted ideas, terms, industry things. And we're just saying, hey, let's look at them slightly differently. And that kind of goes throughout the business, right? How do we look at things just slightly differently so that we can turn the knob here just a little bit more to improve our yield, our profitability, our asset utilization, our driver satisfaction, our customer um satisfaction, those kinds of things. And so Lane's kind of is a is a good um indicator of this makes sense to most people when you say it. And then as you start to shift over to it's really circuits, and then origins and destinations have to be handled differently. It's a little bit of a an analogy of the entirety of how we're thinking about you know, these are the problems in the industry. What are the solutions in the industry? So kind of runs akin to all those things. And lanes is an easy one to illustrate. This is something everybody understands. That's a good jumping off point to think about how do we make it better.

SPEAKER_01 29:31

I really appreciate you taking something as simple as Lane's and turning it into like a mindset change. Yeah, that's really great. Well, thank you so much for joining me, Matt. Will you tell our listeners how to get a hold of Magnus?

SPEAKER_00 29:43

For sure. I mean, the easiest way is just go to the site, magnustech.com, um, reach out, phone number, there's a web form out there. There's a little simple ROI calculator out there that that people can use to kind of look at you know, what can Magnus do for you to improve your business? But you know, e any of those are there. We're we're at a lot of the industry conferences. So come up, say hi, happy to talk to you about any of the business. You know, this is uh you know, our passion for sure is is the industry, not just the software side of it. It's it really is the industry. So reach out and in in the website or or phone or at one of the shows. Happy to chat anyway.

SPEAKER_01 30:23

Awesome. Thanks for joining me, Matt.

SPEAKER_00 30:24

For sure.