Cognex Corporation (CGNX) Earnings Call Transcript & Summary

Good morning, everyone. I'm Tommy Moll, I'm analyst here at Stephens. We appreciate your joining us in Nashville this week for the annual investor conference. To my left, I'm joined by the CFO of Cognex, Dennis Fehr. Dennis, thank you for your time and insight today.

Yes. Thanks, Tommy, for having us. Thank you, everyone, for being here and your interest in Cognex.

So this conference is intended for both specialists and generalist investors. And with that in mind, I'll start with some introductory questions for the generalist in the audience who maybe aren't yet familiar with Cognex and then we'll move to some of the more specific questions. If at any point you want to ask a question directly by all means show up a hand and ask 1 or more than 1 question that might be on your mind. But just to kick us off, Dennis, Cognex is a machine vision competitor. Tell us what that is for those who may not have dug into your market before?

Yes. No, absolutely. So think us about like a software company, software on device. And that means we are working in factory automation and warehouse automation. And maybe to give you a few examples what we do, I would reference a customer visit I did earlier this year. So I was in France and visited a famous kind of cosmetic manufacturing or brand and they are manufacturing only in France. And so we went into that factory and walked the line and saw a couple of applications. So basically, what is this company doing? Obviously, they create they would call it magic probably in kind of a cream form. And at the end, it goes into glass bottles and then these glass bottles at the end get packaged into kind of some carton packaging and being sold on shelves, right? So think about that. In that regard applications could be, for example, that they need to feed in these glass bottles into the production line, and they have some robotic arms, basically, they have pallets of these little glass bottles coming up and the robotic arms coming and picking these glass bottles up and placing them on the production lines. We have the guidance of that robotic arm that would have a machine vision system to really identify where are the bottles and where to place them. So it's one of our application's guiding. And then from there, it goes further, that these glass bottles going further down the production line, eventually, they may fill the cream to it, and then you will want to know like, oh, maybe along this way, was there any damage to the glass bottle right? One of the big issues would be a little glass splinters maybe even drop into the cream or some outside defects. So that means we do such kind of inspections. That means we have the cameras placed there and the cameras would look at these glass bottles and would see other damages in the glass. So there's an inspection application as well. And then as it is also a kind of highly quality environment, they would like to have some serialization of their products. So they have little numbers printed on these glass bottles, very hard to see. And it would basically in each step of the production would read out the serial number so that they basically can tie back the step of the production to that particular glass bottle. So it means there's some kind of identification application with our cameras as well. And then maybe the last application, as an example, would be a measurement application, a gauging. In this case, for example, before they pack the glass bottle, the filled glass bottle into the kind of that carton wrapping, they want to make sure that the carton is really cut out in the way they want it. So because if they feed in the carton into the machine and it's not cut in the way, then they get a jam that means they want to inspect and measure basically is the dimensioning of this carton in the right way? So there is some kind of this gauging application as well. So think about it along this production process, there are different areas and applications, which we can solve, and that's kind of what we bring to this type of customers. And we are active in different verticals, maybe to wrap that up, right? So this was an example. We call this market really packaging because it's all about packaging, so it's food and beverage, health care, cosmetics, we are active in the logistics vertical. Think about warehouse automation, a lot is about code reading there and then automotive is a big market of us, consumer electronics kind of device manufacturing and then semiconductor, semiconductor manufacturing. So these are kind of our top 5 verticals, so a diverse set of markets we sell into.

Let's think about how artificial intelligence factors in here, Dennis, first on the opportunity side. This is something that Cognex has talked about for a while now. Give us a sense of how AI can improve the ease of use and expand the use cases?

Right. So we think AI is one of a great opportunity for Cognex, right? So we are a 40-year-old company, and we have been basically the technology leader in that time. And that was basically when we talk about what we would from today's perspective called rule-based software architecture. That means you have very smart people sitting there writing codes, saying what if this, then that, right? Back to that example, maybe with the glass bottle inspection, we would try to write a code to say, if you see this, then it's good or bad. And you can do a lot of things with that. But it can become very complicated to write such a specialized code. And then the question is, is it repeatable? And that's here we're really AI model. So basically, we created our proprietary vision model. Basically, which then is loaded on devices and then the customer only needs to train a few of their own examples. In this case, like, for example, some of these glass bottle inspection, you would need to show a couple of pictures, good, no good and the model would learn that. And with that, you basically achieve higher accuracy, that means you can solve for more use cases for the customers, maybe which you couldn't do in the past. Like in the past, without AI, it would have been very hard to inspect like the top edge of the bottle for glass damage inspection because they are so small, in rules-based, you could just not do it and with AI-based you can. So that means all of a sudden, you have an additional use case. It means the customer instead of having a person looking at it, out of a sudden basically can put one of our cameras there, and that means we are creating basically market with that, and that's the great opportunity which we see is bringing AI-based technology into the machine vision market.

Now on the potential threats from AI in particular open source substitutes, how do you protect against what I would call a good enough solution that may cost a lot less than Cognex?

Right. I mean, I think I would feel like that's probably one of the biggest misunderstood part in some of the Cognex story over the last 12 months or so. A lot of people thought like, oh, are you being disrupted by AI, all these hyperscalers creating these large models and will these large models all be able to do what you can do very easily. And I think we showed at our Investor Day in June this year that the different -- there are really 4 distinct topics which you need to have to be successful in this market. So first, you need to have high precision, right? So that means you can't miss a damage on that bottle and then glass has fallen and you miss that. So that means precision, very high accuracy, you need to have. And for that, you really need to drain it on -- create this proprietary vision model, which we have. It really is very highly specialized to the applications, which we do in our markets and kind of generic language models can't solve this. They might be trained on a variety from pictures of horses to mountain landscapes, but our models are really trained on very concrete and detailed factory automation examples. So precision matters and we are -- we can prove we are better there. Then second, speed matters a lot, right? So in this example, where I visit this French customer, the bottles move so fast, you can't see them with your eye, right? It looks like maybe they move very slowly, but they move so fast, your eye can't see the individual glass bottles anymore. In that regard, you can't use a very large language model because the processing time would be much too high. So you need to have a very specialized model like ours, and then you need to bring it on device. You can't do it with the cloud because your connection time, your latency is too long. And therefore, you need to have that capability to match the hardware with the software, so to say. And then you want to have scalability. That means, right, you have a manufacturing line, but today, you produce product A, but tomorrow, you may want to shift to product B, right? And then the bottle might look different, the colors are different, the shapes are different and you don't want to recreate everything. So you want to have scalable models. And that's where our models help a lot. And then the last piece is ease of use. You don't want to have very complex. You want to have as much as you can plug-and-play solutions. And that's, I think, where we -- especially here, we invested a lot and where also AI helps kind of self-tuning, self-setup where we created this type of features. And I think that's how we differentiate, and that's why we're not worried about this type of larger generic type of models or good enough type of approaches.

Thank you, Dennis. I want to move on to discuss some of the elements from your recent Investor Day, just starting at the top and working our way down the P&L. In terms of the multiyear sales outlook, you framed it in the low double-digit range in terms of the compound rate. One of the key levers to enable that was doubling the customer count over roughly 5 years. What are the elements of the strategy that you're pulling together to achieve that?

Right, so here, I would say the growth algorithms, which we introduced in -- at the Investor Day, really looked at the vertical markets, which were -- which I mentioned before, which we're serving. We then basically looked at and said, like, what's the underlying growth rates in those vertical markets. And they are clearly not in a -- in this low double-digit range. They're maybe in a low single-digit range. But then we see a strong opportunity by increasing market penetration. And market penetration can come from 2 areas, the AI side, which we just talked about, like that means creating more applications and with that, driving more penetration. And then the second piece is what Tommy just referred to it, that means it's like bringing machine vision to more customers. So we traditionally, as Cognex, we have been serving kind of like large-scale, sophisticated customers, and we saw that there's a long tail of the market as well. And -- that almost brings me to, I would say, the second point, which is probably has been most misunderstood about Cognex in the last 12 months or so, right? I talked about the AI and how we think that's an opportunity. And then the second piece is about our transition from emerging customers to sales force transformation, right? So that means maybe in 2023, we launched an initiative called emerging customers. And that means like we said, like, let's put boots on the ground and go to more customers. So it was all like expanding sales force to serve more customers and give them easy-to-use products. It was a good strategy to say, like, let's tackle that long tail of the market with really the focus to create more customers. But since then, we have really evolved what started as an emerging customer initiative to what we now call sales force transformation. And we think that's not just a rebranding that's really kind of a next step in the evolution along that line. So if you think back emerging customers, boots on the ground versus if you think about sales force transformation, it's -- first of all, it's not stand-alone. It's really creating a combined structured sales force with very dedicated sales profile. That means we thought a lot about like what type of sales profiles do we need selling to what type of customers. We structured that in 3 groups. Basically newer, let's say, smaller customers than kind of the larger existing customers and then machine builders, which are very kind of spec in type of sales approach. And then on top of here, and here's really a very distinct view is that we are focusing a lot about sales efficiencies and data-driven sales analytics. That means bringing CRM tools and then also the way how we manage our sales organization in terms of KPIs, leader boards, and how they perform on a day-to-day basis, on a weekly basis, on a monthly basis. And that means that we moved basically from more boots on the ground towards a focused and sales efficiency driven kind of sales force transformation. And that means the sales force transformation, we not only want to reach more customers, but we also want to increase the efficiency of our sales force and basically to optimize the dollar spend per dollar booked, and that's really what is key difference between where emerging customer initiatives started, and that's why we think it's really part of an evolution. And I think a lot of people maybe thought it's just a rebranding when it's not.

Moving down the P&L here. I'll hit a couple of the elements in your expense lines, and then you can answer it in whichever order makes the most sense. But on the gross margin line, you moved away from an explicit target there. On the R&D line, you're emphasizing much more than previous the efficiency of that R&D spend. And more holistically at the OpEx line, you've talked about more dynamically managing those expenses through a cycle. So I've thrown 3 different themes at you to hit on them in whatever order you choose.

Right. So maybe start on that gross margin piece first. So first of all, I think, right, we are say, attractive gross margin company traditionally slightly above 70% right now, maybe in the high 60s gross margin range. So it's an important level for us, right? But I think in the past, Cognex, I would say, almost over-indexed on gross margin, and I would say almost from also internal decision-making to say like are we focusing on gross margin? Or are we looking at shareholder value creation, which we think is much more in terms of adjusted EPS growth. In that regard, I think there's a bit of a shift in terms of financial management of the company happening which, however, does not mean like we're not caring about gross margin, right? We just think like it's one lever, but it's also very clearly that high gross margin we have, COGS, our COGS are smaller in absolute dollars than our OpEx. That means there's much more we can work on in OpEx than on COGS. And that's why I think OpEx has become a much higher focus on where we talk much more about it in the last -- especially since Investor Day, where we clearly also outlined that our path to higher profitability is through OpEx efficiency, right? So in that regard has been clearly a focus area here. And I think over the last 3 quarters, we made great progress here with revenue up in each of these quarters and adjusted OpEx in absolute terms down. So really driving nice efficiencies and flow through to the bottom line. And yes, it has different components when we think about the OpEx efficiency. So there's clearly the R&D piece to it, where we have 2 things. So first of all, thinking about how we do capital allocations in R&D, that means bringing more financial metrics when we make decisions about into which R&D projects we allocate funds and where not. So I think that's a shift something which you can't see from the outside, but it's happening on the inside. And then there's clearly efficiencies, which we drive, right? So we -- first of all, over the last couple of years, we migrated from a product line software stack to more a platform architecture. That means we are creating synergy effects across product lines and software coding and then adopting AI-assisted coding. It's a big productivity driver in our engineering function as well. And that allows us basically that we think we can achieve the similar level of innovation with going forward or as a midterm target kind of rather a low teens in percent of revenue R&D spend versus the mid-teens in the past. And then, yes, we already talked a bit about the sales force efficiency, where we really transitioned from that more boots on the ground towards like let's drive really sales force efficiency, optimize that dollar spend per booking. And that means we think we can also drive an optimized SG&A in percent of revenue over time. And that's kind of -- is very much part of driving profit bottom line growth, both on adjusted EBITDA margin percent as well as in terms of adjusted EPS.

Dennis, to compare what you've described in terms of margin others in the market is sometimes difficult because there aren't a whole lot of great direct comparisons. But Keyence is one that often comes up, in particular, in terms of the gross and operating margins there. Why would you say that your aspirations are perhaps more modest by comparison?

Right. So I think, there are 2 things, right? So first of all, where are we against our own historic comparison, right? So historic average has been 28% adjusted EBITDA margin. And last year in 2024, we have been only at 17%. So we first have work to do to get back to where we have been historically. I think with our implied guide for Q4, we're kind of starting to see maybe a 2 in front of that number. And then certainly, our next milestone would be to get to like a 25% number where we said like that's the number which we want to see as kind of the minimum even also in a down cycle, right? So that means avoid that we are getting compressed on adjusted EBITDA margin. And then certainly, the question then comes like why would you -- where could you go from there? And then people point at Keyence and say like, hey, how can they achieve even higher gross and operating margins? I would say on the gross margin side, it's a simple statement. They work in different markets than we do. I mean, right, I would say our factory automation gross margins are very comparable to what they have, and they are factory automation only. They're not in warehouse automation. So it means there's just a mix effect. And then I think where they are very well set up is in their SG&A efficiency, right? I think they, a, first have a very good playbook, which is kind of what we are driving also a bit into our sales force with the sales force transformation. But then b, they certainly have also a clear in this advantage. We are a pure-play machine vision company, and they are more diversified factory automation player. And that means with that, they can achieve higher sales force efficiency than we think we can do as a stand-alone machine vision company. And that's kind of a bit where our M&A thinking comes into play, right? As part of Investor Day, we said like a part of our growth algorithm is also inorganic growth and clearly adding additional products maybe in adjacencies to machine vision could be part of that, and that would really then drive further sales force efficiency and certainly would, in the long term, enable us to go beyond the adjusted EBITDA margin target range, which we have announced so far.

Last question for you. Dennis, on the Investor Day themes. If we pull all of this together, should we -- is it fair to say that if you achieve what you set out the P&L will be less cyclical and more boring in the past? And I do want to get you on record here, can we still expect profligate spend on Halloween and annual reports?

We're having a lot of fun on Halloween and with annual report. So we definitely don't want to give up on that fund.

Sacred cows.

As CFO, you want to say like there are no sacred cows, but I would say there are just things they are fun. And so well, we'll not give up on those. And then on the cyclicality side, I mean, clearly, was going for a broader base of the market, that's clearly part of the strategy. But are we there today? No, we're not, right? So it's really a multiyear journey. And so in that regard, I would say we are definitely still a more cyclical and volatile company, both in the up and the down as many other companies, but I would expect that to change over time.

Last question for you on the P&L, and then we'll pivot to Q&A. Early 2026 commentary you offered on your most recent earnings call, you basically said if we look at today's PMIs, the rough math would suggest mid-single-digit sales growth next year, but that with continued discipline on the OpEx line, you could feasibly achieve, call it, 20% EPS growth. How do these comments tie back to some of the themes you laid out at Investor Day in terms of managing through a cycle?

Right. I mean, yes, I think, as we -- as I just concluded the prior remarks, we are a cyclical company. So that means we have basically looked at typically like your 5- to 7-year cycles, typically in 3 phases, maybe 2 years or so kind of initial phase with moderate growth and then 2 years or so with high growth, outsized growth and then kind of 2 years, the tail end of the cycle down to flat. And basically, if you think back the last -- the peak of the last cycle was in 2021, you had then kind of flat and down in '22 and '23 and probably '24 felt like the end, the tail end of the prior cycle. And at the moment, you could think that 2025 is the initial stage of that cycle where you see that type of moderate growth. And then that's where we really said like in this phase, especially compared to where we are in profitability, that's where we really want to drive outsized bottom line growth and some of the OpEx efficiency measures, which we talked about play a key role into that. And -- but at the same time, I would really like to remind everyone, we are a short-cycle business. That means, a, we have a limited visibility from a funnel perspective, right? In factory automation, it might be only 3 months. And then we use this PMI basically to give us a bit of a view like maybe how could the next 6 months look like, maybe PMI can move fast. So I would say like -- I would, in that regard, say like our remarks were probably like to say like, hey, based on funnel, based on PMI where it is, maybe the next couple of months or a couple of quarters, we would expect a moderate growth, and that's a time where we can still drive very attractive adjusted EPS growth. And then what's coming beyond that, that's very hard to say. That's really we'll need to watch PMIs further. And certainly, I would say maybe give it a positive spin in that regard, the moment where we see higher growth, the flow-through to the bottom line could be even larger, right? I mean we are typically seeing 50% to 60% flow through to the bottom line of each dollar, which we grow on the top line. So in that regard, think about if you can grow mid-single digits top line and 20% or so adjusted EPS, that could become even more attractive if growth rates go further up.

Thank you, Dennis. I want to pause here to take any questions members of the audience may have. Just raise your hand and fire away.

If you think about the competitive environment in machine vision, are we seeing new competitors emerge beyond the existing competitive side, there are couple of Chinese players that continue to get more and shares [indiscernible].

Right. See, I think if you zoom out a little bit and look first over a bit longer period, you would say that competitive landscape is almost unchanged in that sense that like the biggest competitor in factory automation always has been Keyence and the largest competitor in logistics warehouse automation was always SICK, a privately held German company spelled SICK. And that has almost not changed for, whatever, 2 decades or so on. And you saw maybe name changes below that, then maybe some competitors entered, some others exited and so on. So you saw things like that happening. And I would say a similar theme, I would almost, at the moment, think like is happening with Chinese competitors. There are clearly some Chinese competitors in factory automation rising like a Hikvision, for example. But at the same time, other competitors like Omron, for example, have been rather struggling in that space. So that means that for us, it feels more like names are changing, but not necessarily the entire landscape as -- it's also clearly it's still a very fragmented market, right, with maybe the 2 largest players with Keyence and Cognex together by far not even holding 50% of the market. So it means smaller players falling out, other joining. And so in our mind, the competitive landscape is not really changing that much, even so you see movement.

Any follow-ups or anyone else want to jump in? Sure. We'll pivot to an end market discussion, but for those in the audience at any point, just raise a hand and we'll work in here. But Dennis, starting on automotive, during earnings, you mentioned that you're nearing a bottom there. Let's break up the discussion into 2 pieces. First, on the U.S., when would the recent announced -- big investment announcements from the OEMs theoretically be actionable for Cognex? And then we'll move to Europe second.

Yes. So automotive has for us really been the most painful market over the last almost 2 years, right? So in that regard, was the market contracted the most. And yes, on the last earnings call, we said like, hey, we think like that we are nearing the bottom, and I hope that in one of the next calls, I can call the bottom. The interesting thing here is that we see -- start to see kind of a geographic diversification in that market. So that means like North America or the Americas specifically is actually right now the best performing regional market within auto and then Europe is the worst performing and somewhere Asia, somewhere in the middle within Asia, also some differences there. So in that regard, I think we start to see that the Americas market is coming back faster. And at the moment, I would not know yet if we could call the bottom, for example, in Europe, right? The bottom we could call on the market as a total. But especially in Europe, if you see some of the announcement, if you see how profits have compressed in the last earnings call of some of the major European car manufacturers, especially some of the German manufacturers, that still looks like a market still pretty much under stress in that regard. I'm a bit more cautious about a Europe statement, but yes, Americas looks more and more positive.

When is the pain going to end in Europe? For those of us not as close to the market as you, what's going on there that's driving all of this?

I mean, I think -- see, maybe taking a step back, right? So automotive, so first of all, had the view of a large technology transition and a lot of companies invested. Now we are seeing that also that transition is not happening as fast and also you have different speeds in different geographies, right? Like China leading the pack and the U.S. probably rather going away from this transition. And then that caused a lot of pain and capital requirements for companies and make it hard for them to make investment decisions. And then I would say, especially for the European manufacturers, the tariff situation in the U.S. hit some of them pretty hard. So in that regard, I think there's pretty much uncertainty. And I would think like at least some of the tariff deals with the EU have now been negotiated. I would think that some of that certainty should come back, but we haven't seen it yet, and I wouldn't be able to give you a time line on it, Tommy.

Moving on to consumer electronics. Trends improved year-to-date in 2025, I think you've mentioned it was the first growth year in 3 years. At the same time, investors have taken note of some recent form factor innovations. Expectations might have gotten a little bit elevated in terms of what that might mean for revenue opportunity to Cognex. So just situate us between those 2 data points, please.

Right. So I mean -- so first of all, change is good for Cognex, right? So that means change in terms of form factors, change in terms of production locations. These are things which typically drive revenue for Cognex. And if you think back about the last 2 peaks of the cycles in consumer electronics, one was in 2017, it was very much driven by a display technology changeover and then '21 was COVID really means different working patterns and different behaviors by end users. So in that regard, certainly, whenever you think about technology changes that can drive business for Cognex, also changes to supply chains moving from China to India or to Vietnam that drives. And we are seeing some of that why it's the first time in many years, we're now seeing growth returning into consumer electronics. And this year, it's a bit more driven by the change in the supply chains. a little bit less by form factors. As it's a very different thing if you change your entire product lineup a certain component to a newer technology versus you maybe add one more production line in terms of the magnitude, what that does to a production line refitting and build-out. But in general, I think we think positively about consumer electronics for the first time for a long time. We think about '26, there can be more form factor changes, further supply chain diversifications, component manufacturing moving into the U.S., final assembly probably still staying in Asia. And then eventually, people are starting to think about seriously about the time after the smartphones, right? So you see the meta glasses starting to being sold in millions, not in very small quantities. So it's not as a smartphone is selling today. But it's clearly that there are companies, OpenAI announced some partnerships there in that sense that people are starting to think like, hey, there could be coming the next wave. So in that regard, we think positive about consumer electronics. It's just from today's perspective for us, hard to call when and how strong that will happen.

Moving on to logistics. This is your second year of solid double-digit growth, albeit the base in 2023 was rather depressed because a lot of the key players there were digesting excess capacity. But walk us through the different customer types here within logistics and give us a sense of where they are in their adoption cycles and build cycles.

Yes. So if you think about the logistics market, you could probably divide that in further subvertical, so to say, right? We have like e-commerce customers, think about large online retailers, distribution centers and then certainly also have what we call more parcels. So think about more like FedEx, UPS, this type of the world. And then maybe you could even add like airport baggage handling. So in that regard, there are different segments, and we traditionally think our home turf is really e-commerce. On one side, there's for us an opportunity to go into more subverticals, over time. But really, the growth has been coming with the e-commerce side. And that's driven by a very low penetration of machine vision in today's kind of e-commerce, I would say, networks. And even sophisticated players in the space have a low penetration rate. We sometimes would say for sophisticated players, they're maybe at a 25% penetration and maybe the broader market is a 15% penetration. So in that regard, there's clearly a penetration opportunity and that -- some of this is related to what we announced in the last earnings call. We introduced a new product lineup called the SLX. And think about it like in the past, the logistics market was very much code reading, high speed, high precision, high accuracy. And that's still a great market, and there's still so much more to automize in this distribution network. So we can grow just with code reading. But then customers also see other problems happening than just code reading that means jams on conveyor belt, side by side -- 2 packages side by side and then only one code is being read, damaged packages, which you want to not only find out at the end, but maybe right when they enter your network so that you're not running through basically waste through your network. And that you can't solve with code reading, you need machine vision. And that's where we're basically teleporting, if you want to say it, existing technology, which we use in factory automation and bringing that dedicated to logistics, and that's the SLX lineup. And that basically what gives us that positive view that logistics can be a multiyear growth driver for us. However, growth is not linear. And after 2 very strong years of growth in logistics and now especially in the second half of this year, that growth was much more focused on large-scale customers. We're a little bit more cautious about 2026. And therefore, while other markets getting better, we would definitely consider that maybe growth rates would also naturally get a little bit lower. But in '26 -- but that does not mean that we are thinking differently about this market from a long term. It's just about growth is not linear.

Any questions from the audience before we wrap it up? I have just one more prepared, but jump in if you'd like to ask anything. All right. Well, I have one to wrap it up here, Dennis, and I want you to gaze deeply into the crystal ball here. Historically, Cognex has grown top line well above the market average. But if you look at the source of that growth, it's evolved over time. If you go back far enough, it was semiconductors, pre-pandemic it was consumer electronics. More recently, it's been logistics like we were just discussing. So if you gaze into the crystal ball and think about what are industries that could -- I'm talking 5, 10 years out, pop up as significant sources of growth, what comes to mind there?

Right. So first of all, I would think like in the existing verticals, there's already a great growth opportunity, right? I just talked about the low automation penetration level in logistics. I talked about consumer electronics with that new form factors time beyond smartphones. So there are great opportunities there. And then I think a market still nascent today is -- which we are otherwise not talking a lot about is aerospace and defense. So I think that's definitely a market where there are great machine vision applications. It's a small market today, but it's definitely an interesting market, and we'll see where that goes over the years.

Thank you very much, Dennis, for all the insight. We appreciate you being here this week.

Thanks a lot, Tommy. Thanks, everyone.