Marc Meyer: 0:04

but it is very important to know, what the numbers say and what's behind the numbers, I would say because, it's a real world business, so there's real world implications, for every decision that we make or that the system, proposes

Tom Raftery: 0:18

Good morning, good afternoon, or good evening where every you are in the world. This is the digital supply chain podcast. The number one podcast, focusing on the digitization of supply chain. And I'm your host global vice president at SAP, Tom Raftery. Hi, everyone. Welcome to the digital supply chain podcast. My name is Tom Raftery with SAP and with me on the show today, I have my special guest Marc. Marc, welcome to the podcast. Would you like to introduce yourself?

Marc Meyer: 0:46

Thanks, Tom. Yeah, hi, I am Mark. I'm working as CCO for, Transmetrics nowadays. And, I'm excited to talk to you a little bit more about AI and logistics.

Tom Raftery: 0:56

Okay. And for, you know, people who are unaware, can you tell us a little bit about Transmetrics?

Marc Meyer: 1:02

Yeah, sure. I guess it's a, it's something that, that came close to everybody's lives in the past year, but before logistics, wasn't the most sexy topic. but the idea of trans metrics was actually already drafted in a 2012. during the transportation conference, I wasn't a part of the team back then but at the time the founders were working as consultants for some of the, largest companies in the cargo industry, and time after time, they ran it through the same problems. And then, you know, there's something struck them, that in most of these companies, there was a explicit issue of inefficiency. To be more exact, the inefficiency in capacity utilization. So a lot of empty space, or I would say space wasted, is the better, a better way to say it. and there was no one really willing to face the challenge, so, they, they wrote down, we still have it on our website, uh, just a little sketch of an A4 with a solution in mind. and as those things go, it wasn't as simple as that. Uh, so

Tom Raftery: 2:01

so what,

Marc Meyer: 2:01

uh, they took, uh,

Tom Raftery: 2:02

what, what kind of inefficiency are we talking about and what was, and tell us a little bit more about the sketch.

Marc Meyer: 2:07

Yeah. the inefficiencies are, broad and wide actually. The main thing is that most of the companies today still, use, um, outdated methods. We've seen anything from, from Microsoft Excel, which is considered modern, to pen and paper, to Plan, track, shipments, and also the number of let's say assets you would need. So anything from trucks to trailers, to ships, and you know, 10 years ago, you had. let's say 20% or 30% of the shipments you have today. So back then it was okay to, you know, just roll with it. You had planners there that most of the time still are very experienced and are, well, maybe 10, 20 years in the business. So they have a gut feeding for okay, I'll need, maybe, you know, 10 vans tomorrow in this particular zip code or, I need two, three trucks going from, uh, country X to country Y and that was fine. but due to a lot of reasons, I think we'll, we can dive into those later, but, it's just enormously more complex than it was before. that means that, simple, planner on his own, or even a small department can no longer, reliably make that planning. So now you're stuck with too many vans or trucks or too little, which has all of these, uh, implications, as you can imagine.

Tom Raftery: 3:27

Okay. And th the sketch that you mentioned. Yeah,

Marc Meyer: 3:30

Yeah, so to sketch was, uh, I don't know how it came to be because I wasn't there then, but it was, uh, a very small, a four with a, a kind of a solution in mind on how to tackle this. And that's basically based on, machine learning and AI. So using algorithms to kind of predict what will happen in the future, using both internal data. So historical data, I would say is the most important one there and combine that with external data to kind of get to a, um, a roster, if you will, of what you needed and when and where, now, obviously that, that sounds great and it's still great, but it took them, quite a few years more than they expected to get it. Right. So, uh, yeah.

Tom Raftery: 4:11

Fair enough. And you mentioned there's been a big increase in the amount of shipments that are happening. Is that because while I knew, I know we had locked down in 2020, which forced a huge increase, but even before that, I'm sure there was a big increase, probably I'm guessing due to, and correct me if I'm wrong, but probably in large part due to a big shift to online sales direct to consumer and like I say, accelerated then by the lockdown in the pandemic, is that, is that it is that, or there more factors that contributed?

Marc Meyer: 4:45

I would say those are the two main things. obviously. The, the, the snowball of e-commerce I would say, or, yeah, e-commerce is I think the right right term there. but also, the outsourcing of production, obviously, as, as been going on for what outsourcing of production to, to other countries, mostly in Asia has been ongoing for decades. I would say, the e-commerce boom, has been going on. Well, depending on where you, where you, where you getting or where you see the hockey stick going is, is probably at least a decade. and so that was a S a slow rolling snowball. And then you have a black Swan event, like, uh, like the pandemic, which just, yeah. Superpower debts, and, yeah, we're we're

Tom Raftery: 5:28

I used to do.

Marc Meyer: 5:29

industry has gone 10 X or something, so it's, it's huge.

Tom Raftery: 5:32

Yeah. I used to do all of my grocery shopping online long before the pandemic. And you know, you go and you order your groceries for the following week and you'd get a, you know, two or three day window of when the groceries would, would arrive. And then when the, the lockdown happened, the whole site fell apart from my locally, they just couldn't handle the traffic. And now. Now when I go to do my groceries in the same place, same shop online. When I ordered them, I'm given, you know, windows within days. So I can say I wanted to come next Tuesday between 9:00 AM and 11:00 AM. And sure enough, bang the following Tuesday between nine and 11, the doorbell rings and it's there, you know, so the, it has changed completely because it was previously, it was, you know, you would get. But, you know, you wouldn't know when now you can say almost exactly when you wanted to arrive and that's when it does arrive. So the level of service has increased massively as well. So it means that there's been a huge, uptake as well of, of, of that. So I'm, I'm, I'm guessing that's leading to a big increase in the requirement for your services.

Marc Meyer: 6:44

Yes. partly it was by the reason why we were founded, I think, in the first place. but yeah. We have several factors, contributing to that. on the one hand there is the, just a quantity that's that's has been well rocket fueled to, to enormous, uh, amounts. the, and then obviously when the amounts increase, uh, it, that goes not as fast, I would say. Yeah, the complexity increases, I would say. And then also. most of the companies that, that are our clients are, well legacy companies and that's not in a negative way that has been around for decades. Uh, and in, in some, some instances even longer. but obviously those, those companies are not used to these kinds of accelerations. they are light like an ocean shipping liner. They correct. course, and then see how it will go on, uh, years and years later, instead of, those, those huge shifts that we see now. So delivery times, uh, the expectation of consumers and myself included by the way, um, uh, if it, if it doesn't deliver within three days, I might as well go to another website nowadays, which is. I hate myself for that actually, now that I mention it, but, but it is the truth. and then we, you know, you have also, shorter fulfillment cycles for, for the logistics companies. and then space utilization becomes, I would say a critical, because if you use the truck, for only 50% that truck's gone and if any new shipments come in, you you'd have to use another truck. So that's not only wasting a lot of, well money, I would say, but also time and, and in the end, uh, it's not good for the planet. There's a lot of, yeah. CO2 emissions, that sort of stuff. which a lot of companies are, yeah, they want to, they want to change something which is very hard to change, but I think a lot of our clients are really pushing the boundaries in, in being better.

Tom Raftery: 8:39

So, how are you

Marc Meyer: 8:40

And in terms of sustainability

Tom Raftery: 8:41

So how are you helping them?

Marc Meyer: 8:43

Yeah. we use a number of technologies of which AI is, is the most important one, I would say. now AI is obviously a buzz word. And, um, since I'm talking to you, I don't have to explain how much, uh, well, how overuse it is, I would say. and, and before, before I go into the details, I would gladly emphasize that it's not some magical cure, all, But what we do and what it does is to make the repetitive and boring tasks go away. So the job and, the function of that, uh, the employees can, can do is is much more interesting than before. As an example, one of our clients DPD group, which is a very big, logistics, operator in, in Europe, we used a, a couple of years of shipment in history, that it was all a mess basically because you have a plethora of systems talking to each other, mostly, interconnected in a way that, you know, it's barely hanging on, I would say. Um, so what we do as a first step is we clean everything. We enrich it a bit, and then we restructure it in a way to make a proper analysis possible. I would say that's the first step, just making things visible. a lot of the time we have different departments, different countries that are willing to cooperate, but just not able to, because they are literally and figuratively not speaking the same language. so I, and I think a lot of people underestimate the difficulty that comes with that because, although these companies, as I said before, are legacy and then older companies, they are, most of them willing to do something. but it's such an enormous test. I don't know where to start. so we start there, and then we, we transform those bits and pieces into something that we can actually make sense of. and then we, we end up with a bit more visibility so that we know, well, you have to the one source of truth so, you know, what's happening where everybody's looking at the same data. and then from there on out, we start to actually enrich the data. making it more valuable for, for everyone, uh, in the organization. For example, we used our machine learning algorithms to guess missing data points, such as weight or, dimensions of, of shipments. And then as you can imagine sometimes something comes in. imagine a truck and there's like three or four shipments or, or packages inside of that truck. now, those packages could either be your every day book, delivery, or, let's say a game or something, which is relatively doable. but it could also be a surf board. And a lot of the time, that's kind of dark whether, whether it's it's it's a or B. So using our, uh, our algorithms, shippers and logistic providers can actually make sense of what it probably is up to. No, there's, there's no guarantees, but it's a, I think we, we bought around 99%, so it's pretty safe. And then you can imagine that the optimization of space is a lot easier because, you know, for example, the weight or the dimensions, where you can say, okay, we can do package a till till T in one truck and a T to C, needs to go into a truck B so to speak.

Tom Raftery: 11:50

Okay. Okay. Okay. So you're, you're like a, a platform for these companies. It's it's cloud delivered. You take all their data, they get logins and they see everything and work from that. Is that the idea?

Marc Meyer: 12:04

Yeah. We, we, we support different, use cases in different, parts of the, industry. So for example, we do a container management as well, where, ocean shipping lines can, uh, kind of actively, monitor and proactively steer their containers where they need to go the quantity, the amounts, that sort of stuff. Also we do line roll. We do last mile. We do a little bit of maintenance. now every industry is different. even within an industry, you have companies running a different strategy or having different kind of safety, a level of safety stock levels. one company would be more, interested in, in always being able to provide, while the other wants to have a bit of a safety net, so to speak, if something goes wrong. So we have to deal with a lot of, challenges and constraints from, from the business or from the industry, but generally we tap into something, existing. So, most of the time we tap into something that's called a TMS, it's called a transportation management system, which is kind of your, your global, steering platform where you, where you see everything that's happening in your organization. And, and we work on top of that and we can integrate with it. So that, that is all in one system. And it's indeed, uh, also accessible as a cloud platform to kind of only, only see what we do.

Tom Raftery: 13:19

Okay. And does the logistics industry have any particular challenges that other industries might not have?

Marc Meyer: 13:28

Well, yeah, for sure. we've seen, a lot of people, other companies and smaller startups also starting up and basically giving up, because the logistics industry is not like any other, I would say, there are so many moving parts, literally and figuratively, um, We have a team that consists of, I would say 50% or 60% technical people 40%, consulting slash commercial people. and all of the people in our, in our company. one or two to maybe not in the, in the HR department to have a very deep understanding of the logistics business, because interpreting these numbers and interpreting the forecast and optimizations that come out of our calculations is, is as important as a calculation themselves I would say. I pride myself in, in the fact that we never made a mistake. So we never, send a, an empty ship, to China, by mistake, for example. but it is very important to know, what the numbers say and what's behind the numbers, I would say because, it's a real world business, so there's real world implications, for every decision that we make or that the system, proposes.

Tom Raftery: 14:35

Yeah.

Marc Meyer: 14:36

And that's the reason why, that's not for everyone.

Tom Raftery: 14:38

Sure. Sure. I know. I gotta think as well that the, potential customer base is massive. As in you get businesses, like you mentioned DPD, they're huge. And then you get some guy with, you know, a couple of vans and a motorbike maybe, and, you know, so, and, and everything in between, right?

Marc Meyer: 14:58

Yeah. I think you hit the nail on the head. we have a very varying, customer base. On the one hand, for example, we have the ocean shipping lines, which are, Well, let's say that the most important ones who do 99% of the, of, of the shipments worldwide are like, well, maybe 200 companies worldwide. That's everybody. and they have, well, a lot of ships, but that's all. And then for example, as you look at trailers, than just in Europe, there's 3 million trailers registered to, well, at least 10,000 companies. So. The scale varies per industry or per vertical or whatever you wanna call it. and then the challenges are, are unique as well, but they all, integrate sooner or later, of course, because they all fulfil a small part of the. journey.

Tom Raftery: 15:47

Right, right. And so can you say, for example, I know you're not into tracking, but can you track a parcel from, you know, going on a container in China, right the way through to delivery to a door in let's say here in Spain?

Marc Meyer: 16:05

Yeah, we could, I think our business is more focused on the, on the asset side. So we would focus more on the, on the container that parcel or package is in, and see where that container goes. And at some point. If the package is offloaded, where does the container need to go? Both from there on out, you of course see the, um, the hub where the, bigger truck gets the parcel and from there it goes through a distribution center and the distribution center there's a van who brings it along to your house or to your apartment, wherever you are. So, we focus more on the asset side and making sure that companies use as less, assets for the most, parcels packages, whatever you want to ship. but in theory, yes, we could add, but it's, it's a very booming space that of the, track and trace.

Tom Raftery: 17:25

sure, sure. sure. No, I was just wondering, I mean, it's through the life cycle of an order, let's say I order something on it's in Chinese. Just following, not necessarily tracking, trace just the fact that it hits touch points that you guys are associated with all the way. Right. And

Marc Meyer: 17:41

Yeah, for sure.

Tom Raftery: 17:42

what are the, what are the big challenges that the, containers shipping companies are facing?

Marc Meyer: 17:48

Basically their biggest worry is a combination of, of capacity. And then, being able to offload on time. obviously the first leg of the most trips is where the trip on sea. So let's take the, your, your example is, from China to Spain, the first part and the longest part is obviously getting it from, from Asia to Europe via container ship. Now, you are not the only one. Who wants something out of China uh, as we've seen, there's been a chip shortage, a huge demand for electronic goods, over the last couple of years. And then, so there are not a lot of containers available and if they are available, they are very expensive to get, a container going. Bottom line numbers have been great for these companies, but trust me, that they would like to see, lower prices and more parcels, I would say, because they have a lot of angry customers right now. who are, saying to them, we've been doing business for, I don't know how many years, and now you're going with a guy who based on $10 more or something. So, they are being in a bit of a pinch. Then when that, container finally gets to Europe, there is a problem of offloading. if I may take another port as an example, the port of LA, there's been a lot of talk about that. at some point there were, I think, 80 or 85. Container ships. So there's not a container that ships and that has, I dunno, how many containers on it, waiting to offload their, their containers. So, and that's not a fast process, so it takes weeks. It's not a matter of, oh, okay. We have to wait around for a day. Uh, no, some ships we're waiting for weeks on end. waiting to offload their, their thing in whatever they have, whether that's, uh, that's coal or, or your package out of, out of a web store. They have to wait for a very, very long time. So, and that something that you can't fix overnight, because that has to do with ports and the efficiency in ports, you have, at the other end of the spectrum, you have just a very human things like a driver, a truck driver is, uh, not able to drive 24 hours a day nor shouldn't he by the way. So at some point he just goes home, for a good night's sleep. And of course that's eight hours or nine hours of, of no trucks. no containers offloading, You can see to, all those hours that he or she is sleeping, people are continuing to order online. So the line is, is increasing while, there isn't, there's no real progress on the offloading. So, uh, they're in a bit of a pinch. and I think every CEO or every top level executive in those companies has also touched upon this saying we've had tremendous revenue growth. but that's not something to necessarily be proud of if we can't fix the problems, afterwards, because otherwise other methods of shipping might be might come in vogue I would say. You see already that, airfreight was something that was historically very expensive. and it's now getting more mainstream because it's just faster. And people, as we said before, we started out with actually a fast is, is key to getting business done.

Tom Raftery: 20:52

Fair enough, the whole AI side. Is that something that, uh, is helping enormously or is it just something that is great for morketing?

Marc Meyer: 21:02

No, it is, it's giving a lot of benefits. first of all, because of the complexity of the business nowadays, it is just not humanly possible to catch up anymore. You have these fluctuations, in, uh, volatility, in, in the number of shipments a day to day, week to week and then historically you had like your ups and downs. You had your seasons, you had your your Christmas, you know, what was going to happen. Nowadays? a new product launch could, could catch you by surprise and, and you're done. so, to kind of improve that AI helps a lot because as I said, the boring, repetitive stuff gets taken care of. So you don't have to go package by package and make a planning which, who takes what basically. So we, you have a standardized planning called rolling out of the AI because of the usage patterns that we had, and then some external factors, you can integrate, whatever you like, you can have an in store API, you can take weather into account, fuel costs, whatever you would like. So basically working with the constraints that, that are already in place, uh, you already get kind of your, your foundational, report or schedule, I would say. and from there on out instead of taking a day or multiple days to actually get that done, planners now get already what they started out with before and then can manually really think about ways that, either it can be more productive or, because they know something out of their experience that the AI doesn't know because AI is obviously steering on data and not on feeling they can adjust it and optimize it even more, I would say. So I would say that, AI helps tremendously in efficiency, but it also makes the job a lot more fun for those people because they were overwhelmed. I would say.

Tom Raftery: 22:49

Okay. And where to from here, what's what's next? What's coming down the line for you guys and for the logistics industry in general.

Marc Meyer: 22:56

Well, for us, I mean, Transmetrics is developed exclusively for logistics and I don't think we want to do or, we'll ever do something outside of that space. So we are, and I think always will be fully dedicated to the logistics and transportation industry. but within this space, there are of course a ton of use cases, which, we want to explore and process we want to enhance. And then even though we are forecasting and optimizing, it's not a crystal ball. So we also don't know for sure what's going to happen. We have our ideas. so that's, that's something that we want to, really be and it's the one is also overused, but a thought leader and real, yeah, torchbearer. It is to be ahead of the curve.

Tom Raftery: 23:40

Okay. And when you say new processes and things that you want to tackle, do you want to name any of those?

Marc Meyer: 23:47

Yeah, sure. we've just launched, uh, predictive maintenance tool. so that's something that's still in the same realm. But it's touching more upon, not, actual processes of, of transportation itself, but more on the, uh, on the upkeep and yeah, enhancing the fleet, I would say. so reducing downtime. Uh, obviously it's it's it's if I can be so blunt, it just sucks if your truck is stranded beside, the road of course. So that's one of those things that we heard from, from customers while we were rolling out our other solutions. So we are very much being led also by what we hear. Um, so that's one thing that we would really want to do. And now that we've, we actually have a solution available for that now, of course, if you have better upkeep and maintenance, that has a huge impact on a few shirts, the tires, the breakdowns in general, I would say, the number of accidents that you have, which we want to keep as low as possible. There's also, and this has made me a more general thing there's regulation, in the most general sense, there's very heavy regulation, when it comes to anything that. But possibly a dangerous, such as a flammable liquids or that sort of stuff.. So you being able to tackle those kind of dangers with technology brings about a lot of, advantages and it saves hopefully, if not lives then at least, assets and costs. So that's something that we, that we really are proud of, accomplishing as well, which is not really in our normal way of thinking. And then who knows what will happen in the future? Uh, there's new methods of delivery. Everybody's talking about these highly futuristic things like drone delivery and that sort of stuff, which might happen in, in, but I don't think it's going to be there next year. Um, but definitely those are the things that we are, keeping track of. Yeah.

Tom Raftery: 25:37

Very cool. very cool. We're coming towards the end of the podcast now, Marc, is there any question I haven't asked you that you wish I had, or any aspect of this that we've not touched on, that you think it's important for people to be aware of.

Marc Meyer: 25:50

Yeah, I would say that what, what I'm very proud of within Transmetrics is that we are, I talked about AI. but I think that augmented intelligence is the, is the term, there. so what we try to do is be more than just a system. we always keep, people in the loop. So we, we, it can go autonomous, but we heavily, advise all of our clients to always keep someone there, because AI is, is refined and is getting much better. And it's it's, as I said, uh, perfect. In what it does. It never makes mistakes, uh, when it comes to objective things. but what I really want to emphasize here is that. And we always believe that, uh, that there should be people, in the loop as well. just to bring, a bit of common sense and a bit of, well it's in some way, a bit of emotion to any process.

Tom Raftery: 26:44

Right, right, right. Good. Okay. Marc. We are wrapping up. Now, if people want to know more about yourself or about trans metrics or any of the things we mentioned on the podcast today, where would you have me direct them?

Marc Meyer: 26:58

Well, people can write to reach out to me, via LinkedIn or via my email address and it's Marc.Meyer@transmetrics.ai. And also there's a lot of information available on our website, trans metrics.AI,

Tom Raftery: 27:11

Fantastic. Mark. That's been really interesting. Thanks a million for coming on the podcast today.

Marc Meyer: 27:15

thank you.

Tom Raftery: 27:16

Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about digital supply chains, head on over to sap.com/digital supply chain, or, or simply drop me an email to Tom dot Raftery@sap.com. If you'd like to show, please, don't forget to subscribe to it in your podcast. Application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast. It really does help new people to find the show. Thanks catch you all next time.