Schneider Electric S.E. (SU) Earnings Call Transcript & Summary

Good morning. This is the conference operator. Welcome to the Schneider Electric's call for analysts and investors with Olivier Blum, Chief Executive Officer; Nathan Fast, Chief Financial Officer; Caspar Herzberg, Chief Executive Officer of AVEVA; and Antoine Sage, Head of Investor Relations. Thank you for standing by. [Operator Instructions] I would like to inform all parties that today's conference is being recorded. If you have any objections, you may disconnect at this time. At this time, I will hand you over to Mr. Antoine Sage.

Hello. Good morning, good afternoon, and thank you for connecting at short notice. So as an intro and as a reminder, we are currently in a quiet period. So accordingly, today's discussion will be strictly limited to the agreement reached by Schneider Electric to acquire Cognite, and we will not be commenting on our 2026 performance. Joining this call, we have Olivier Blum, Schneider Electric's CEO; we have our CFO, Nathan Fast; and we have Caspar Herzberg, the Chief Executive Officer at AVEVA. For this call, we will present to you a couple of strategic slides that you will be able to retrieve on our website after the call as well as the press release that we issued yesterday. I'm going now to hand over the floor to Olivier and Nathan and Caspar, who will elaborate on the definitive agreement reached to acquire Cognite, after which we will open for question and answers. Olivier, over to you.

Thank you very much, Antoine, and good morning, good afternoon to all of you, and thank you again for joining in such a short notice. We are excited to be with you today, of course, to make an important announcement, which is the acquisition of Cognite. If I just go back to what we told you last year in 2025, we've decided to refresh our strategy and to enter in the new cycle. This new cycle has one simple goal, which is really to advance energy tech to the next level. And it means really being this company in the market, which will be able to connect the physical and to the digital world by electrifying, automating and digitalizing every industry business and home with a goal to drive efficiency and sustainability everywhere. So I told you in our Capital Market Day in December that we were entering in a new era, a new era where we believe intelligence is key, a new era where AI will require more compute, more compute will require more energy and energy and industrialization will sit at the center of everything we do at Schneider Electric, not only because it's important for Schneider Electric, but it's important really for everything we do, our customer. So for us, it's extremely important that we create a company that is able to connect this physical and digital world, a company where we can capture data, structure data, contextualize data and deliver those data across the life cycle. We believe that the company which will be able to structure those data on top of physical assets will be the company that will win in the market. So we believe this acquisition strengthens our belief that Schneider is in really in the position to be able by leveraging our data cube powered by AVEVA technology to deliver that unique value to our customers. If we go to the history of how we have built this stack industrial world, you remember, we started in 2008 by combining AVEVA and Schneider Electric Industrial software to start really to create the first industrial digital twin in our company. Later on in 2021, we have enhanced, we have amplified everything we are doing with AVEVA by adding OSIsoft, the world's leading source of industrial time series data. And now, of course, we are entering in this new era, in this new era of [ in-depth ] intelligence, where we want to build an AI industrial champion by combining the historical capability of AVEVA and everything that Cognite has been able to build. So we are building really a foundation that brings data to the next level and that can create true intelligence in the industrial world. So if I just tell you briefly about Cognite. Cognite is a company that has been created in 2017 in Norway. It's a company which has 800 people globally, a large number of R&D tech product people being located in Norway, great people. I had the privilege during the process to meet the historical founder who are still in the company and will continue to stay with us in the future. Their vision about the industrial world and how AI is going to impact the industrial world is excellent. They are benefiting to a very, very strong pool of talent in AI and they have been able really to do a remarkable performance, to deliver remarkable performance over the past years. And beyond the performance is with every single customer that I've met in the past 2 years, I can testimony that customers love the platform and really love the value. So let me briefly walk you through Cognite core technology stack, which is designed to transform industrial data into actionable intelligence at scale. The first layer is what we call Cognite Data Fusion, which somehow is a core foundational piece. It provides a cloud-native industrial data foundation. It ingests and contextualize if you want data across IT, OT, engineering system, creating a unified knowledge graph. So all together, this is what enables customers to unlock significantly greater value from their industrial data within a fully open ecosystem. The second layer that you see on the slide is really Atlas AI that brings an industrial AI agent layer, a unique one in its industry. And through a low-code workbench, customer can deploy AI agents on top of this data foundation to automate workflow and accelerate decision-making, which drive very tangible business impact and generate efficiency for customers. And if you go to the upper part of the stack, you have Cognite Flow, which act as the execution layer. It allows customers, people on site to rapidly build and scale production ready, AI native workload, which empower really the frontline team, as I said, to translate expertise into enterprise-wide value. So all together, you can see that those 3 layers create already stand-alone a powerful end-to-end industrial platform that turns data into intelligence and intelligence into action, which is really, really aligned with the long-term vision and strategy we have at Schneider Electric. So I remind you that we have started a journey at Schneider over the past year to start to create something unique in the industry, which is called CONNECT, where we combine really from design to build, to operate, to optimize, as I said, a unique set of application and analytics across the life cycle. So we are, as I said in my introduction and what we do in industry now today, we want to do it, of course, in data center. We want to do it in infrastructure. We want to do it in building, not always with the same technology, but always with this [indiscernible] that the company that we will win will be the company that can connect the physical and the digital world. Of course, Schneider Electric historically has a very strong positioning, a strong legacy in the physical world in all the segments, including in the industrial segment. But going to the next layer of intelligence is absolutely essential. And that's why I repeat myself, we have created this unique combination first of AVEVA and Schneider Electric software, then amplify with OSI, then now we amplify with Cognite. We believe that we can create an ecosystem that can be unique in our industry. And all of that we want that ecosystem to be enabled to be amplified by developers and partners everywhere in the world. So this platform has to be extremely open to welcome any kind of technology partner that we onboard on a regular basis. So that's what we have done so far at Schneider Electric with AVEVA. And now I would like to hand over to you, Caspar, to explain a bit more in detail how Cognite and Cognite CONNECT and Cognite are going to work together.

Thank you, Olivier. And when you look at the design, build, operate and optimize life cycle of industry and you translate this life cycle into data, then you will see on the design side, models, assets, right? And these assets are at times very, very large, millions of data points if they are big process plants. right? Then on the operational side, you have the time series data that Olivier talked to that comes from how machines fare when they produce something. So this is vibration data. This is all sort -- this is the experience of the machine, if you like. And then, of course, you have optimization data, which is what you do with all of this data, asset and operational data and other IT and enterprise data, right? So all of this together, we brought to the market in CONNECT, right? Most of this data today still sits on-prem and is then usually copied on the cloud for analytics and for AI. We've introduced a no copy capability, meaning that only the data you need to work with in the cloud is taken. And the challenge, of course, with these enormous amounts of data is how to scale this and while then dynamically maintaining the context of that data to each other, the context of plant to machine of time series data like a certain temperature on a certain day, 10 years back, all of this, how to maintain that and how to dynamically model that in the cloud. And what Cognite does for its customers is take this fragmented complex industrial data and integrate it into a single unified data model and most critically, a knowledge graph, supported by, as Olivier said, the Agentic AI workbench where you can use algorithms to dynamically model this without a lot of coding. And that gives us now as AVEVA, Cognite and of course, at Schneider, the ability to have the full life cycle of design, build, operate, fully working in the cloud for our customers for analytics and of course, because of the dynamic modeling as a way of feeding into what the AI models of robotics, the AI models of any type of industrial AI need. So this is at the heart of this acquisition. In summary, it gives us the ability to ingest, to contextualize data, not just from the Schneider and AVEVA systems, but across because we are -- because we have open softwares. All of our customers broad pre-existing data ecosystems, as I said, third-party data and so on. Let's go to the next slide. Let me talk about how AVEVA significantly accelerates Cognite because what we bring them is immediate scale across all of the large industrial segments that AVEVA is currently -- that AVEVA and Schneider are currently supporting. And of course, the global footprint on top of that, that Schneider Electric has with its countries and its strong go-to-market engine. In addition, we have an installed base of more than 23,000 customers with the comprehensive portfolio I described earlier. So that gives, in summary, Cognite a reach, a depth and a scale to accelerate adoption and to bring the innovation they have to very often our joint customers and increasingly as they move towards life sciences out of the pure process industries to new customers. Cognite, in turn, as I described earlier, accelerates AVEVA. It accelerates by bringing a modern cloud-native SaaS architecture with the focus on industrial data and AI I described. It brings advanced capabilities in industrial data management, the data graph, et cetera, that I just mentioned, a rich library of industrial extractors that will be added to the huge library of connectors and extractors that AVEVA already has. We would then be able to do any type of industrial data extraction for our customers, more than probably anyone in this industry. And of course, together, we will form a unified platform for the next phase of industrial AI because what Cognite brings neatly fits into what CONNECT has. And lastly, to say, of course, they bring a significant level of innovation and of a dynamic go-to-market focus on growing new customers, winning new logos. And you have to imagine this is like a locomotive that pulls the larger AVEVA with it to significantly more growth. Next slide, please. And what you see here is just a very small extract of the different segments in which AVEVA is playing today and some of the customers. Some of them, many of them, Cognite customers today, often with a small land presence. But of course, the combination of the 2 companies is going to create a scaling effect across that customer base of, as I mentioned, 23,000 customers that is going to be hugely, hugely powerful. With that, I'd like to hand over to Nathan for the next step.

Perfect. Thank you, Caspar, and good morning, good afternoon. I guess let me take a brief moment to cover the key terms of the acquisition, which you'll see are fully aligned with our disciplined capital allocation framework and priorities. So starting first with Cognite's financial profile. In 2025, the company reported an excess of USD 170 million of revenue with strong momentum reflected in 36% growth in ARR bookings. If I turn to valuation, we have reached a definitive agreement to acquire Cognite at an enterprise value of USD 3.1 billion with the transaction to be fully funded in cash. In terms of timing, the completion of the transaction remains, of course, subject to customary closing conditions with closing expected over the coming quarters. Once completed, Cognite will be integrated with AVEVA and will be fully consolidated and financially reported within Schneider Electric's Industrial Automation business. And to conclude, overall, of course, this transaction, again, is fully consistent with our strategy tied process-defined M&A discipline, combining a strong strategic fit first, a compelling financial profile, strong growth and gross margin and a high degree of integration readiness. So Olivier, maybe before we go to Q&A, I'll hand over to you for any closing comments.

Thank you, Nathan, and thank you, Caspar. As we said many times from our Capital Market Day to the different conference and meeting we had together, we said we will be always really open for M&A in a very, very targeted and selective manner. And Cognite is really in this category. I mentioned as an example that in the past, we have acquired, for instance, Motivair to accelerate really our technology stack in liquid cooling to go faster in capturing the growth opportunity in data center. That's very similar when we talk about Cognite today. The goal is really to accelerate the execution of our strategy, becoming a worldwide champion in the industrial world by taking AI to the next level is part of our ambition. It's a strong element of differentiation. And what we found in Cognite is great technology stack, great product, high-quality people. And as I said in my introduction, a leadership team, which is made of historical founder who are committed to stay with us after the transaction and also many other people on the technology, on the commercial side that really understand the industry. They understand technology. They understand AI, but more important or equally important, they really understand the industrial world, and there was a strong technology fit, but there was as well a very strong cultural fit, which is always extremely important for me. This is a capacity of not only acquiring great product, but how it will fit with our culture. And I'm really excited. And of course, we will have a period as Nathan mentioned until closing, but preparing the next step where we will combine the force, and we will ask really Cognite to lead this AI industrial platform is super exciting for us. So you can imagine that a strong attention will be put in place on retaining the people, developing those people and make sure we do a great, great integration culture in order to retain the key talent. So it's time for me to conclude. Cognite accelerate our AI journey, you understood. If I step back a little bit on the big picture for us, it's really executing our strategy, going to the next level of AVEVA story. But I would amplify even more that what we found in Cognite will help also to enhance all our energy management technology stack on the software side because as we said multiple times, our goal is to bring industrial intelligence to our customers, but also to bring energy intelligence. So we are extremely excited. And of course, the focus will be really on delivering strong results and be able to grow fast that business with high level, of course, of profitability. On that, I will stop, Antoine, and hand over to you for the Q&A.

Thank you, Olivier. Thank you, Nathan. Thank you, Caspar. Look, we've covered a number of areas, and I think likely addressed some of the key questions that you may have. So we just have 10 minutes remaining, so let's move to the Q&A quite fast. [Operator Instructions] So with that, operator, can we please open the line for the first question?

The first question is from Alasdair Leslie of Bernstein.

One of your opening lines yesterday in the press release, you talked about industrial AI shifting from supporting analytics to acting on and kind of executing operations. So I guess that's really interesting and quite exciting, obviously, could unlock a lot of potential productivity and growth. So I was just wondering maybe if you could just help us understand how much Cognite might help you kind of leap forward to that point. How close might you be with Cognite to kind of AI autonomously taking command of real operations?

No, sure, that's a good question. Caspar, do you want maybe to give a concrete example because we have already some customers who are using our own AVEVA platform and Cognite. Maybe it would be good that you give one customer example or one application where we've been able already to demonstrate.

Absolutely. So we have a large customer in the Middle East that is using the combination of Cognite platform with the data from the PI system and the data from our -- both process simulation capabilities to model and autonomously make decisions for their large petrochem assets today. Maybe further than that to the question because when we look at robotics and when we look at the growth in robotics in factories, the more autonomous that is going to become, the more the core data infrastructure needs to be dynamically modeled. And this is where the combination of Knowledge Graph and Agentic AI capabilities, their AI workbench are incredibly important because you will be able to dynamically model the changing data, the changing operations data, the sometimes changing asset data for your robots basically. So I think it's going to be a key enabler of the use of the accelerated use of robotics in factories. Back to you.

The next question is from Andre Kukhnin of UBS.

I just wanted to see if you could help us to understand better the kind of market positioning of Cognite versus its peers and who they would be? And could you help us to assess the kind of technological position of Cognite as well? And how can we track that in the future?

Caspar, please go ahead.

Yes. So in industrial software, it is the largest and probably quite unique company in that space, which is why we've been after it, frankly, for many, many years, right, because it complements us so well. If you're looking at the more analytical level, I would look at the companies like Databricks, Snowflake and some of the hyperscalers as comparative. Basically, what you do with industrial data in the cloud in an AI agentic way is a new area where a lot of people are interested, including some recent announcements by Prometheus and others. But with this type of customer base and this proven way of doing things, both the combination of AVEVA Cognite and Cognite itself is pretty much peerless, I believe, at this point in time.

The next question is Phil Buller of JPMorgan.

And perhaps Olivier and Caspar, I can see the strategic fits of Cognite. The questions I am getting today more along the lines of are there more gaps to fill? Does the deal complete the [ IA ] software portfolio? Or are there more to come that perhaps you've been looking at for several years as you had with Cognite and is this the multiple we should get used to really?

No, thank you. I will take that one. Look, as I just said and I repeat it multiple times, we are not obsessed by inorganic. We are obsessed by delivering our technology stack to our customer to integrate properly, to deliver great customer value proposition. This step is an important one, and it comes at a time where AVEVA and OSI have been digested, have been integrated. And definitely, the team now has the bandwidth, the possibility really to go to the next level. It doesn't mean that we will come back tomorrow morning with other acquisition. I think we want to do step by step and again, to continue to be very, very selective only if it makes sense. So as I said multiple times, the focus of Schneider Electric is to deliver our equity story organically mainly -- and by exception, when there are great technology, great company that help us definitely to accelerate the strategic execution, we will do it. So my short answer is don't expect us to come back to you with many, many deals. This one is an important one. Now it's time for Caspar to integrate, to deliver the synergies, but we'll continue to monitor the market whenever there is great opportunity.

The next question, gentlemen, is from James Moore of Rothschild & Co.

I just want to come back to the primary rationale. I don't know, Olivier, if it's for you or Caspar. But is it that the white space and the thing that you really needed was the knowledge graph. And as we shift towards Agentic AI, the knowledge graph understanding without having to search through millions of second -- millions of data records in order to come up with the answer. And is that not somewhat similar to the Ontology of Palantir? And is it something that is similar to the sort of Rapidminer, Siemens software? Is that the space that we're talking about? And is that the rationale and what you were missing and why you really bought the business?

Two great questions. Caspar, do you want to take it?

Yes. So in the industrial space, it's the only one, we believe, that has the combination of Knowledge Graph that you have very well described and agentic workbench that works with the data and puts it into the Knowledge Graph. So in that respect, it's fairly unique.

Okay. Thank you, Caspar. Thank you, James. Look, all right. I think that now it's time for us to wrap up. So thanks, everyone, for your time. Thanks, Olivier. Thanks, Nathan. Thanks, Caspar, for your participation. Next time we will recollect together will be for our H1 results release. So in the meantime, let me thank you again and wish you all a very good day. Thank you. Bye.

Thank you all. Have a good day.

Ladies and gentlemen, thank you for joining. The conference is now over, and you may disconnect your telephones.