Expeditors International of Washington, Inc. (EXPD) Earnings Call Transcript & Summary

All right. Hello, again. [Foreign Language] to everyone. We have a cosmopolitan audience today. Welcome to one more webinar from us at Expeditors. Today, we are going to talk about technology. Yes. You may think technology from a logistics company, well, it's in our nerd DNA, right? So we're going to talk about the importance of data in the supply chain and the technologies related to these. So we're going to discuss supply chain data, what data is available in relation to supply chain, the digital transformation, what's happening in the supply chain world in regards to this data and a digital toolbox, what technologies are out there to manage data. So before we start, please raise your hand if you hear me okay. I hope I'm not talking alone today, so give me some hands up by clicking the button down there. Okay. Okay. I see a couple of hands up. So great, it seems that I have people hearing. That's good. This session is planned to last about 40, 45 minutes; and we're going to have a Q&A session at the end. [Operator Instructions] We will answer as many questions as we can at the end; but if any question cannot be answered, we will follow up afterwards, okay? And last, we will have a satisfaction survey to keep improving and continue to make these webinars better and more relevant to you. So if you can respond to this survey, we're going to appreciate that. All right? So who we are talking today? First, nice to meet you all. I know I have the participants here, some very familiar faces. Hi, everyone. For those that do not know me, I'm Sebastián Medina, Director of Sales and Marketing for Expeditors Latin America. I'm going to be your host today. I work for Expeditors since 2005, 17 years, had different positions in our Buenos Aires office and since 2015 leading the sales and marketing organization in the region. Natalia, Naty Beck has been working for Expeditors for the last 16 years and has recently taken the CTSM role, Customer Technology Solutions Manager for Latin America, focusing on basically supporting the region in positioning and presenting Expeditors' customer-facing technology solutions and tools for our customers. And Shane, Shane has been with us for the last 17 years. Today, he helps lead the supply chain solutions team in the Americas, the whole continent. Since joining the supply chain solutions team in 2015 as well, Shane has led hundreds of transformational projects for customers across a broad range of industry segments. And Shane is based in Denver, Colorado. So thank you, Shane, for helping us today. All right. Moving on. We're going to start with a poll. So we're going to publish a question for you all to participate and make this a little more interactive. How often do you think supply chain disruptions occur that last 1 month or longer? What do you think? I can't see the people polling but you guys let know if... [Voting]

All right. Are we able to publish the results? There you go. 45% of you think that every 1.2 years; 36%, [ 50 ] every 2.5 years; 17% every 3.7 years and only 2% every 4.9 years. And the right 1 was -- the correct 1, every 3.7 years. Based on research completed by McKinsey, supply chain disruptions of a month or longer occur every 3.7 years. So we have this quote from Charles Darwin, "It's not the strongest of the species that survive nor the most intelligent but the one most responsive to change," is what Darwin told me once. And I guess he was right, right? He was right. This couldn't fit any better what we are going through these days. We move from office to home. Kids move from schools to home schooling. We have a few Zoom calls, team conference calls, some virtual meetings every day. You're doing online shopping and some good things and some others not so good; but we certainly have to adapt to new ways of doing things, right? So -- and so our businesses, we are, right now, going through the Fourth Industrial Revolution, which is the digital transformation. And this is what we want to talk today. And this is, I think, where Darwin's quote applies to being responsive to change, right? So if we go to the next slide and if you look at some of the data that we have here with digital transformation, take a look at the amount of data we need to deal with on a daily basis. 46% of the data that we have nowadays was shared during the pandemic. During the last 2 years, was shared -- almost half of the data that we have these days. We do 5.6 billion Google searches a day. That's crazy. We sent 100 billion WhatsApp messages a day. 95% of business of companies say that they have a problem as they don't know how to manage data, unstructured data. So there's an enormous amount of data that we don't know how to manage and what to do with that. So how and what are we going to do with that? I don't know. I personally don't know, but that's why we have experts that are going to talk to you today. So I will start turning over to Natalia and come back in a while. So Naty, please go ahead. Thanks.

Thank you, Sebastián. Thank you for raising the bar that high up for me. I hope I can answer all of the questions. What we're going to do with all of that data? But -- so hi, everyone. Thank you for being here. Let's start off by thinking what is happening to all of this data that it's now being accumulated by those platforms and how are they affecting the management of the supply chain in the logistics world. So we thought it would -- best to start us off by reminding everyone of what digital means in this space and how it's being applied in logistics, right? So how do we define digital? Let me give you some practical examples. First, digitization. Okay? It's scanning and holding an image electronically. This has been a common practice for several years in logistics. Here at Expeditors, we have been holding image of proof of delivery, customs declarations and commercial invoices, for example. So digitization, it's taking -- turning documents, turning objects into the data. Now the second, digitalization, taking information from that scanned document and transforming it into usable data, so taking like this POD information and turning into a time stamp in an RFP system. So digitalization, it's going to use the data to automate. Now the third one, digital transformation and this first phrase that we have been hearing all about, and Sebastián was mentioning the Fourth Revolution, basically using that information to initiate an action. In our system, we can read a scanned invoice and transfer it to a customs entry and then calculate the duties applicable, all of that electronically. So we're taking the data and transforming it to -- in an operational efficiency, right? So in the pursuit for digital transformation, well, the path that the companies have taken usually have some following characteristics. They could be just starting, embarking on this role. I think most companies are evolving. And many are like steady, gaining momentum, but this momentum sometimes is in silos. So for example, the manufacturing department could be already totally digitally transformed, but the supply chain department could be still running on spreadsheets and e-mails, right? Next one is those companies that are at an advanced stage or even accelerating the last phase and they are totally digitally transformed in all of the aspects of their operation. It has become part of their DNA and those advantage, they are being used to gain a competitive advantage. Now I would like to understand from our audience, and I see we have a lot of people that took their time to be here with us today. Thank you very much. We're going to have a poll and I would like to understand from our audience here today where is your organization on this digital journey. If we can launch the poll right now. Yes, there you go. So those are the options that are in the bottom of the screen. If you can respond, where do you think your company is, right, just an idea, so we can have an idea. And I would like to know because I cannot see the -- how many people has voted. So when we're done, if you guys can finish the poll for me, that would be great. I'm going to have some time here for people to vote. [Voting]

Okay. It's finished? Can we see the results? There you go. Cool. So majority, 35 of the people that responded are already advancing. That's nice. That's very nice to see that our companies here are already going over the digital transformation road. Anyway still, regardless of where your company is on this digital transformation journey, that's for a fact that, at some point, all of us will or already are rely on a software to manage the supply chain of your company. The next one. Thank you. So putting in perspective how the companies have been evolving on its own digital journey, we recognize the existence of a digital supply chain and with that, the need for a system or software, where those interactions will take place. Those are known as supply chain management software or they could be a separate model for transportation management software, the TMS, or order management. Those SCMS systems are predominantly cloud-based. They can be off-the-shelf systems and are often a module to the traditional ERP systems like SAP or Oracle. So the information now can be in real time as there are going to be various parties of the supply chain constantly feeding the SCMS system, and that will enable to make instant decisions such as reordering, canceling order, ocean conversion to air, those things. So this responsiveness makes the supply chain more efficient and cost effective, avoiding of everyone in supply chain [ ones ] that the -- avoiding the excess of inventory, avoiding the delay bottlenecks of the more traditional supply chain. So in summary, a digital supply chain, it's going to be nimble and agile. It will rely on legacy and newer technology. It will continually take data from many different sources to drive optimization and automation. And it's going to react in real time to demand by giving visibility, control and resilience to a supply chain. Next one, please. Thank you. So now to put all of those subjects together and kind of try to link them all, first, we have broadly identified the growth of data, how we're producing data in nowadays world; then putting the companies in perspective. How are they evolving towards the digital transformation? How are you evolving towards the digital transformation? Also how the digital supply chain is gaining momentum? And with that, the need of a software to manage the supply chain. Now we're going to explore some concepts and technologies that are being used in the logistics world that are supporting those companies to improve their supply chain, all of that from a freight forwarder perspective. Okay? So thinking on how the data is reaching the company's ERPs, we're going to cover 3 topics, which involve some technology that are being used and some solutions as well. And they are platforms, integration and the quality of data itself. Now the platforms, they're there in many different shapes and forms. They can be linked throughout the whole supply chain. Here on the green circle, you see a platform, a freight forwarder such as ourselves, would offer. It's basically an interface that packs together different modules. So it's able to input a booking, offers visibility of the status of a shipment and, in many cases, also offers analytical capabilities. A different type of platform would be that centrally managed software that I described earlier. So this software will allow linkage with several different entities in the supply chain and which intends to result into one version of the true for the customer. Often, this platform is part of an ERP system. This supply chain and vendor management would be one of the modules in relation to this system, sometimes also called a TMS, transportation management system, or order management system, OM. Regardless of the type, it will always need to be linked with other systems in the chain, right? So this brings us to our second topic, which is integration. So how can integration be achieved? The most well-known method is EDI, but there are different types of reporting formats. There are document image as well. For higher volume of data, for reporting data, the FTP is a very popular communication method. And when there are multiple connections that need to be built, API could be an interesting solution and can be easier and quicker alternative to EDI. The next slides, I'll go into deeper detail on all of those integration types. But besides of that, we also believe that the quality of data itself also plays a very important role because, well, with quality, we mean the accuracy, the completeness, the consistency and timely availability of the data. If integration is achieved, all systems are properly connected. But the data itself, it's not good. That obviously will cause problems. But first, let me talk first about the other mentioned technologies. Okay? Here, the platform. Here, you'll see an example of a freight forwarder platform; and of course, for this purpose, we're displaying our own visibility system, which is called EXP.O NOW. Good platforms offer all the different services in one package, and they are very easy to use. It's going to offer visibility of all of the steps of the process. Also, those platforms can typically be used to create customized reports and allows you to filter on a specific flow when you want to see. But looking back at that centrally managed supply chain software, it could be very well that a company doesn't want to use an online portal. They're connected to so many different parties. They just want to absorb the data into their own ERP system. So this can be achieved via integration. Now our next topic. Two popular integration methods are the well-established EDI and the relatively young API. Now I would like to offer you a short overview on both. Here are the main differences. Okay? As mentioned, the EDI is the established message type that most of us know. It is widely used in our industry. EDI is popular because it can be created in many different -- with many different associated business rules, including very complex ones, and it's also available in many different formats. We do believe that EDI will stick around in the industry for a while, okay, because industries and companies has put so much investment and time on building the EDI connections that it's not going to simply go away. The downside of EDI might be the speed of implementation. It is relatively time-consuming and, therefore, expensive to set up. That's very inconvenient if you're going to have many connections to build with your central supply chain software. So in some cases, API could be a good alternative because instead of a system-to-system push, API is an on-demand pull type of method. So it's similar to online music apps such as Spotify that when a user wants to hear music, they're going to simply open the app, choose a song and then start to pull in the music. That's the same idea with API. The difference is that you're pulling in the latest status of your shipment and not the music. API, it's quick and cheap. The only downside with it, it's not as flexible as EDI yet, but we do see a lot of development on API for the future. So let me show you how API could work in relation to a shipment. Here to demonstrate how this internal process, the back-end process of an API works, let's think about someone tracking a PO number, like a purchase order they have done in a e-commerce website. So first, there will be the request of the user, then the person's authentication and the API call and then the answer that we're going to -- yes, taking loading, there you go, the answer. So this demonstration here show this whole process at a pace that we could all follow because, in reality, the time between clicking search and displaying the data to the user, it is a fraction of a second. Next up for us to talk about, it relates to data quality. And for that, I would like to bring you a concept, the Internet of Things or IoT. So IoT describes the network of physical objects, the things that are embed with sensors, softwares and other technologies with the purpose of connecting and exchanging data with other devices over the Internet. So when we apply this concept to logistics, we get what we call a sensor-based logistics. But why am I talking about data quality and IoT? Well, because the data about your freight, it's going to be coming directly from the freight and now consider smart freight. This ability to get more accurate data from multiple smart data sources and then create an output, that's what IoT is all about. For example, we can retrieve more accurate delivery times when sensors can now be positioned on the containers, trucks, pallets, even cartons. And another popular reason for using IoT is the ability to check for the conditions -- the condition of your goods. So this is particularly critical when you are transporting foods or medical goods, which have specific temperature requirements or limited shelf life. Another big one is the ability to access information of the location of the goods in real time. Through that, the companies can drastically reduce the number of lost goods. Also, the supply chain people can identify and even prevent theft from happening. Last but not least, through knowing the exact location and the conditions of the goods in transit, a supply chain manager can make decisions in real time. For example, if this road is congested, it can instruct the driver to pick another route. It can extend or cancel a night shift if this -- the trucker won't show up later at night. So this -- and also between a lot of other examples we can share. The data that is being retrieved via the GPS devices is typically accessible via a platform, but it can also be integrated with the supply chain software via API. Expeditors' subsidiary company called Cargo Signal, offers a carrier-agnostic IoT solution. The next, yes. Here, you see just a snapshot of the software platform for Cargo Signal. We just wanted to put here a screen for you to see. And if you are interested on learning more about it, just please make sure to contact your local Expeditors representative. We can go over a lot of the benefits that this can bring. So now that we just saw how IoT is one of the ways to get -- to access better data as it is coming directly from the real location of the freight, this is a great segue for us to think about how we can leverage, how we can take benefit of all of this data to better manage the supply chain. And for that, I would like to welcome our next speaker, Shane. Shane, with you now. Thank you.

Thanks. Thanks, Nata. So I think Nata talked about a lot of different data sources, just recently talking about IoT, immediate real-time sensor-based updates, talked about supply chain management software and communication methods through EDI or API. So we have all this data in the supply chain, and I like to sort of think about it using this slide of how to think about those same data elements through different time perspectives and purposes. So the first one would be the operational layer, which is the supply chain activities every minute. So this is using data to answer the age-old logistics question of where is my stuff, right? So that could be through transmissions to your system, through reports, right, but using data to track down activities. I would say the next one would be aggregating some of that data on a weekly perspective, which we can classify as tactical layer. And this is used to really understand what are the activities, the trends, the performance of my supply chain; where are things not going according to plan or things, maybe opportunities that I see that I need to take advantage of, right? So this is aggregating some of those daily activities into your performance scorecards that you have a finger on the pulse on. And then as we think about maybe the strategic layer, this is rolling up all that same data for the different aspects of your supply chain and then using it to perform network assessments. So maybe they -- these network assessments are put in place or you do them to evaluate, is my network set up to best support my upcoming business strategies. Maybe it's a new product launch or a new market or you see patterns from the tactical layer where maybe you saw an increase of expedites or air freight. And there's something going on in your supply chain that you think has a strategic aspect that you want to go and evaluate through a supply chain design project, or you're looking at identifying what changes at the strategic aspect of your supply chain, so the nodes and the flows you need to get out ahead of to best optimize your network. And we have historically talked about this layer as a -- like maybe we do it once every year if you were on top of things. But for many companies, maybe it's every couple of years. But through the technologies like a digital twin, it now can be enabled by on-demand, so being able to do these studies in a matter of hours or days as opposed to where they used to be done based off of maybe weeks or months. And so a digital twin technology is something that you're going to probably continue to read a lot more about. And [ Paula ], if you go to the next slide, let's talk about what is a digital twin. So a digital twin, it's a new concept that's gained, I think, a lot more awareness over the last, I'd say, last 5 years, especially over the last 2 years. But the technology actually dates back decades. I think the first digital twin that people sort of associate to was from NASA and the lunar module that they built in the simulation model that they built for Apollo 14. If you are a science buff, you may remember, I think it's Apollo 14 that had the famous saying, "Houston, we have a problem." Right? And it was the first time that they would have the computing power, the telecommunications power to actually reproduce in the simulation model the conditions that were happening in space when things went awry and the engine burned out, I think, on the Apollo 14. So the technology's been around for a long time, but it's only been made widely available probably over the last, like I said, 5 years and really gained importance and been able to have more adoption over the last couple of years. And it's not just a supply chain thing. It really spans multiple industries. So you can see here, we have aviation. So companies are developing digital twins of their engine, so taking all the data that they have from the engine, creating simulations, and they use it for predictive maintenance. If you know about a lot of aviation companies and engine manufacturers, right, they're committing to certain uptime, and that's the revenue models that they have. So they -- it's critical for them to be able to get out in front of any maintenance so that they can make sure that their engines are not down for massive amounts of time. So they're using it to get for predictive maintenance. If there's any Formula 1 fans in here, many of the racing teams will use a digital twin to actually simulate and evaluate how different components fit with the different racetracks. So they may use it for simulations to figure out what's the right tuning and the right components for a particular racetrack and the conditions on the ground that they're expecting at race time. And then it's actually used in the third one, a built environment, so actually taking all the information that they can gather around the building, the energy use, maybe the exposure to the sun and the different seasons, the people that transit through it, and they can run simulations to figure out what are the changes that we need to make to all these things to optimize for a specific event. I recently heard about a podcast where actually the airport of Hong Kong has built a digital twin for their activities of the -- all their activities in the airport. And they said that when they think about maybe there's a delay of a plane and there's not a gate available, well, they may use a digital twin to look at not only what is the available gates but also the passenger activities and the security lines and the flows of different items. So it may bring it on the complete opposite side, where they're optimizing for multiple different components, not just in available gate and a specific carrier. [ Paula ], the next slide. So if we take those same concepts and we think about it from a supply chain perspective, we can use a digital twin to really take all of the historical data, the activities of the supply chain and build it into a virtual environment that is a supply chain digital twin. And there's a couple of characteristics of a digital twin. So first thing is that a digital twin is connected, so it's connected to the activity. So we're getting a consistent flow of data that is automatically updated, systematically, automatically updated on some frequency. And in supply chain, it could be daily. Maybe it's weekly. There's different trade-offs with all of this, but it's a consistent and updated environment that allows us to connect to real-world assets with real-world data so that we can have a constant flow with the most updated information. And that creates a virtual model of the real thing where we can understand the behavior. And when I say understand the behavior from a supply chain perspective, we're really talking about the performance of that supply chain, spend decisions as well as the overall design. How is our design supporting or constraining some of those behaviors? And digital twins really helped companies understand the past or what has happened so that they can then use it to prevent future problems and inform decision-making through insight visualizations, analysis, simulation and prediction. So let's kind of transfer from, in the next slide, [ Paula ], to talk about the -- Expeditors' version of a digital twin. So we call it our Living Model platform. We've been building this out for a number of years now. And I think the first thing to highlight is that it is a carrier-neutral platform. So in building this out for the customers, we're not concerned about who the carriers are. We're not just concerned about Expeditors' data, but we're trying to capture all of the rich elements of the data that's in their supply chain. So because it's carrier-neutral, all data is privately maintained in those servers and governed by the NDAs that we set up with the customer. So we're really trying to get a comprehensive view of the different activities of the supply chain. And the team not only provides the technology to give customers a digital twin; but probably more importantly, we bring the resources to actually get it up and running for the customer. So starting with the beginning process of holding the hands of the customer of identifying the data that we want to bring in, how we're going to connect to those and what frequency. That could be from logistics service providers from ERPs, TMSs, SCMSs, right? We're going to try to get as much data as we can to give a comprehensive view. So we'll help sort of walk through that process. And then we're going to do what is sometimes the hardest part, which is actually engineering the data into the database to make it usable. And that means organizing, cleansing, then geocoding, assigning all of these different rules to make it actually usable so that we can then do visualizations and analysis around it. And I think as anybody that's wrangled with lots of different data, right, even on a similar supply chain flow, so Asia into LatAm, you may have multiple carriers. And if you know, if you work with multiple data sets, you're going to have challenges where there's different naming conventions. There's going to be different rules, right? And so actually trying to bring those in into one database requires a lot of work to do that in a one-off basis. And so we'll be able to use algorithms and tools to actually clean up that data where there's limited manual manipulation, and we're setting it up to run on a consistent basis and pushing into the database so that it could be made sense. So from -- once we do that hard work, that's really where the magic starts to begin to happen because we have now maps and modes and logistics information and perhaps purchase order details or warehouse activities where you have a comprehensive end-to-end view of the supply chain that we can then put interactive dashboards on so that you can understand what's occurring at different portions of my supply chain. How are the relationships happening from supply into demand? So we think about that as the visibility aspect of the platform. But it doesn't stop there. So it's great to have a comprehensive view to understand spend, understand activities. But then you need to be able to get into those design studies to actually see how should my supply chain evolve to meet the needs of my -- of our strategy or that's changing based off of demographics. And because we're going to get a consistent flow of information to the platform and it's -- because it's going to be clean and we can apply tariffs to it to give us a constant and ever present baseline, well, that means that we can jump into doing alternate studies right away. And our experience in doing studies is that it takes probably 2/3 of the hours of any study just getting to the point where we say we have a representative baseline that we can then go and test alternate scenarios against. So it really puts you in a position to be on a proactive side of your supply chain, where you are doing multiple studies a month because you can jump and do alternate studies very quickly to go and evaluate various things because we've already done the hard part of getting a baseline evaluation. And then the last piece is control. So we're going to continue to get that data. We're going to continue to receive it. And many customers see the benefit of then being able to control and measure the implementations that they expected. So we'll be able to see and understand if there's any deviations from the plan that we had maybe implemented from one of our designs. So we can get out in front of those problems before they become too big, and it really helps to understand what's causing them and being able to be more proactive about getting them into a spot where they can be just a minimal problem, if maybe a week of a snapshot as opposed to looking at it 6 months after the fact and trying to figure out what happened. So in a persistent modeling environment, these are really the 3 major values that we see engaging in a digital twin. Let's talk about maybe a case study. So if we go to the next slide, so a lot of resiliency. It's been a term that we've used a lot over the last couple of years. We talked -- we showed the McKinsey study. I don't know how recently that study was, but it made me think that maybe the last 2 years probably have changed those month-long disruptions probably a little bit more frequently. The average is probably going to continue to come down. And who knows what the next year will be? Hopefully, we're through the majority of the problems today that we've been experiencing in the past. But resiliency is an important topic. And as we think about resiliency, we're really talking about your firm's capacity to recover. So how well can you bounce back from a disruption when it occurs? And I think that your ability to respond to a disruption is, in many cases, dependent upon how well you plan for it. And so using a digital twin, we can actually simulate when a disruption occurs and actually try to evaluate how to optimize around it. So [ Paula ], you could bring in just a little visual. So in this case, we had a disruption occur with our network, maybe our supply and our demand. So we can take this historical data, and we can evaluate if this type of disruption occurs, how should we best optimize for what nodes would we need to pull volumes from what locations. How would we support our demand? And because the model and the service of a digital twin is continuously connected, you can run that disruption or a similar one week-over-week, month-over-month so that the playbook for recovery is never stale. And the days following a disruption is not when you want to start to create a reactive plan and a discussion with other stakeholders in the company about what should we do. I think that those supply chains that are really best in class are in the proactive mindset. So maybe they're first able to use the Living Model to extract cost and optimize for cost and service. But then as they get that low-hanging fruit, they're really focused on being better prepared and more proactive to focus on things like resiliency. Next slide. So another quick case study on carbon footprint reporting. So carbon footprint, of course, is gaining in importance as it's an item that's been highlighted as really important to consumers, especially of younger generations. Also, shareholders are really starting to ask companies to be more transparent around it. And then, of course, governmental organizations are asking for more and more information as it relates to companies' carbon footprints. So in the Living Model environment, because we have all the inputs for carbon footprint reporting, which is modes, ship froms and ship tos, the weight and the volume, we have all of the key inputs to be able to give discrete carbon footprints as their carbon footprint reporting. So I know probably for many of you that have had to go through that exercise, maybe you've used a consultant, maybe you have resources that do it internally. But it's collecting all that data, trying to come up with a consistent methodology and then saying, "Here is our carbon footprint for last year, and it was plus or minus based off of last year given these reasons, more air freight, et cetera, et cetera." But that's a native function within the Living Model because we have all those inputs. But really where it can also be used is that you can incorporate it into your alternate scenario evaluation, where you can look at it not only from a cost and a lead time perspective in and out but also bring in the metrics of what does it do to our carbon footprint to give another little wrinkle to your decision-making. So in this case, if customer went through a study, they were evaluating volumes into their DC in Reno, Nevada, which is on the West Coast of the U.S. They were using Los Angeles as their main gateway, trucking it from Los Angeles up to Reno. And so you had the transportation for that final leg, which was almost cut in half, and they ultimately made the decision to use San Francisco because there was a lead time benefit. There was a carbon footprint benefit, and then it was a pretty cost-neutral environment for them. So just another wrinkle to think about in terms of some of the capabilities of a digital twin and how to think about carbon footprinting as maybe another layer of the overall decision-making. So I hope that, that was helpful for many of you in understanding sort of where digital twin arose from and kind of where we are today and sort of the Expeditors supply chain solutions' take on the digital twin offering. So with that, Sebas, I'll hand it back to you.

Thank you, Shane. Very punctual. So we have enough time to respond to some questions from our customers. Thank you. So we started by referencing Darwin at the beginning, this acceleration about the need to be responsive to change, right? We touched on the traditional -- how the traditional supply chains and sales being transformed digitally so that we can now see our supply chains in real time. Natalia dived into some of the details regarding the use of those technologies that are helping with this transformation. And Shane explained how we can further utilize this information to simulate disruption and change. So this is the DNA of our topic today, has been data. So we invite you to engage with Expeditors in this digital transformation. And we welcome the opportunity to talk in each of you about how we can harmonize our systems to give the visibility, control, resiliency that you need in your supply chain. So feel free to talk to your main contact at Expeditors. We're going to be happy to help and engage with you on that.

So with that, we have 13 minutes for a Q&A session. We have a couple. I have another one from [ Mario ]. [ Mario ], you are the first man to submit a question. We have women, so welcome. Let's do more, please. Let's go to the next slide, [ Paula ], if you can. Okay. So I think Naty, this is for you, I guess, on the API. [ Elisa ] says, you mentioned that the implementation will be cheaper on API than on EDI. About what percentage on average is that reduction and why?

Okay. Yes, I'll take that. So I mentioned that API, its implementation, it's cheaper than EDI. The reason behind this is because EDI needs to find a common language between those 2 companies to -- in order to effective operate. And the API is like a menu that it's ready from the Expeditors side. So basically, the customer will pick and choose whatever information, piece of information that we are going to deliver as available in our system. And the customer can then quote and program their system to ping, to call our system to collect that information based on their shipments. And responding to the question, how percentage reduction is, it's actually -- the API implementation has no cost to our customers, okay? Different than the EDI setup that, most of the times, it will require hours of people on our IT department. We do have a specific EDI development team. And then, of course, there are time allocated to make those codes, make those translations available to -- so the EDI can work. And the EDI -- no, we don't have that. We have like a menu. Customers then can then plug in because we're going to offer -- we're going to give a credential, like a security token for our customers to utilize. So this technology is completely secure.

All right. Thank you, Naty. Shane, probably this one is for you. [ Shiska ] says, in building a digital twin with the customer, what do you think are the major wins or benefits that they gain?

Yes. Well, I think so there's probably a couple of different dimensions to it. So our experience to customers that are looking at doing supply chain design studies, and I'm categorizing supply chain design studies with the Living Model because I think they do go hand in hand, is that there's probably cost savings and optimization work that can be done. I think the team in a Living Model for customers that first enter into the environment, right, the first year or 2 is all about being able to, in most cases, for most customers, squeezing the juice that's available through cost savings initiatives on the design aspect of it, right? And I think they've highlighted for many customers, it's a 10:1 ROI. After you get that, I think there's the proactive part of then being able to have your supply chain best set up to like figure out if the resilience aspects of it, different pieces of questions that they have where you're just constantly evaluating. I think everybody in this room probably has questions asked to them, what if this happens to their supply chain or what if we did this. And imagine if you could answer those in a matter of days to be able to support some of the executive decisions they have to make. But I think that probably the benefits that don't get highlighted enough are actually in this aspect of being able to align functions, being able to sort of bring multiple functions in to understanding what's happening in the supply chain and having to weigh in on how do we think about these things, what's happening in our supply chain, how can a consistent view of data and the patterns across all functions be brought in to really align and harmonize the groups and create a playbook for the team. And then I think the third piece would be master data management. So as a native function, we're going to find where there's exceptions that then you can go and fix those data corrective issues. We're going to fix it through our algorithms and some of our data cleansing tools and surface those back to you. But then ultimately, it's important to get it back into the master data. And as time goes on, right, like any great innovation, it's tinkering and understanding and seeing and tweaking and then figuring out the next layers of complexity that you want to take into your supply chain, right? The light bulb wasn't invented overnight. It took lots of tinkering, lots of failures, lots of fixing, adjusting. And I think that optimizing all aspects of our supply chain is very much the same way that it's a journey. And a digital twin, I think, is a great way to be able to set yourself up for being the most successful that you can in that journey.

All right. Thank you, Shane. I think that this hard question is probably related, but I don't know if you want to touch a little more on this. And this comes from [ Mario ] and says, on your experience, performing a digital transformation project will enable new business models that create growth through new revenues that were not accessible under the traditional supply chain model.

Yes. I guess I would take a slightly different twist. My short answer is I think that it's a great tool to enable growth as a means of like sensitivity analysis or as a means to use your -- the forecast data or your projections and setting your supply chain up to best capture or support those projections. And maybe you can say what happens if this market, if the Africa market goes 20% or 30%. You're going to be better set up to support that, which ultimately means you're better executing on your strategy, which means that you're going to probably have a higher likelihood for success. So it's another aspect of data that we can bring in of like matching projections and sales and market information into the logistics piece that maybe we already have the data from that we can connect to be able to do evaluations and continue to refresh those as maybe changes happen and forecast change. So I hope that answered it, [ Mario ].