Cognex Corporation (CGNX) Earnings Call Transcript & Summary

Thank you for coming out. My name is Ethan Chuang. I'm an associate under Ken Newman, covering the industrial supply chain. With me today is Dennis Fehr, the CFO of Cognex. Dennis, thank you for coming out today. To kick things off, why don't you give a little bit of background about yourself and an overview of who Cognex is.

Yes, sure. Happy to, and good afternoon, everyone. Thanks for taking the time and your interest in Cognex. A few words about myself, Chief Financial Officer of Cognex, about a year in the role. This is my third CFO job. I have been at both private and public companies prior to that as a CFO. Who is Cognex? For those who don't know us. So we are the cognition experts. That's what the name stands for. I'd like to say we bring the real world into the machine world. So we take the photons in the real world, we convert them into images and then we put our software and vision tools on top of it and really look at what's in this picture. And that means in factory automation, for inspection, for example, or for guiding of robotic arms can be identification of products, very good old barcode reading, if you want to say, and engaging as well. So that's kind of what we do. And I would say as a company, we are regarded as typically as the tech leader in the space, both kind of in the pre-AI area in that pre-AI era. And now also, I would say, since 2022 when we launched our first AI product also in that now new AI area that we have really embraced AI as kind of the next level of machine vision and to drive basically additional use cases and penetration. Overall, we are, I would say, in an attractive market, which has the potential for attractive growth rates, driven by continuous cost out and quality optimization desire by our customers, reshoring and maybe regionalization of global manufacturing as well as labor shortages in some instances. And then at the same time, while we operate as a kind of software on device model, so that means we sell the software and hardware and go out with that, we command kind of software-like margins, at least traditionally, have been like a historic average of 28% adjusted EBITDA margin that has compressed a little bit over the last couple of years, and that's what we are right now addressing heads on as a -- maybe as a new leadership team, if you want to say so. So Matt Moschner, our CEO, came into the role just 6 weeks ago. And as I mentioned before, I'm about a year in a role. So we're driving back to where we think we belong in terms of bottom line profitability. And so in that regard looking optimistic into the future.

That's great. And so maybe just to kick things off on my end. You guys just reported earnings a few weeks ago and commentary around positive improving trends within factory automation and e-commerce logistics look pretty good. Investors clearly seem to like it with the stock up 20% on the day. But can you talk a little bit more about what you're seeing in your rates and what's driving visibility into the third quarter and second half of this year?

Sure. Absolutely. Maybe before I go into particular end market, maybe first, big picture, right? So on the one side, we are cyclical in nature as very often industrial automation CapEx-based businesses are. So we saw the peak of the last cycle in 2021. And then saw more pronounced, I would say, down cycle, '22 flat, '23 strongly down and then starting only to flatten out in 2024. And during this time, the company also did some investments into future growth, which on the one side we -- as a new leadership team from a strategic angle, rely, but at the same time, it really compressed bottom line a lot. So I would say I think what the market reacted a bit to at least what I hope the market did in the last earnings call was to say like this refocus on bottom line profitability and at the same time, showing also really first progress there. But maybe to the questions on the end markets, more specifically what we see there. So first, which markets are we serving? Our largest end market is logistics and call it warehouse automation. And it's about 24% of our business. And then the second is automotive. Third is, we call it packaging, that's fast-moving consumer goods and health care. It's just like the application is very similar on this one. That's why I put that into one. consumer electronics, the fourth and semiconductor is the fifth. And I think over the last 12 months or probably now 18 months, we've seen logistics growing very nicely and that we see strong momentum there as that's a market which is not very deeply penetrated or it's actually the lowest penetrated market with machine vision. And therefore, we see really a long-term growth potential there. It's also the market where we typically have the most visibility. So that means for us 9 months, right? So in all the other end markets, which we sometimes combine to, call it factory automation, we just have like 3 months visibility so much shorter. And then I would say maybe other highlights we saw in the quarter, we highlighted positively packaging that we've made good progress there, especially with the dedicated sales focus. And we've -- for the first time in many years, we highlighted consumer electronics as kind of an early sign of positivity. So we have seen consumer electronics 2021, a great year. But since then, it was almost like kind of a refresh cycle year after year. And it was the first time that we said like, hey, in this market, we are now seeing the opportunities from the reshoring, seeing the first moving of supply chains from China into other Asian countries. And then in general, a more positive sentiment in that industry. So that's maybe a few words upfront on the vertical markets.

Yes. That's great. And then you touched on it a little bit, but maybe on the margin side of things. It was pretty good to see you guys have EBITDA start trending towards that 20% you guys had outlined earlier. Can you help me understand what sort of initiatives are in place right now? And what -- how much of it is more structural as opposed to just flexing what the company's needs at the moment?

Yes. No. Thanks on that. Yes, on the one side, great progress, right? So for 4 quarters with year-over-year EPS increase first quarter since Q2 2023 above 20% adjusted EBITDA. So nice progress. And it's really -- if we think about it, we're looking at the entire P&L, right? So in our mind, mads in mind, we're thinking about like, let's drive what we can influence and what we can control. So what can we control? On the one side, we can control on the top line. We can control a bit like where do we focus our sales efforts like less automotive, which is not a good market right now and more unlike packaging, health care, fast-moving consumer goods. And that gives us at least a few percentage points of growth, even so if we would leave market out for the moment. And then we can control our cost base. At our recent Investor Day, we talked about that we believe our biggest opportunity in driving bottom line profitability is through OpEx efficiency. And that's what we have seen now in this quarterly results that we saw kind of year-over-year in a constant currency basis, OpEx coming down 3%. So in that regard, we think we're really driving structural cost optimization and it's, therefore, there to last. So it's not something driven by anything external. It's really something we control and we are focused on.

Yes. That's great. And then you said you just had your company's first Analyst Day, which is very exciting. You and Matt talked a little constructively about M&A as a pillar of the long-term growth strategy. I guess maybe can you touch a little bit more about what sort of targets you guys are looking at, maybe, say, higher-margin software as opposed to hardware like Moritex or what that might look like? And then just overall, what's the shift behind the strategy?

Yes. No. Thanks for that. Yes, so we talked about Investor Day about our kind of new growth algorithm. And in general, so first of all, we brought it down a bit to where it was before. And then we kind of sliced it in almost like you can say 3 components. So first, we said like what's the growth -- I think my mic dropped -- sorry for that, guys. So 3 components. So the first one is -- is it still on, is it good? Great. Okay. And then underlying market growth. So it means like how much is the market of our customers growing. And we said, like through cycle, it's 4%. And then we said like, and that's really the biggest block of growth. It's like 6% to 7% penetration. That means we see the opportunity to penetrate our customers from 2 directions more. One thing is more applications enabled by the adoption of AI and then the second one is about going to more customers, which we have traditionally not served. So that's kind of the 2 vectors there. And then the third one M&A. That's really the smallest in the 3 growth components with 3%. And so we brought that in as we believe Cognex has a very strong balance sheet, no debt, very strong cash generation. So could we add additional shareholder value creation through synergistic M&A plan -- planning or execution. And that's kind of what we wanted to convey with that. And what are we looking for? We look for highly synergistic businesses with the conviction that they can meet our financial framework criteria, especially being in that 20% to 30% adjusted EBITDA, either being within or with a clear path to within. And in the past, for Cognex, synergistic M&A really meant focusing on tech and said like, is that a tech which we like, which is maybe a niche, which we need. And that still exists for us today. But as we have built out a really strong direct sales force, there's also a great opportunity for us to add and create synergies by driving more products through our sales force. And that could be through additional tech, of course, it can be through consolidation in the market or it can be by entering adjacencies. So that's kind of what is driving us there. But again, I really want to clarify that we don't think like M&A is like the key piece to the growth algorithm. It's actually the smallest.

Got it. That's helpful. And then maybe on the first 2 pillars that you kind of mentioned on the organic side of things. You guys recently announced OneVision, which is a very exciting product. Maybe for people who don't know, could you explain what that is? And then maybe who you're kind of seeing the most traction with in terms of what types of customers are maybe adopting OneVision?

Yes. I think OneVision is one of these great examples to say, like, let's drive market penetration. And maybe let's talk about what it is, but probably don't know the knowledge here in the room, there might be different levels of information. Let's maybe take a step back first, what do we do mostly, right? We sell, and I mentioned it before, we sell software on device, right? So that means think about like you put a machine vision system on a production line, and it really executes and does all the computational task on the device in the line. And that's what customers like because for 2 reasons, latency, that kind of speed going into a cloud just doesn't work. And then second, cybersecurity. So the customers, they really like to have devices on the line, and they don't like very much to be in the cloud. And that means for you as a machine vision provider and a machine vision user, you can only use as much compute power as you have on the device. You can't use easily what the compute power is available on the cloud. And that means as Cognex I would almost argue one of our most secret sauce is to create machine vision models which are just optimized for the available compute power and make it work and cover as much as you can. And that's probably where we are better than everyone else in the industry. But still, there can be use cases, especially very complex inspection tasks where the compute power just is not enough. So you would want to tap into the cloud in some way. But the way how we found to do it is OneVision. And think about like OneVision maybe as a training room in the cloud. So that means a customer has a device, maybe has already used it for inspection task and now he wants to drive it to the next level of inspection. So let's extract all the data from this -- our Cognex device, bring it to the OneVision cloud and then run a deep learning training model in the cloud using the compute power of the cloud and basically improving the model, not improving, let's say, the one inspection, it's improving the model in the training room. And then you bring it back from the training room back into the device. And at this moment, you close the door to the training room, you cut your connection to the cloud, you're back in the line, you have the speed and you have the cybersecurity aspect. And that's basically what OneVision does. And why is that important? It's important from 2 aspects. It's, a, it makes it easier for, let's say, kind of the middle segment of the market to use deep learning type of applications, which in the past, you would need to use complex PC-based kind of cloud connected vision systems, very complex to set up, very complex to operate and to maintain. And then -- so it adds basically what gives access to a new customer group to that ability. And then for the more sophisticated customer like the top of the market, they maybe have been using this more complex system, but it was still a hustle for them. So now it becomes much easier for them. So for them, it drives efficiency. And therefore, we believe it's really a strong kind of differentiator and another addition to our Cortex ecosystem, which makes our customers being attracted to buy and stay with Cognex.

Got it. And so maybe help me understand, is it at the moment, are you seeing more traction with those customers that maybe have it easier to scale? Or is it the customers that have more complex techniques?

I mean traditionally, Cognex as a company has always served kind of the most sophisticated customers with the most sophisticated problems. And we're pretty good at that, and we serve some of the most kind of iconic companies around the world or globally with that. So in that regard, that's really where our stronghold is, and that's a good business and especially like in logistics, where I think it's well known Amazon is our largest customer, goes very well. But then at the same time, right, we drove this sales initiative to go broader into the market. And we like what we see at the moment in the packaging vertical where we really see kind of it yielding results and that kind of led to some of the more positive commentary in the last earnings call, where we said like, okay, instead of seeing that more flattish this year, we see some growth happening for that. So in that regard, I would say there's traction in both. But very clearly, our original strongholds the more sophisticated side, very clearly.

Got it. And then maybe on the longer-term view of things. When we think about AI becoming more democratized and processing becoming more available, Obviously, you guys have positioned yourself well within the machine vision space. Are you guys concerned that any smaller players may be adopting technology at a faster rate and just the accessibility to computing power, maybe that becomes a threat at some point?

Yes, it's a great question. And I think there are 2 sides how you think about it. There is a smaller player potential startups entering the space. And then you could -- sometimes you're getting asked like, do you think NVIDIA and Meta will be your future competitors with the large models which they train? I would say maybe the first part is very easy to answer because history already proved us that it's not a risk the start-ups, right? So a lot of start-ups like 4 years ago, collecting a lot of money trying to get into the space, and they have all not been really successful in that regard. So I think we can really say history has proven otherwise. Now on the other side, with the hyperscaler, the large language model provider, obviously, that vote is still out in that sense. But we believe that there are very good reasons why it would not. So first of all, I think one thing is you need to have very high accuracy, right? So you can't have like 99%. You need to more go towards 5 Sigma, 6 Sigma, that type of very industrial machine vision specific task. And we actually ran a comparison of some of the large language models against our machine version-specific model. And we can see that we beat them on accuracy on industrial machine vision tasks. So that's one, accuracy. But then I think even more important is that what I said before, it just can't only run in the cloud. It needs to run on the device. So that means you really need to optimize it for efficiency, right? You can't use this big language model, which use clusters and clusters of GPUs, but you don't have that on your device. So in that regard, that is a big step. And I mentioned before, I think that's where really the secret source of Cognex is. And then the other topic, scalability, how easy does it transfer that model from this specific task to another one. Now if you run another product on this line, can your model still address it. If you want to add now add another production line, how easy is it to transfer. And that's where we really consistently see our advantage and really also kind of our right to win, so to say. That's why we are not entirely concerned about kind of this large language models. But at the same time, we feel like there's a lot of opportunity bringing AI into machine vision. And why? Because with AI, we are able to solve so much more applications, which we couldn't do in the past, that it's really a demand generator.

Got it. And as you guys look to maybe fulfill this demand, you guys recently announced a new leadership team to help increase sales and growth and innovation. So you're a part of that. So I guess maybe from your perspective, what's kind of the most exciting thing that you're you want to see in the next few months from this group?

Right. So first, I would say I would applaud Matt, how fast he has moved on that, right? He's less than 6 weeks in the job, and put together his leadership team, and that's definitely part that he has been 7 years already in Cognex before. But then I think if you look a little bit into what was changed, there's a very clear alignment of that team towards the strategic objectives, which Matt outlined. The first being #1 in AI technology and machine vision. So you now have people in that -- from that leadership team who have not reported to a CEO in the past, they're now reporting to the CEO. So that means they get more weight in the overall discussion, right? First. Second strategic priority drive customer experience, be #1 in customer experience in the industry. Now our Head of Customer Success, who runs our gross functional customer experience push hasn't reported to the CEO in the past, now reports to the CEO. So again, very clear tie to the strategic objectives. And then last, to double the number of customers. So here, we have a new Head of Sales who is Carl Gerst. He's not new to the company. He is 27 years in the company, but he never worked in sales. He worked on the product side and what he brings is process, process focus, very clearly driving a playbook, a very consistent sales playbook. And I would say that's really a bit of a shift for Cognex as well. So again, here, a very strong alignment to the strategic objectives. But maybe you ask what excites me the most about this team. I think for me, it's really focused execution. I think that's really what we want to bring across to everyone on the Street is that we put our targets at Investor Day, and I think we are very focused and very clear about we will drive these targets. And we think we can control at least a good portion of the destiny, right? We can't control generally the market, but we can control some part of that growth by our sales resource allocation, and we can drive our bottom line performance by being disciplined on cost. And therefore, I think I'm pretty excited about that.

That's very exciting. And it's great to hear you guys are all focused from the top of the management all the way down. Maybe touch on the emerging customer initiative. I know that's kind of a big point for you guys. And I know that the second cohort is probably ramping about now. So maybe just how they're progressing and what makes you success -- makes you confident in the success for the Cognoids?

Right. So maybe, again, maybe a different information level here in the room. What is it? What are we trying to do? But if you go back to the last peak of the last cycle 2021, Cognex, fantastic growth in the years before, but very high customer concentration with 2 very large customers, right? And then at the same time, you see some of our competitors, namely Keyence being very successful in the broader market. So in that regard, you would think like, hey, is there a great opportunity for Cognex to grow outside of the established customer base going to more customers with attractive margins, actually. So that's kind of the strategic rationale behind it. And I would say, the initiative launched in '23 was hiring the first class then the first class of maybe I should say, what are we trying to do, bringing in a different type of sales people, which are more transactional focused and going broader into the market. So we decided we are hiring a bunch of between college grads and kind of 1 to 3 years' experience and bring them in, train them and then deploy them into the market. So we hired in '23, released the first class in '24 and then just released the second class beginning of this year. I think we went through a couple of learnings. I think we talked about that in prior earnings calls, on like what products are they sell, what are they really the right products? So we adjusted a bit on that. We certainly also learned in terms of management. So they are a bit different in terms of management. So in the beginning, we kept sales management separated for that reason. But at the same time, we also saw it drove a lot of inefficiencies in terms of the coordination of the sales force. So we combined the sales forces. And then we also realized like when we say about going to more customers, that does not mean necessarily to new logos. It sometimes can also mean that within one logo, you have different buyers, and we haven't visited all these buyers. So we also let them go to existing logos, but trying to find new buyers who have maybe a small buckets of budget, which we haven't tapped into to past. So we went through this learning curve, I would say. And I think we made some positive comments about what we saw in the packaging market in the last earnings call. So in that regard, I think we feel like we are moving into the right direction. But at the same time, I would say it's a strategic shift for Cognex, right? It's really kind of almost repositioning Cognex from only focusing on top of the market into a broader plan and that won't happen overnight. So in that regard, I would say, we're on the right track, but there's still maybe, I would call it, opportunity because we expect that the sales productivity of each of the salespeople will gradually increase over 3 years' time. So that means we'll still have a lot to get from this organization.

Got it. Yes, that's all been very helpful. And I know we're kind of up on time here. So Dennis, I appreciate the time today. It's been great.

Yes, thanks a lot. Thanks a lot everyone.