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

Right. Hello. Welcome, everyone. Good morning and good afternoon. Thank you for attending our topic today. We appreciate your time to spend with us. My name is Nick, and I'll be your host and moderator and we'll handle any sort of administrative issues for the session today. This is part of our monthly series of webinars we're offering throughout the year. And today's session is called strategic decision-making with landed cost analysis. We'll be giving you a front row seat, so to speak, on how we approach the quantification side of landed cost calculation and I'll be introducing our speakers here shortly. Before we get started, just a few administrative details to cover. [Operator Instructions] Lastly is we also want to hear your feedback overall on the session, and so we always send out a survey once the session has completed. And there's a few questions there. It's pretty quick to respond. And if you would like to get a copy of many of the slides today, you need to fill out that survey, and it will take you to a link where you can download those. And again, your feedback is really helpful for us to kind of decide what to do on our upcoming sessions. Okay. Before we jump into today's topic, I do want to mention what we have coming up in about a month. So our October webinar has 2 options to attend. And it should be a really interesting topic. We'll be talking about trade policy in the U.S. 2024 elections. And so what role does trade policy play looking ahead, depending on which candidate wins the presidential office and potentially what happens in Congress. What we'll see in terms of different trade policies starting next year. So it should be a really great session as you're planning ahead, making your strategic plans for the next year. A couple of sessions probably for those of you attending today's session, the 1 on October 17 will be the most convenient, but certainly, whichever option works for you, we'd love to have you there. Okay. A quick overview of Onyx before we jump into the content. If you haven't heard of us, what we are is a division of Expeditors. We were formed in the last couple of years, and we offer consulting through the lens of geopolitics and economics. We offer projects that are either ongoing in a retainer type relationship or more of a one-off scoped out project and help our clients solve different types of problems in terms of policy planning, economic issues, whatever it is, you're trying to work through, we offer various projects for that. So let us know if you have any interest there, any needs. I'm happy to talk to you. You're welcome to reach out to me and explore that. One more thing is if you're interested in this kind of content that we're offering today and in our webinars in general, we encourage you to follow us on LinkedIn. We have many posts a week. Some of these are short quick takes. Also we do longer-form articles and analyses that you can download, sometimes in slide decks. And so to keep up with all that information, following us on LinkedIn is a great way to get that. Recently, we also started a newsletter. It's called Vantage Point. So if you go to our LinkedIn profile, you should be able to subscribe to that. And that's a great way to get notified when that longer-form content is published. It will go right to your inbox. So that's another option for you. Okay. So I'd like to introduce our speakers today. We have with us Adam Karson and also Matt McKenzie. You'll hear mostly from Adam today. We also have Matt with us in the session as well. So Adam has -- he's our Chief Economist of Onyx strategic insights and he has more than 20 years of experience as an economic adviser to global leaders across a range of industries. His extensive experience in the U.S., Europe, and Middle East. And he most recently worked at Chevron as a senior economist before coming to Onyx where he's responsible for our macroeconomic analysis and forecasting. Matt is a data architect products and has over 10 years of experience in supply chain systems and data and he is dedicated to developing cutting-edge data solutions that integrate macroeconomic and geopolitical factors to assess and forecast their impacts on client supply chains. So welcome both of you guys. Thanks for being here. And so I'll turn it over to Adam in a second. But before we jump in, we just actually want to launch a pole to kind of help level set, we'd love to hear from you all in terms of landed cost. We're going to talk a lot about that today. And like how do you get it today? What's your primary way of doing that? So just give me a second here, I'm going to launch this poll and should be coming up now in everyone's screen. So there's 4 options, and we're just looking for your primary method, understanding that you may use multiple methods. But when we ask this question, when you see this, kind of what comes to mind? What's the primary way you go and find this. And this will help, like I said, level set as we're talking through the content. So I'm going to give you just a minute here to respond. We do have a couple of other polls coming up throughout the session. So there'll be more chances to give your feedback. Okay. It looks like we're starting to slow down in our responses. I'm going to just call it now and share the results. Adam, can you see that, okay?

I can. Yes.

Okay. So hopefully, you all can see that, too. It's like kind of a split between 3 different areas with basically a different provider being not really an option that people are using. So that's kind of interesting. That's roughly like 1/3 across those 3 categories.

Yes. I think that's consistent with what we've heard from our clients some have a tool available. Some have to kind of go out in externally and kind of ask that information and others don't have a solution right now. And just to kind of maybe jump into some -- into the content now and give an overview of our tool. That certainly -- that poll is really helpful to kind of level set here, just kind of better understand to the audience and your needs here. Because we often get these kind of questions about total landing cost and how to find the best sourcing options, maintain cost discipline, and weigh cost against a variety of other factors and key performance indicators that help drive your business. But our clients also want to understand sort of what's under the hood, what's driving costs? What are the factors that determine total landing cost? What direction are they heading in? How do you compare across markets? What's the variation or volatility in that data? Is there any seasonality? How confident are we in the data and so just shown here on this slide, is just one example of the type of analysis that we kind of pull together for clients being able to quickly and efficiently compare costs across a bunch of different markets and then drill into some of the specifics behind that data to help them think through what are the best cost options in terms of different markets for sourcing? And then how do you weigh that against things like market share. Like are those markets big enough to even source from, even they may be low cost, but if they're a tiny market, and you can't source from them, then it's not worthwhile. But when we do this type of analysis, what we're hearing from folks is a couple of things. First is everyone is under cost pressure. Everyone has the mandate to at least maintain costs, if not lower them. But you don't -- this often can lead to sourcing from low-cost countries, but that may be counterbalanced by some of the other external risks in those countries. And also constantly changing cost structures, whether it's exchange rates, inflation rates, changes in commodity prices or just external shocks that kind of disrupt the market, which we've all experienced many of those over the past, say, 5 or 6 years. In addition to a variety of geopolitical risks that pose uncertainties for the future and thinking about not only the cost today, but how costs are going to evolve over the next 3 to 5 years. And then how to balance costs with different trade-offs. So things like ESG are coming up more and more in conversation. And it's not always -- there's not always a linear relationship between cost and ESG performance or time to market, ease of doing business and other factors. So we can, in a sense, sort of put $1 figure on those trade-offs and understand like moving between different markets, what you might consider in balancing your different KPIs. Now easier said than done. There are a lot of challenges in doing that type of analysis. And as we've scanned the market and looked for a solution to these kind of questions, and talk to clients. What we found is, number one, there's limited visibility into cost structures and cost analysis around the world. So the data is pretty opaque. A lot of the data lacks quality, and it's hard to really have confidence in granular cost data. And if you want to go out and get that data yourself, it's very time intensive and not a very cost-effective endeavor to do that on a regular basis. And you're probably going to be left with some blind spots. Certain countries are very difficult to get data for and might not be comparing apples-to-apples in terms of the right HTS codes and definitions across countries. Even if you want to go down that route, a lot of the clients we talk about -- talk to have resource constraints. And it's not necessarily the best use of your internal resources to be constantly searching for data, scrubbing it and analyzing it. And then not to mention the forecasting and unreliable forecasting that's out there. You may be doing some forecasting on your own, but doing that in a consistent, structured way that enables comparison across countries in time. That takes a lot of modeling, a lot of data, a lot of man hours to put that in place. And ultimately, what we've heard from clients is that they feel like they may be at a competitive disadvantage. So 1/3 of you have a tool, right? So 2/3 of you don't. 2/3 of you are either not doing this analysis or have to continually go out and get bids or talk to some external third party to do that analysis. So there may be some gap there where you feel like, oh, you don't necessarily have a view of what's going on in the marketplace in real time. So we wanted to build a solution to try to solve some of these problems. And what we came up with was our total landing cost tool. So let me just give you a very quick overview of what the tool is, and then we can get into some specifics and show examples and some use cases of how we put this to use for some clients. So let's just start with how we define total landing cost. There are different ways to do this. You can include a million things if you want. But we settled on a pretty simple and clear definition. One in which we can be very confident in the quality and consistency of our data across markets and down to very fine detail in terms of product level. So what we've said around our 3 components: the product costs, logistics cost and duties. And this enables us to have a very broad and deep coverage. We think we're covering about 80% of 4-digit HTS codes, and that's of all HTS codes. If we think about just products that are containerized, we have a higher percentage of coverage. We have over 100 sourcing markets in our database and global destinations. So we can pretty much cover -- we feel like we can cover pretty much any solution -- any question that you guys are interested in, in terms of origin and destination and HTS codes. And the level of detail goes anywhere between 2 and 10 digits on HTS codes. 2 digits, you get a lot more data, but you're mixing and matching apples and oranges, if you will, 10 digits, there -- you have less data available, of course, but you're making sure that you have a really strong comparison and making sure you're looking at the same products across country -- across countries, excuse me. In terms of problems that we feel we're solving compared to the prior page, we think we're checking all the boxes in terms of really improving visibility on cost and risk. We're doing this in a highly efficient way, and I'll show you how quick -- how quickly this -- we can pull this data together. We're eliminating geographic and product blind spots with our breadth of coverage. We're able to gain competitive insights by doing benchmarking against the industry that you're in. I'll talk about how we're forecasting and considering future costs into this equation to giving some of that visibility as well. And then, of course, bringing up your team to do higher value-added stuff and then really thinking about strategy. So the benefits here are really about empowerment, helping you make better decisions, being more confident in those decisions, doing it as efficiently as possible and ultimately driving performance and understanding and optimizing the trade-offs between cost and your other performance indicators. So how does it work? It's actually quite simple. With just a few inputs, including HTS code, the origin country or countries, the destination to which you want to ship your goods, the mode, and we put period here, you can look at the last month of data, last 6 months, last 12 months to get a sense of how costs have trended over time. But really, all you need is an HTS code, and we can figure out the rest for you. And what you get as a result is very detailed and broken-down costs on a per product basis. In addition, we are very -- we try to be as transparent as possible about the quality of our data. So it's something called a level of confidence index, the LOC index, which gives you a sense of like is this data good enough and how much can we rely upon it. And then as you can see, in terms of the total landing cost, we break it down in terms of the item costs, freight costs and duties. And everything is simplified into a per-item basis. So that way, you can compare across markets, across modes, you name it. It is detailed but as simple as possible for the user. Now a couple of technical details. It's key features of the data. We think we have a pretty unique combination of both proprietary and market data sources. That enables us to really drill down to a specific product and get that per product price. Now this means we have some shipment level data in here, of which we maintain the utmost confidentiality. So the product level data is aggregated, averaged and otherwise transformed. So shipment data is not available to the public. It's all sort of wrapped up into our total landing cost calculation. We do a lot of data cleansing to maintain the highest quality. So this includes tail trimming and other kind of anomaly detections to ensure that the data is highly accurate and that we're comparing sort of doing, again, apples-to-apples comparison across countries. And then we add in forecasting 1 to 5 years really depends on the product, the market and the client use case. Now there are a couple of caveats with the state as well. HTS codes, no matter how high quality they are, they do have limitations. So we don't just automatically take the data at its word. Like I said, we do a lot of data cleansing, but you still have to sort of interrogate the data and make sure that what you're looking at is accurate and what the client ultimately wants. In terms of forecasting, every forecast has some margin of error, no matter how good it is. So we try to demonstrate our confidence intervals in our forecasts, give a level of confidence and that depends on the quality of the endpoint data, of course. And I want to be super clear that we do not forecast freight rates. So think of the 3 components of our total landing cost calculation, we forecast product prices based on both macro and microeconomic trends. So thinking about overall inflation rates, but then thinking about sort of industry and more macroeconomic cost drivers for different industries and products. And then on the duty side, our geopolitical team has a forward-looking view of policy and regulations that would impact tariffs and other duties. But the freight rate component, we look more historically, look at volatility and then also run scenario analyses to understand how different events could affect rates going forward. We've done some really extensive econometric modeling to understand how, for example, geopolitical and economic shocks affect freight rates, and we can build that into our tool as well. And then our total landing cost is port to port. We're not including right now ground transportation or warehousing costs. But this is the kind of stuff that can be added in. So one of the nice features of our model is that we have very robust data, but we can also incorporate any client data or add on to what our sort of model is. So if our client thinks that they have particularly unique data that they want to incorporate, great. If we want to add in some warehousing cost data as well if that's part of your network design that can be accommodated as well. All right. So what can you do with this? At least 4 or 5 things that we've already worked with clients on. One is the first is a country comparison. So evaluating cost basis across multiple countries or regions. We've done industry benchmarking studies, so we compared our clients' cost structures to industry averages and other metrics. Forecasting, as I mentioned already. So how do you plan for changes in future cost and build that into your network design. Scenario analyses. So Nick mentioned, for example, our next webinar is around trade policy coming out of the U.S. election. Those are the kind of things that we can quantify and then tie into an outlook for alternative scenarios for duties, tariffs and how that affects total landed cost. And then we've also done quite a bit of analysis on cost volatility to understand how costs have changed over time, including seasonal patterns, sensitivity to shocks, et cetera. And then on the right, there's some basic visualization examples of what the output of those things might look like, but we'll go into more detail into the case studies. Before we get to the case studies, I think we have another poll question for the audience.

Yes. Great. Thanks, Adam. Let me pull this up now. Just give me a second that should be coming up on your screen now. So the idea with this question is kind of your motivation to do a landed cost calculation. If you look at this, like, a, we'd be kind of your origin sourcing market, b, or more of your port-to-port transportation move and then c, your destination market kind of perspective or d, all of the above. So maybe you have really a kind of a global or a wide view of things. And so we're just curious what drives you? We've heard kind of where you go. And now it's like, okay, what's the motivation? What's the reason for doing this. So we'll give you here a second to answer. Okay. I give you about 5, 10 seconds more, get your votes in. Okay. Let's call it there and sharing results, Adam, can you see those?

Yes. Yes.

Okay. So we can see all of the above is pretty much the winner there.

Yes. And that's sort of -- that's the -- that's what we expected, right? I mean all -- sort of all of those answers are fairly important. Some may be more than others to particular companies and teams. But yes, whether you're assessing different sourcing options, looking for the optimal routing and want to consider cost in that. I mean, those are all obviously, there's a very, very important things in your sourcing decisions and questions we get all the time around how do you optimize these things? And all of the above fits with what we've heard, which is you need to consider multiple variables in your sourcing equation. So let's -- maybe let's go into some use cases here then and show you how we put this into action, which ties to that question of like, how do you balance these trade-offs and how do you solve for some of these challenges. So let's start with the country comparisons and benchmarking case study that we did for a client in the consumer retail sector. And they were looking for sourcing alternatives. They're based in Europe, and we're sourcing a lot from Southeast Asia. They were concerned that they weren't getting the best cost in the market, and they were also worried about ESG. And being in Europe, in particular, rising pressures around ESG reporting and wanted to make sure that they are very clear about their ESG performance and how to balance that with cost consideration. So we looked at specific products that they were selling. They gave us a list of about 10 products that they were most concerned about, and we analyze their sourcing options across a handful of markets and then whittled that down. Well, we started with about 10 or 15 markets, and whittled it down to about 5. And then for those high-priority locations, we looked at current and forecasted total landing cost. We compared those current and forecast costs against other criteria, including where we saw ESG rankings going in those different markets, focused mostly on carbon emissions. And then -- and we ranked their locations based on sort of this multi-factor approach. The deliverables were a packaged report that included all of the data and forecast and analysis and ranking for them, which really help them in their decision-making to have a clear view of where their costs and other metrics were going. Now this is a -- these are just some snapshots of what that deliverable look like, and I'll walk you through these, so you don't have to read all the fine prints here. But in the top left, this is one product we were looking at books, they're a retailer of book. So we were looking at a couple of different markets and comparing the total landing costs. And you can see how we break it down between the product cost, freight, and duties in the top left. And then on the top right, we looked at some historical trends. What was -- costs are actually coming down from 2022 to 2023, largely because freight costs were coming down off the 2022 peaks, but we were able to analyze those trends. And then in the bottom left, look at -- we had a forecast out 4 or 5 years. And then also layer on top scenarios. So for example, there's been discussion of under a second Trump administration 60% tariffs on Chinese imports, 10% tariffs on the rest of the world. So we were able to play around with different scenarios to see how that would change cost structures. And then on the bottom right, we were then able to weigh costs against other metrics, including carbon emissions to understand what the trade-offs would be when sourcing from different regions. And the punchline there was when you looked at Singapore, South Korea and Hong Kong, the sort of the cost carbon trade-off was the best value in those markets. Now that was our first case study. Moving on to our second one, where a company in the auto sector was thinking about decisions around derisking and near-shoring. And of course, costs has to come into play and then thinking about those kind of decisions. So the client was really in the middle of a pretty large network redesign and thinking about strategically where to position themselves around the world. This fell into the category of sort of a China plus one or China plus many type of strategy. And the things that they were really concerned about were, of course, maintaining cost discipline, maintaining or improving the efficiency of their supply chain and then improving the resilience of their supply chain to external shocks. So the way we approach this study was to look at sourcing and production shifts around the world and identify potential production hub locations that would be attractive to them, compare those locations on total lending cost, logistics performance and resilience to geopolitical risk and then rank and recommend based on those of options. And then deliverables, similarly to the last one, we're a package report with all of the data and analysis that went into our study. And so this study was bigger than just total landing costs. It considered a lot of different factors. And on the top left, you can see a dashboard of how we compared 5 different countries across a bunch of different metrics, including macroeconomic environment, cost structure, ease of doing business, corruption, logistics, geopolitical risk, ESG risk. And then behind all of those rankings with a lot of data and analysis. That's just kind of a snapshot dashboard. And the top right gives you a sense of how we're like looking at logistics performance, infrastructure quality, port performance, overall logistics performance and efficiency and the trends over time. And then highlighted in the bottom is really where we brought in the total landing cost data where we looked at particular products that the client cared about, again, breaking down product logistics and tariffs. And then on the bottom right, a bit of a complicated chart here, but to explain briefly just some -- like a 2x2 trade matrix showing the trade-off between logistics performance and total landing cost and some different scenarios for logistics performance depending on sort of best case and worst-case scenarios in terms of external shocks, congestion, et cetera. But that snapshot of that chart in the bottom right gives you a sense of like how we're able to visualize the trade-offs that we can quantify and use in our country rankings to help clarify decisions about best sourcing options. So we're kind of halfway through. We've gone through 2 case studies. We have 2 more. I think we have one more polling question, oops, I think I hit the wrong button there, Nick, sorry about that.

Yes, no worries. I do want to ask this poll, but I got a great question from someone in the audience. So I'm going to ask that before we launch the poll actually. So it's a question about the trade compliance aspect. And so how does Onyx provide consulting for the trade compliance aspect this tool may identify a cost-effective solution. But what if that solution adds or creates trade complexities not represented in the total landed cost. And I know we offer some things around trade policy and monitoring and such there. Could you help address that question?

Yes. So with any question around like complexity of where trade policy is going, regulations, compliance, like. Yes. I mean it's a rapidly changing environment, right? And so what we try to -- the way we try to capture that is our total landing cost calculator looks at current like status quo, current state of duties and tariffs. But we have a team that is sort of behind the scenes, if you will, looking at forecasting where the markets are going and where trade policy is going. And so that really comes into play in terms of our forecasting and scenario analysis to and we have a base case forecast for tariffs and duties for different markets and major product areas. And then we're able to run scenario analysis on top of that to kind of test the sensitivity of cost structures to different alternate news of the world. So for example, I'll bring up the U.S. presidential election is kind of front and center right now and because you could have very divergent outcomes in terms of how that impacts tariffs. So that's the kind of thing where we would build scenario analysis and test whether alternate realities kind of change the cost structure and change your decision making.

Yes. Actually, I know I think yesterday, we ran a piece on our LinkedIn that was a repost from something we ran earlier this year on the scenarios with the higher tariffs coming out of the U.S., at least that have been proposed. So okay. Great. I'm going to launch this third poll now. Sorry, I am sharing a wrong thing there. Okay. Should be up now on your screen. A little fumble there. But yes, answer this third poll and it is the last one. It's the last chance to give your feedback. And we talked about where you go and what motivates you it drives you to do landed cost. And now it's sort of like, well, what's missing, like what's incomplete and this will be great to understand kind of nothing is perfect, but what are the limitations that stands out for you? Just a reminder too, if you have any more questions in the audience, feel free to send those in. We have about maybe a little 10 minutes or less of content left. So we'll gave some time at the end for questions. Okay, 5 more seconds, and then we'll wrap this poll. All right, showing results. So it looks like the -- having the data, but it's too time consuming to do regularly is the top one there or missing data. So things around data, really, the ones that stand out.

Yes. Missing data, time consuming, I don't know where to begin. Yes, that we -- we knew the feeling, and that's -- these are the reasons why we wanted to build this thing. That all makes a lot of sense. Given the time, let me -- I'm going to run through the next 2 case studies here. And let's just go through these quickly and I then I'll see if any final questions, Nick. So the third case study is on procurement, sourcing, and production. And this was a consumer goods company. They were really looking like kind of at near-shoring rate in Europe and North America. And I wanted to know whether or not they would have sufficient suppliers in those regions to justify near-shoring or would they just be sort of near shoring Tier 1, but then the rest of like Tier 2, Tier 3 would be kind of still reliance on other markets. Included in this is that they wanted to make sure that if they were to near shore to North America or Europe that it wouldn't blow out their cost structure. So they really wanted to understand in detail the total landing costs for different markets and make sure that they were being maintaining cost discipline in these strategic decisions. In terms of the output, again, this was a really robust large study that included a lot of different variables, including looking at investment trends, so we were looking at foreign direct investment at a company and industry level into Mexico and Central and Eastern Europe. Really tracing out how the upstream supply chain was evolving for this particular client. And that was sort of like if you look at the top row, those 3 slides, that's kind of what those hit at. We also, in the bottom left, we look at the policy environment. So we were looking at investment policies and ease of doing business to understand whether these markets are supportive of near-shoring, or it was going to be difficult to do business there. Then in the middle there highlighting the total landing cost. We looked at current cost structures in different markets and also forecast those out in the future to better understand how cost competitiveness was going to change or not over time. And then ultimately, make recommendations around, in this case, it was around Mexico, maintaining its position as a low-cost market. But you can kind of get a sense here that total landing cost is a -- the fact -- one factor in a pretty complicated multivariate kind of equation around whether near sourcing made sense. And then the last one, last case study is around logistics risk monitoring. And this is for a tech client that we're -- so the prior 3 use case studies were kind of one-off studies. This is for a retainer relationship that we have with the client, where we are constantly monitoring geopolitical risks, logistics performance and cost structures, et cetera. So we're on a kind of a monthly cadence. Sometimes we do quarterly cadence where we give these kind of updates and analyses to executive level and do executive level briefings to help them make better decisions about their strategy and planning. And this particular situation. We were doing a scenario analysis for the client and looking at different geopolitical scenarios, monitoring those -- monitoring the risks from in this case, globally looking at all elections, but then a deep dive on the U.S. election and how trade policy could unfold. We did this study now, I don't know, 4 or 5 months ago, and now we're updating that for October. But we looked at different trade policies, how they might diverge across different administrations. Also, we looked at industrial policy and how Harris -- well, at the time, we were thinking a Biden administration, or a Trump administration would handle industrial policy. We modeled that out in our global macroeconomic model that we use that is able to break down growth and its drivers and then cost and cost drivers across really any country in the world. So that's in the bottom left, those heat maps show how supply side factors and demand side factors are heating up or cooling down. In particular, we looked at producer price inflation in different sourcing markets. And then we're able to apply that to our forecast for total landing costs across markets going to feed that macro data into our more microeconomic and industry and product level forecast. In addition, kind of getting back to the prior question, we're able to layer in our forecast or scenario alternatives for tariffs and duties across different markets depending on the political scenario combine all that together to get a total landing cost forecast for products and markets over the next, say, 4 or 5 years. And that's that bottom middle chart. So you can see just to summarize that again, it's the forecast is including scenarios around not only the economic and very quantifiable impacts, but also our view on policy. And so that's all incorporated into the outlook. And then the bottom right, there's also a demand component to this. So we were able to tell the clients. In this case, they were selling components into the auto sector, and we wanted to give them a sense of what the final demand for autos in this case might end up being. Maybe we have -- that's the -- that was the last use case, Nick, I think maybe we have a minute or 2, if there are any questions in the queue.

Sure. Yes, definitely. And I just put up the -- or dropped in the chat, the link for the October 17 webinar session kind of presuming most of you would attend that one, but feel free to use the QR code if that's easier for you. We had some questions from, I would say, like a few people who registered about like what's included and what's not. And there was questions around seasonality, like depending on what time of year you're shipping, a risk of adverse events. The unforeseen things, duties changing. Can you talk to this? Like how does our data capture this? Or how do we handle those various types of things?

Yes. We're able to capture all of that. The way we handled it really depends on the type of product that we're analyzing, right? Like if it is a product that has some type of seasonality to it, then we look at a higher frequency of data, maybe monthly or quarterly to understand those seasonal patterns. We can go back. We have 4, 5, 6 years of history in many cases, so we can look at those patterns over time and build that into a forecast. So we can do annual forecast, so we can break that down into seasonal patterns. In terms of adverse risky events, that comes into play more in terms of their scenario analysis and testing sensitivity and resilience of cost to sort of exogenous shocks. And then on the -- I think I touched on the poll, how we incorporate changing policies and into our forecast.

Great. There's a question about destination clearance and handling, I think Matt is actually answering that in the Q&A. So that will be answered in writing. There's a question about from someone who sources very technical components with high quality requirements. How does our tool consider that? It sounds like maybe more of just like higher standards, maybe limits the available supply and choices. Might more in a discussion understandably, but kind of just quick take on that question, Adam.

That's a really good question. And these are the kind of things where maybe it would be lovely to have like a self-serving -- self-service tool where you just like we're able to dial these things up or down. But I think those are the kind of situations where a little bit more bespoke analysis might be warranted. So it really depends on the use case is what I would say to the listeners out there. I think if you are in a market or an industry where you have a very, very specific kind of niche product, the chances are that the data, there's not a lot of sources in different countries and the data might not be that robust. So that's where we would want to kind of work hand in hand and compare our data with yours and kind of maybe have a little bit of a more bespoke approach to it.

Great. Okay, thanks for answering that. It's our last question is one that Matt is also answering in writing. Alan, you should see that here shortly. So I think we'll wrap it there. We did say 45 minutes. So I hope you all enjoy a little bit different type of webinar that we offer than we've offered, I should say. Just want to give you a little bit more insight into kind of behind the scenes and how we do some of our work. Next month, it will be a bit more of a return to sort of the topics that we cover out there. So look forward to see you there, hopefully. And thank you for attending again. Just a last reminder, you should get a survey from me, and it will -- a few questions, answer that, and you'll be able to get a copy of many of the slides today. So thank you all for attending, and thank you, Adam, and thank you, Matthew. Everyone, have a great day.

Thanks, everyone.