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

All right. Hello. Welcome, everyone. Thank you for being here with us. My name is Nick, and I will be the host and moderator and anything administrative related today for this presentation. Okay. So we're going to get started now. Today's webinar is part of our monthly series. We have different topics each month. And today's session, as you can see, is called Strategic Decision-Making with Landed Cost Analysis. If you've attended any of our previous webinars this year, you've become familiar with how we've highlighted topical trends in trade plus various policy initiatives and their impacts on supply chains. Now we pride ourselves in Onyx on taking a quantification view of the topics we cover. We believe that's how it makes this information usable to our clients for day-to-day business procedures. So with that in mind, we wanted to try something a little different this month than how we've covered previous webinar topics. And so we're going to be giving you a front row seat, so to speak, to how we approach quantification work, and this will be in the area of landed cost calculation. If you've been in this business a while, you've heard landed cost come up in different conversations. And maybe while the idea of determining a land of cost may seem simple, once you start to unpack things and try to make it work in practice, it gets more difficult. So just a few administrative details here before we begin. You are muted and your cameras turned off, so just sit back and enjoy this. If you do have questions, we welcome those and just use the Q&A window for that. You'll see that there on the bottom of your Zoom screen. And we'll try to get to the questions as best as we can, either in writing or we'll address them verbally, and we'll leave some space at the end for Q&A as well. If we can't get to your questions, we'll follow up afterwards. We've got about 45 minutes of content here. And last thing here is, if you want to get a copy of some of the slides that we're sharing today, we'll send out a survey once the webinar is done shortly after that. And if you respond to that survey, give us your feedback, you'll get a link to these slides to download. So we definitely look forward to that. Okay. So before we get started with today's topic, I'd like to highlight what we are featuring next month. We have a pretty interesting topic, having to do with trade policy, a focus of that in the U.S. with 2024 elections coming up in early November, the less than 2 months away from that now. There's been a lot of conversation about U.S. trade policy and varying viewpoints from the 2 parties on that. So we'll take a look at those proposed policies, analyze potential impacts on businesses who will need to naturally navigate that landscape in the years ahead. So it should be a very interesting one. You don't want to miss. I hope you can make it to one of these sessions. Probably for those of you attending today's webinar, the first session that's listed there on the left, in more Asia business hours, would be the one appropriate for you most likely. But feel free to attend whichever one works for you. So you can see the QR codes if you want to register now. I'll make sure to drop the link in the chat here shortly. And also, if you follow us on LinkedIn, you'll see that we announced those events usually every week or so leading up to the webinars. All right. A quick overview of Onyx. We are known as Onyx Strategic Insights. We are a division of Expeditors. We were formed in the last few years. Now we offer strategy consulting through the lens of geopolitics and macroeconomics. And that macroeconomics is a good example of how we bring the quantification to our offering, and you'll see that even more so today with the landed cost topic. We offer projects that are tailored to different client needs. These can be one-off projects, which is a onetime need or we have clients who need more of an ongoing advisory relationship, and we offer that type of service as well. So let us know if you have any interest, and feel free to reach out to me, in particular, if you have any needs there. Next thing is, I did mention, you can follow us on LinkedIn. Just to highlight some of the stuff you can find there. Various types of material, a mix of short posts and longer articles. Recently, we started a newsletter. It's called Vantage Point. You can subscribe to that. And when you do that, you'll get notification in your e-mail inbox as soon as we publish something. So a couple of options there, follow us. Just simply follow us on LinkedIn and how an explorer would you want? Or in addition, I should say, subscribe to the Vantage Point blog. And also coming up soon, we'll have a blog by the same name on our own website. So same content in 2 places, something to look forward to soon. Now with that out of the way, I'd like to introduce our speakers for today. We have with us Adam Karson, the Chief Economist for Onyx. He has more than 20 years of experience as an economic adviser to global leaders across a range of industries. He has extensive experience in the U.S., Europe and the Middle East. Adam most recently worked at Chevron as a Senior Economist before joining Onyx where he leads our macroeconomic analysis and forecasting. We also have with us Matt McKenzie. Now he'll be here with us in the Q&A. Adam will do most of the speaking but we also have Matt, who is a lot of the brains behind the data that you'll be seeing that Adam will walk us through. Matt is our Data Architect. Over 10 years of experience in supply chain systems and data is dedicated to developing cutting-edge data solutions that integrate macroeconomic, geopolitical factors to assess and forecast their impacts on clients' supply chains. All right. So now that we have our speakers introduced, I will hand it over to Adam, and he'll take us from here.

All right. Thanks, Nick. Thanks for that introduction. And I'll just echo -- I'll be kind of running guys through this presentation, but Matt is definitely the brain behind this and instrumental. And there's a lot of the technical details. So we'll be answering questions together. So feel free to fire away, and we can have this as much discussion as possible. But what we were going to start off with today is actually just kind of level setting a little bit with a poll because we want to talk about total landed costs and get into some of the details of different use cases. But one way we wanted to kind of kick off with getting a better understanding of just how you and your organizations -- how you approach total landed cost? And what kind of tools, if any, you have available to you?

Sorry, trying to get my thing off mute there. I was stuck. I've launched the pole. You should see that on your screen. I can see people are responding now. So we'll give this just a minute. So it's a single option to select. So that's why it's our primary method, understanding that some of you may go to different places. So we're just kind of curious like what stands out is the -- like if you had to go to one thing, what do you go to what's available and I guess, kind of what works. Just give us a little bit more time, people to answer. And I'll show the results here just a second. Okay. Let's end it now and then let's share the results. So Adam, you should see that, and everyone else should see that as well. And so it looks like mostly people rely on their broker or forwarder to provide this today. That's 40% with second being they don't really utilize it much currently, that's 35%. So really relying on logistics partner or don't utilize it at all. Interesting?

Yes. I think that kind of fits with what we've experienced and kind of why we wanted to build a tool like this. And going to the sort of the genesis of this tool, we recently got asked a question by a client about the best sourcing options and weighing different markets and the cost factors that are driving total in the costs across different markets, in particular, for women sweater. So an apparel company was asking us about some of their products and how to think about cost. And it got us looking at our data in a different way to understand what we could bring together to answer those kind of questions and help not only provide a total in a cost estimate, but break it down into different components that help the client understand why costs are what they are. Think about the sort of margin of error or volatility in those cost estimates over time. So is it a steady cost? Or is there seasonality? Is there a lot of variability in the data? And also how do we weigh cost against other factors like market share? So a particular market may have the lowest cost, but they have a really tiny market share. So there's really not a viable sourcing option in that country. And as we were going through this exercise, what we were hearing from our clients is that they're facing just constant cost pressure. So in particular, coming out of this era of high inflation, there's a ton of pressure to maintain cost discipline, but also manage a bunch of different other priorities, including ESG, geopolitical risk, among others. And then this is also happening in a rapidly changing landscape where there are a number of external risks that can happen all of a sudden or come about slowly and effect and kind of disrupt how we think about the economics of different markets and different sourcing options. And then again, this trade-off of how do cable, I need to maintain cost discipline in my supply chain, but I'm facing all these other pressures. And how do I think about those trade-offs and make smart calculated decisions in the face of so many competing interests. And the challenges that folks are facing when it comes to this kind of -- these kind of questions are -- there are really quite a few challenges, including limited visibility. So there's just a lack of data out there, and efficiency and gathering what data is available. So maybe you have to go out and get it on your bids every time you want to do some kind of cost estimate or benchmarking. It can also be quite expensive to gather a bunch of other data sets and pull them together and spend all the time doing that. And even when you do that, you're probably still going to have quite a few blind spots. You're going to have certain markets that you just aren't able to get visibility into. And so you're not quite sure if you have the full picture. And then resource constraints. A lot of what we hear from clients is that if you were to go down that route, you would be tying up your team and your resources to be doing data gathering and analysis instead of the higher value-added work that you want them to be doing. Not to mention all of the data that I just kind of talked about is backward looking. It's historical data. So how do you think about forecasting forward because costs are going to change. We have some confidence in our ability to forecast forward, but then there's always going to be wild cards and scenarios and how do you plan in those different situations. And so this is leading a lot of clients to feel like they're at a bit of a competitive disadvantage. It makes it very difficult for them to gauge where they stack up against their competitors and benchmark themselves against the industry. So we wanted to come up with a solution for this, that could be applied to a wide variety of use cases. And the solution we came up with was to develop the Onyx total landed cost tool. So let me just give a quick overview at a high level what this tool is, and then we'll go into some details, and then we will get -- also get into some use cases -- specific case studies where we've worked with clients with this tool. So starting with the service overview, the way we define total landed cost for this particular tool is albeit fairly general. We're including 3 major categories: the product costs, logistics costs, and any duties paid. And this is from -- so this is the total landed cost of the product from the source to the destination. We're basically saying from port to port. So we're not including a lot of land transportation costs and warehousing costs. And I'll get into some of those caveats in a minute. In terms of coverage, we're pretty confident we can cover 80% or more of 4-digit HTS codes. The codes that we're not covering are things that are more traditionally moved by bulk. So in terms of containerized trade, we then -- we have even a higher percentage of coverage. And we have over 100 sourcing markets so those origin markets, so over 100 are covered in our database. And we're talking global destinations. So we can go down at the port level and look at pretty much any destination. And then in terms of level of detail, we can go anywhere between 2-digit and 10-digit HTS codes. So a pretty robust tool. Obviously, the larger number of digits made [ Cisco ] the more specificity, but we can also do sort of roll those up into kind of industry or sector views as well. So we think this -- reflecting back on the slide before in terms of the challenges that our clients are facing. We feel like this checks the box is really on all of those problems in terms of improving visibility, it's much more efficient than having to go out and gather data yourself, much more cost efficient. We're eliminating most, if not all, of the blind spots, given the breadth of our coverage. We feel like this is going to gain -- users getting a lot of competitive insights that gets sort of some of those disadvantages. And we also add in our economic forecasting and our policy forecasting to give a sense of where future costs are going to land. And this is particularly very important when we think about scenarios and then doing country-level benchmarking. So ultimately, we're here to help empower your team. We want to give you guys insight to help you navigate the complexity of this ever-changing world and cost structures in different markets. So you can be more confident about your decision-making, be more efficient with how you dedicate your team and resources and ultimately improve performance, right? So optimize those trade-offs between cost and the other KPIs that you are prioritizing. So how does it work? I'm sure you guys -- this is the meat of it and kind of why you're here. You want to see what this tool really does. So it's actually quite simple. You need very few inputs to get going. At most, you need an HTS code, an origin, a destination, you can choose a mode, ocean or air. And you can choose a period of analysis to get you can either narrow or widen the scope of data that you want included in the analysis. Now even more specifically, all you really need is an HTS code. We can fill in the rest. We can sort of give you all the data that's available for a particular HTS code for different modes, for different origins, for even different destinations, if you will. What you get out of that is a very robust set of outputs. And here's an example of a table you would extract from the tool showing in rank order of total landed costs in origin a level -- the LOC index is a level of confidence index, so that gives you a sense of how much we believe in the data. There are always data anomalies and we want to scrub those out. And then this gives you a sense of how confident we are. You have the destination, then you have the item cost, freight cost, duty and total interest cost. And all of these are simplified into a per-item basis. So if you want to move a pair of sunglasses or a mug or an iPhone cover or whatever, this is all boiled down to per item. So that way you compare apples-to-apples across origins, across destinations and across modes. Now a few technical details that we should highlight for you. So where does this data come from? And what do we do with it to get it to provide these kind of output. Well, we have a pretty unique combination of both proprietary data and market data. So we're pulling together half a dozen or so databases that include all the details on product costs, shipping costs, duties, et cetera. And combine that in a way in our products, in particular, we have enough information about characteristics of each product that we can look at its weight and volume, et cetera, and kind of bring everything down to a per annum basis. Some of this data is proprietary. There's shipment level data, and we maintain confidentiality on that data. The data we're showing on that table, for example, is aggregated and averaged and there are other transformations that take place. So confidentiality on shipment data is always maintained. We also go through a pretty robust and rigorous set of data cleansing, including tail trimming and some other anomaly detection methods to ensure that the data that ends up in the output is of high quality. And then on forecasting. We add forecasting to that core data set, usually going out 1 to 5 years. It depends on the product, the market and also the use case of what we're able to do. Now a couple of caveats. So these are important. HTS classifications have limitations. So we can do 2 digits, we can do 10 digits depending on where you land, you might not be comparing apples to apples. So we really have to be careful about how we use this data and make sure that what we are looking at are actually comparable sets of products across different markets. Forecasting obviously has limitations. We try really hard to show confidence intervals or a range in our forecasting. Second decimal point forecast 5 years out, we all know that there's a lot of air in that, so we need to maintain a sense of confidence and give a sense of confidence in our forecast. I also want to highlight that we don't forecast freight rates in this tool. That Onyx doesn't forecast freight rates at all. So what we are forecasting for this particular tool are the product costs and any duties or tariffs that may come down the line. For freight costs, we look at historical volatility, and we can also do scenario analysis -- sort of what-if scenario analysis to better understand if certain events unfold, what -- how that might impact freight rates. But it's not a standard forecast that we use. And as I mentioned earlier, this tool is port to port. So it currently does not include ground transportation, warehousing, but additional -- these additional cost factors can be added on. And I might add, just in general, clients can always bring their data. So we have a very robust data set, but clients can always bring their data as a comparison or in addition to what we have. So what can you do with the total landed cost tool? Here are a couple of examples that I'll walk through very quickly. I think we then have a poll and then we'll start going through some use cases. But in general, we find that our clients have 5 or so particular use cases for this kind of tool. First is country comparison. So evaluating cost basis across multiple markets and looking for the best deals. There's also industry benchmarking. So you can compare your cost to what the rest of the industry is to it. Where do you stack up? Are you paying more or less than your competitors. Forecasting. So how do you plan for the future? You're thinking about potentially changing your sourcing arrangements over the next, say, 3 to 5 years? And you want to know, well, it doesn't know good to know what costs were a year ago. You want to know what they're going to be in 3 to 5 years. So we can add that forecast. And the scenario analysis really gets to how resilient your supply chain is. So under different circumstances, cost structures in different markets may move in completely different directions. So we can look at different scenarios and alternative views of the world, how that affects not only cost but also the volatility in those costs. And then cost volatility itself, looking at seasonal patterns, sensitivity to macroeconomic and geopolitical shocks like again, looking at kind of the resilience component of your supply chain. On the right, I have a couple of just kind of example, very, like high level examples of how that data might be presented to you. There will be a lot more detail in the use cases that we walk through. The next -- let's go to the next poll, Nick, and ask this question on what causes you to do a total landed cost calculation? So in your business, what are the drivers that would move you to get a total landed cost estimate?

Yes. I think we're interested to see -- you see one of these is more on the sourcing side. Some might be a sourcing procurement person or then there's like port to port, so optimal logistics routing or on the sell side to the destination market. So we're just curious like and it could be all of the above, like people that have broad coverage, which is -- I can see actually is coming in as the top response. So maybe we'll unpack that perhaps. Yes, these actually share in the Q&A, too, if you have another response that we missed here. I mean, we'd love to hear that. Okay. Let me just end this here, and then we'll share the results. Seen a few trickle in. Okay, let's stop it there. So yes, you could see hopefully now 74%. So yes, 3/4 of people really all of the above. So it's pretty broad coverage, but nobody really was just looking at the destination market interestingly. But I guess sort of indirectly are just among other things, too.

All right. Thank you. So let's jump into a couple of different case studies. I have 4 here that we can walk through. Let's -- actually, maybe Nick, do you want to pause? Are there any questions in the queue before we go on to use cases?

No questions. I would say, yes, keep going.

Okay. Great. So let's start with the first case study on country comparisons and benchmarking. So this was a client in the consumer retail sector that was looking at sourcing alternatives and of course, wanted to maintain low cost but is very concerned about ESG trade-offs and has made particular commitments to reducing their carbon footprint. So they ultimately were looking at getting out of their current market and finding the next best low-cost options that met their client -- their ESG target requirements. So for this project, it included -- our approach included analyzing different sourcing options for very specific products that the client highlighted, there were about a dozen or so products that they most cared about in this first round. We're looking at different locations and added a 3-year forecast on total landed costs. And then we wanted to compare and contrast total landed costs against other decision criteria, in particular, ESG, and then rank those top locations and identify the best options for them. And so the deliverables and the benefits included those cost estimates and forecasts and a deeper analysis on those particular markets. And here are a couple just snapshots of what the deliverables look like. And you see in the top left, one of the products that we were looking at for this client stores [ were in the ] books. So they were trying to compare costs across a couple of different markets. In this case, China, Estonia, Hong Kong, South Korea, Singapore popped up as relatively low cost and kind of competitive. We then looked over the past couple of years to see how much those costs have changed and how much they've been affected by inflation rates and in particular, the drop in freight rates from 2022 to 2023. So that was in the top right where we're able to disaggregate the total landed costs and then what it trends over time. And then in the bottom left, we were able to do some forecasting and also some scenario analysis to anticipate what -- in particular, what U.S. trade policy, how it might impact us -- costs in different markets over the next 4 or 5 years. And we looked at the scenario of a 60% tariff on Chinese imports to the U.S. and how that would change the cost structure of Chinese imports relative to other markets. And then in the bottom right, we were looking at China again as kind of a mid-cost provider, but we were weighing these different markets against their carbon footprint and their carbon intensity. And so while China was kind of a mid-cost provider who is very cost -- very carbon-intensive, and Hong Kong, South Korea and Singapore come out as much better alternatives in terms of the sort of the cost carbon trade-off, if you will. And these are just 4 examples of a much, much larger and deeper study, but it gives you a sense of how we kind of do these country comparisons and are able to benchmark very clearly the alternatives in different markets. Moving on to the next one. This use case was really around de-risking and nearshore. So this is an auto company that had -- was looking at a bit of a network redesign like a lot of companies, again, thinking about geopolitical risk in China and Asia and potentially looking to nearshore or reshore back to North America. But wanted to do this in a way where, again, cost discipline is a theme throughout all of these use cases, but maintain efficiency of their supply chain and resilience of their supply chain. So we approached this in terms of analyzing, sourcing and production shifts, identifying potential production hub locations in different markets, in particular, Mexico in this example, and did a deep dive into the logistics market in Mexico and whether it met efficiency and resilience requirements. And then we compared different locations on total landed cost and the risk of resilience -- risk to resilience in those markets, and range again at the top locations and identified the best options for the client. Deliverables were similar, and they include all the total landed cost baseline and forecasts from our proprietary data. These deliverables also included an overlay of geopolitical risk across different markets and different scenarios and how that might change perspective into other markets. Here are, again, some examples of total landed costs -- of the deliverables and the ones sort of highlighted in red and pink are our total landed cost factors in very explicitly. But this gives you a broader context of how these sort of sourcing studies kind of look. Where in the top left, this is a dashboard of pretty much all of the analysis that we did for different markets rolled up into one page where we're looking at a variety of different risk factors, including macroeconomic and cost risk, user doing business, corruption, logistics performance, geopolitical risk and ESG performance in different markets. In the top right, we did a deeper dive into logistics performance and compare different markets across a couple of different key performance indicators, including quality of the infrastructure, things like dwell times and overall logistics performance. And then we went deeper into the total landed cost analysis, where we were looking at particular products for this client and breaking down the total landed cost across the markets that they were most interested in. And you can see that you can sort of guess Country 1, in this case, is the only one facing duties, that was China in that case. But then they were looking at other markets where there were new duties. There was a trade agreement in place that reduces to 0. And then in the bottom right, looked at comparing costs to different performance indicators. In this particular case, we looked at, logistics reliability. And we look at reliability in a couple of different ways. We looked at it sort of under normal circumstances. And then we did scenarios in which when those markets are stressed and reliability is at its worse, where do those markets stack up. And then from there, including all the analysis that went into that dashboard, we were able to kind of give a multifactor ranking of each market and say, like, if you want to hit certain cost requirements, here are the countries and how they rank across other performance indicators. All right. So moving on. The third example, this use case was around procurement, sourcing and production. And this is a consumer goods company. Ultimately, they were trying to figure out whether Mexico and Central and Eastern Europe would have sufficient suppliers if they wanted to nearshore their production to North America or to Europe. They are currently doing a lot of business in Asia. Their supply chains are very oriented towards Asia, and they were looking for these alternatives. But before they make a move, they wanted to make sure that they would have a sufficient amount of local suppliers to meet their needs. And they were concerned about cost, obviously. So for this project, we mapped end-to-end sourcing trends across their supply chain for both in Mexico and Central and Eastern European markets. We looked at investment trends and production on the ground in those different markets, get a sense of what the volume of their upstream inputs what were. We analyze sourcing trends and long-term investments in logistics and infrastructure. And then we did an analysis of installed on future supplier capacity, all including through the lens of cost and cost structure and where we saw costs going into those different markets. And so this is a proved -- very comprehensive study. And the assessment -- our assessment included the capabilities of each country to absorb more near-shoring investments, including and specifically on the client product lines. We looked at the countries that are best positioned for nearshoring. So for example, throughout Central and Eastern Europe, we highlighted sort of the best options. And then we also delivered some executive-level communication for a terminal alignment as they were trying to make their ultimate decisions. And this -- I put more slides into this example because it was such a large study, again, highlighting where we introduced total landed costs. But you can kind of -- I won't walk you through each sort of image here. But as you read this, you can kind of get a sense of we were looking at investment trends and looking to where money is flowing into different markets and how that's affecting upstream supply in the clients' industry. And then also look at the policy environment to better understand whether or not it was supportive for nearshoring in their particular industry. And then on that overlay the total landed cost and a forecast where cost pressures were going. So we had a pretty clear picture of how the value chain was evolving and this missing component of total landed cost kind of rounded out the picture to help the client understand that. Indeed, Mexico, in particular, was going to stay at a relatively low cost market and a pretty viable option for them given their criteria for making the decision. And then let me wrap up with one last case study where we were looking at logistics, risk monitoring and scenario planning. And this is actually part of our retainer relationship that we have with the client every month, looking at their supply chain through different lenses and then tackling different questions. This particular work that we did for the client in the tech sector was around monitoring geopolitical risks that directly affect logistics and then quantifying what that impact might be. And then putting that into some executive level messaging that they can use for their own strategy and planning. So the deliverables here included total landed cost forecasts, scenario development and macroeconomic modeling, and then quantification of the direct risks to the client. And so if you've listened to other webinars of ours, you may recognize some of -- the slide in the top left where we kind of highlight some of the key election risks in the U.S. And then moving to the right, we broke that down into specific industrial policy risks as it would affect the tech sector. And we looked at a scenario -- we looked at a range of tariff scenarios. So depending on who wins the U.S. election, we could be seeing any number of tariffs come about. So that -- the chart on the bottom left is kind of a heat map of different tariff scenarios and markets that are most affected. And we took the results of that macroeconomic modeling and the impacts of a tariff scenario, specifically on producer price inflation and translated back to how it would affect total landed cost across different markets. And those different inflation rates flow directly into our forecast for total landed costs. In addition, we had a forecast for -- or at least in the scenario as sort of an alternative view of how duties would change. And so you can see the results showed not only impacted TLC from product costs, but also impact from rising duties. And then ultimately, we were able to translate the macroeconomic modeling into demand -- impact on demand as well. And in this case, we were looking at a particular part of vehicle parts demand that this client serves. So with that, that comes to an end of our case studies. I think we have one more question and then maybe a little bit of time for Q&A.

Yes. Great. Thank you, Adam, for walking through all those. So one last question here is, what you can read right there is, in terms of more of the limitations when you're try to utilize landed cost, when we launched that pole now for you all. And just a reminder, I put a note on the chat. If you have any questions, just submit those in the Q&A, and we'll have a few minutes here shortly to address those. And while those are coming in, I'm just going to also drop in the link to next month's webinar. I'm going to share the one that is sort of the more appropriate time for this audience, given where you are, and that's on October 15. Okay. 2 things at once here. Let's end the poll and share results. So fewer respondents here, but kind of a mix. I think a mix of things. The biggest one is not sure of where to begin, and I can understand that. Hopefully, that's something if you have that need, and this is -- we have that issue and you do have a need for this, please reach out to us and be willing to talk through with you if what we offer is a fit to your needs. Yes, definitely.

Okay. Adam, just one question for you real quick here. So I'm going to just look actually to more of the registration questions that came in. No live questions here for today, which is fine. We had a few questions though, about like what's included and what's not? And you went through a lot of scenarios there. But in terms of like seasonality, different rates, different times of the year or risk of adverse events, the unknown things that just happen or duties when duties change. Can you talk to these and kind of how you and that approach, those types of issues?

Yes. That's a great question. So you can kind of try to boil the ocean. If you want to -- you can -- the definition of total landed cost can really expand to include a lot of things. As you can see from this, we came up with a pretty tight definition of what total landed cost is. But we can -- that can be altered depending on the use case. And so we're not including any kind of land transportation to warehousing, as I mentioned. However, that data can be included depending on the use case. Things like seasonality or adverse events, seasonality comes, I think, more into play if we're going to do a higher frequency type of forecasting or if there's a particular time of year that a client wants to ship something. And the beauty of this is that we have very high frequency, we have daily data basically. We have super high-frequency data that we can roll up to weekly, monthly, quarterly or annually and analyze those types of trends to get a sense of, at least historically, seasonality or -- impact from adverse events have particular markets been hurt more or less than others. So we're able to kind of dig into those details. And then one final comment I'll leave -- I know we're at time here, but in terms of constantly changing duties and tariffs, that's where we get into the forecasting. And our unique ability within Onyx to bring insights on where policy is going in different markets and apply that to our outlook for duties. In addition to our economic forecasting, which forecast the product costs forward. So -- that's -- now I would leave you on and echo what Nick said. If you have any questions, please reach out. We'd be happy to talk to you about what your use case might be.

Yes. Great. No, I think that answers the question really well. And I know you mentioned that we'll welcome -- a client can bring their own data too. So the client has a given set of data, but they're comfortable with based on their carrier relationships or their forwarders. So we have our own mix of proprietary and data sets, but like we're totally open to working with other client data, too, to make it meaningful to the client. Okay. Great. Yes. Well, thank you, everyone, for joining us. You will get an e-mail in a few hours, and you'll get a copy of a lot of this content. If you fill out that survey, so just a link in your e-mail. Please reach out to me if you have any questions. Thank you, Adam, and then thank you, Matt. Really interesting, and I really appreciate it. So everyone, have a great day.