Hexagon AB (publ) (HEXAB) Earnings Call Transcript & Summary

Good morning, good afternoon or good evening dependent on where you are watching this. But welcome, a warm welcome to the Hexagon Capital Markets Day. We're going to talk about capturing opportunities for a sustainable future. But first, we're going to go back in time. And do you remember 20 years ago, how life was? Do you remember that the world was in paper? You read the morning paper. If you wanted to know what was on TV, you looked up your TV Guide. And if you try to get from A to B, you took up a physical map, a big map, and you navigated using that map. And if we dive into the year of 2001, well, we use Internet. Internet was definitely becoming a big thing. But we also used normal television when getting the news or read newspapers. When it came to food, we went to our local supermarket or our local grocery store, and we bought whatever we needed. Logistics was done by trucks, trains, ships and air. And travel and transportation, we begun to see the low-cost airlines, but they weren't really a big thing 20 years ago as they are today. And in energy, we used coal, oil, fossil fuels, nuclear, hydropower. Retail was done on site. We went to retail parks, to the high street to luxury city centers and malls. And if we wanted entertainment, we went to the cinema. We went to arcades and parks. And if we fast forward to 2021, look at how our lives have changed. Today, when we want entertainment, we use Netflix, we stream movies. We download movie rentals. We got Spotify or Apple Music. The gaming industry, the online gaming industry is huge, not to talk about the social media platforms that we're using a little too much in our society today. And news we get from the Internet, from social platforms or IPTV. Food is shipped to our doorstep. If you live in Manhattan and you use Amazon Fresh, you can have your groceries delivered to your doorstep within 40 minutes. Logistics, we're beginning to see the introduction of electric and hydrogen trucks. And when it comes to travel, we all think should my next car be an electric car. Energy, we've seen a huge growth in renewables. We have solar farms. We have windmills. And when we shop, we do a lot of digital shopping today. So it's a complete change of the way we lead our lives to only 20 years ago. And you might wonder what's this dog got to do with this? Because the message today is that digitalization has reached the industrial society. Over the past 20 years, we've seen most consumer industries being transformed because of the digitalization -- And now its industries turn, and that's what we're going to discuss here today at the Hexagon Capital Markets Day. So what's this fellow got to do with that? Well, we're going to discuss digital twins. And you've heard the concept of a digital twin. And I learned a new phrase today, and it's called cat fishing. I'm way too old to do online dating. But if you want to improve your chances on a Saturday night, you post a slightly prettier picture of yourself, maybe trying to describe yourself in a little more rosy way than the true origins of yourself. So that's what a digital twin should not be. And I'll give you real life example. Let's say you scanned New York City 1931, 90 years ago. And you got a perfect representation of New York City down to centimeter accuracy. Well, it's a good digital twin from a technological point of view, but it's useless. And the reason why it's useless is all the construction we've seen since 1931 in New York City that has changed or altered the real world. So what we want to discuss that Hexagon is smart digital reality. And that's when you add another dimension, and that is time. Things change over time. It's not good enough to just have a digital twin. You need to have a workable digital twin that is up to date. And what we do to create that is we create smart digital realities by fusing our technology. It starts with the real world. It's always a real-world event. And we do data capture and transfer in real time to our digital twin, where we have data visualization and analysis. And it always leads to a defined action that impacts the real world. So when you fuse the real world with the digital world in real time, that's when you create smart digital realities, and there are a few prerequisites. First of all, your data collector must be in real time. And we have some friends here today. I don't know if you can see them on stage, but we have our dog, the BLK RTC or [indiscernible] as some people call it, and we have the drone. And these are typical examples of real-time capture sensors. Then you need a real-time transfer into your visualization model, you need to define the actions and then you end up in physical activities. So this goes for any industry Hexagon touches. We can do this in discrete manufacturing using our current technologies. We can use it in industrial facilities to create efficiency. And we can use it in building an infrastructure and also in safety, security and surveillance. And as a matter of fact, when we fast forward into the next 10 years, this is going to have a great impact on the way we lead our lives. We're going to see autonomous systems in logistics. We're going to see autonomous manufacturing of food. We're going to see autonomous travel systems. They're going to be green. We're going to see a huge transformation of how we harvest energy. And we're going to see a continuous change in the way we shop, and we're going to see a continuous change in entertainment. And Hexagon is going to impact all of this. And that's why we're so excited about the future, and we can't wait to introduce all the things we're going to talk about here today. The opportunities are virtually infinite, and they extend beyond our traditional core markets like manufacturing, AEC plants, public safety and so forth. Just imagine to use one of these robots to replace manual labor such as security guards. Think about you being or having a digital twin, an Avatar, that you could use in many situations from medical to online shopping or even surgery. Think about digital realities for media, entertainment, tourism or even collaboration between geographically dispersed groups. And to the right, you have a snippet from the next generation of Hexagon digital realities. It looks really good. You really have to look twice to see is it just a digital rendering or is it photos? So at the end of the day, don't settle for a digital twin, go for the real thing, digital realities. And with that, I would like to kick off the first section, which is autonomy in buildings and infrastructure. And I'd like to welcome Hexagon CTO and my dear colleague, Burkhard Boeckem.

Thank you, Ola. Welcome. My name is Burkhard Boeckem. And I'm the Chief Technology Officer of Hexagon. Today, I'm going to share with you Hexagon's vision for an autonomous future. And then Thomas Harring is going to show you how we apply it in building and infrastructure. You will hear more in other areas as we continue throughout the day. Together, we will look at how we at Hexagon transition from automation to true autonomy and how our enabling technologies create autonomous systems that put data to work. Our ecosystems have come to a limit. In fact, our planet has come to a limit. Our future requires a big shift. And the best way to do this is by scaling automation and hyper connectivity to achieve higher levels of autonomy. Think about mobility, automations like cruise control on your car. It is great when you're cruising down an open road, but as soon as something unexpected happens, it is not sufficient. The ability to learn, adapt and ultimately predict the unexpected before it happens is what autonomy is all about. And think about construction of buildings and infrastructure. Are our processes and the way we work, sustainable? Are we using our resources to the best of our ability? Across all industry, our goal is to drive efficiency and achieve sustainability. At Hexagon, we believe autonomy is the path forward. In today's automated and hyperconnected world, data creation is by far outpacing our ability to leverage it. Most of it sits unused and unconnected. Autonomy enables you to put all of it to work, providing the advantage to shape unpredictability to your benefits where you can be proactive, predictive or even preventative and artificial intelligence will help us achieve that ultimate form of putting data to work. We believe that autonomy will play a key role in all the vital industries, taking the human factor out of potentially harmful or risky operations, using smart machines and robotics for the execution of repetitive task, utilizing artificial intelligence to predict and prevent events long before they might happen. And this will have a major impact of the efficiency and sustainability of these industries. At Hexagon, we own and further develop the enabling technologies for autonomy. And we developed the corresponding platform such as HxDR and Xalt to build industry-specific end-to-end solutions. Autonomy will be the key in building and infrastructure for efficient solutions for the complete life cycle of buildings, vertical structures and large-scale engineering projects. The blue print of our core processes, agnostic of industry and segment, can be explained as follows: reality capture, positioning and data transfer, create digital realities, digital twins, enhancing these digital realities by design, simulation and location intelligence. With this, the physical world and its digital twin become one reality. And this is what we call smart digital reality. And in this smart digital reality, one can build, maintain and redesign the physical worlds. Creating a smart digital reality is key. And that's why our latest autonomous innovations come from our BLK series of reality capture sensors. But first, let's define what we mean by autonomy in reality capture that leads to autonomy in industries as building and infrastructure. Robots and platforms navigate in thin spaces without human intervention. Sensors adapt to the environment while continuously capturing reality. Artificial intelligence-based software connects directly to our autonomous sensors and process the data these sensors create in real time. Combined, these technologies create a complete autonomous system from data capture to creation of deliverables, insights and experiences. One key enabling technology for autonomy to allow for perception, navigation and reality capture was introduced with a Leica BLK2GO in 2019. We call this technology GrandSLAM. SLAM stands for simultaneous localization and mapping. At the same time, we estimate all 6 degrees of freedom for the BLK2GO and build the 3D map of the environment we navigate through. And we use best of both worlds, visual SLAM and LiDAR SLAM combined, a technology unique 2 Hexagon sensors. We call it GrandSLAM. We took this unique GrandSLAM technology and developed an autonomous perception, navigation and reality capture module for all robotic and autonomous platforms. We call it BLK ARC. ARC stands for autonomous reality capture. BLK ARC brings autonomous navigation and laser scanning to these powerful robotic platforms to allow for an autonomous reality capture workflow. The fully integrated module consists of multiple high-resolution cameras for navigation, perception and creating panoramic imagery and even point cloud colorization. Our unique dual axis LiDAR allows for 3D scanning, and together with the inertial measurement unit in combination with the multi-camera system for GrandSLAM navigation. Our first robotic carrier for BLK ARC is the Boston Dynamics Spot robot. Boston Dynamics is a world leader in robotics and we're excited to collaborate with them in this field. As a module, it can be integrated with many different robotic platforms for many different applications. BLK ARC will revolutionize how our robotic platforms can capture reality and navigate in 3D spaces autonomously. A further step is to take this tight integration into the flying system that we develop from ground up, and it's called BLK2FLY. We took our GrandSLAM technology and our proven lightwave dual axis LiDAR. And these we combined with additional perception sensors, such as multiple radar sensors, added cameras to allow for an all-around vision, a dual frequency GNSS for surveying grade, absolute referencing, and even a time-of-flight range finder for smooth landing and created the world's first autonomous flying laser scanner. The BLK2FLY enables users to capture complex buildings and structures completely, from facades to roofs, by bringing reality capture to previously inaccessible spaces. BLK2FLY creates its own scan path and flies around structures while capturing reality in 3D. And after a successful mission, BLK2FLY returns home safely. BLK2FLY is a true autonomous system, and we are not considering this a drone. It's an autonomous flying laser scanner. We again minimalized the size of the whole system and tight integration for portability and to make it simple and easy to use. The BLK2FLY will change workflows in many industries. Building and infrastructure will be a primary target. The age of autonomous robots and platforms is here. With BLK ARC and BLK2FLY, we start a new era of autonomous really to capture systems. Both new solutions will allow for scaling of reality capture and boost efficiency. BLK2GO, BLK ARC and BLK2FLY will also connect directly to HxDR our cloud storage collaboration and visualization platform. These autonomous sensors upload their data automatically to the cloud where users can view and share data with colleagues all over the world. What's beautiful about HxDR is that it takes the same concepts of 6 degrees of freedom applies it to the data itself and even at the element of time. HxDR users can explore highly realistic visualizations by navigating through a digital 3D space with full control over movements, views and perspectives. HxDR will create a new way to work with reality capture data in real time from AI-based advanced data processing to high-end photorealistic visualization. HxDR completes our autonomous system for reality capture. Imagine then, being able to put on a pair of augmented reality glasses, and take advantage of the smart digital reality that you have created. With the ability to utilize the 6 degrees of freedom in augmented reality, you can explore the digital world and the real world simultaneously. The combination of spatial anchoring, as introduced by the recent acquisition of Immersal and smart digital realities allows us to directly connect the real world with a digital twin. Thus, closing the feedback loop as it is required, for example, in building and infrastructure throughout various stages in the life cycle. From automation processes of construction site and infrastructure projects, to special effects in extended reality such as virtual augmented reality, HxDR can apply data autonomously to real-time situations. Thank you for your attention. I'm going now to turn it over to Thomas to show how we pair this technology with our domain expertise.

Thank you, Burkhard. There has never been a better time to bring autonomy into buildings and infrastructure. Hello, everyone. My name is Thomas Harring. I've been with Hexagon for 18 years, and I'm President of the Geosystems Division. In Geosystems, we are focusing, among other industries strongly on solving current and upcoming customer problems in the buildings and infrastructure ecosystem. Let me take you now on our journey towards autonomous solutions in building and infrastructure in a simplified manner. It's about pairing technology leadership with domain expertise. What is the context of buildings and infrastructure? Buildings are any vertically built structure. Infrastructure refers to anything horizontal, which includes everything from large public works, roads, dams, bridges to water utility distribution networks. I believe William Gibson is right. The future is already here. It's just not evenly distributed. Most of what enabled change, at least, the short to midterm is simply the spread of existing technologies to become more persuasive. We are powering innovation for sustainable future. Let me give you some background to it. There are so many statistics and facts about buildings and infrastructure, and it's known from industry productivity that it has [ trailed ] that of other sectors for decades. And the gap has not been reduced. On average, the cost overrun for large public projects is greater than 50%. Construction is challenged with greater than 50% of non-value-add activities. In manufacturing, this ratio is well below 25%. Also greater than 40% of world's carbon emissions are tied to the construction operations of buildings and infrastructure, not including transportation or other adjacent industries. And it's estimated that roughly 30% of the emissions are wasted. But the performance of the global industry is not uniform. There are regional differences and major variations depending on projects. For quite some time, the ecosystem has been in a deadlock to overcoming the barriers to higher productivity and sustainability, but this has changed. Today, technology offers significant opportunities to improve the total cost of ownership and pave the way for a sustainable future. The evidence is overwhelming, powering away industry to [indiscernible]. No wonder the digital transformation is gaining momentum as innovation gets faster, collaboration more efficient and more value is delivered with less effort. Digital transformation is software empowered. But even more, it's a customer driven. It's a never-ending journey, focusing on key elements for buildings and infrastructure, collaboration and remote work. Connecting people and equipment in the field, in the office, and, of course, between field and office. Productivity, health and safety. Workload has moved from specialists first into operations and further on into robotics. Insight-based decision support with machine learning and other AI technologies, data can be analyzed and prepared fast and without human intervention. An example on the right indicates that today already AI-empowered construction insights provide automatically identified safety issues on site and can benchmark safety measures across multiple production sites as well. Let's have a look at the asset life cycle, a holistic, integrated digital landscape, unifying the off-site and on-site activities with seamless collaboration within the cross phases. Hexagon's core competence is putting data to work by delivering what we call working with smart digital realities. In simplified terms, bringing the physical and digital world into 1 reality. In the design phase, dynamic real word scenarios and cloud collaboration become more of a reality. In the planning phase, our solutions support holistic and transparent model-based planning in all relevant 5 dimensions, truly 5D. During the build phase our solutions support to deliver on time, on cost, on specs, while ensuring safety and compliance. And during the operate and maintain phase, our solutions facilitates the operations of assets, where the customers own, manage or occupies them. Key overarching topics are placed in the center where they belong. Sustainability by design means put sustainability at the heart of the business and integrate it with everything which is done throughout the life cycle. Green engineering with engineers of environmental stewards ensure sustainable developments right from the drawing board. Design to life cycle means to keep a virtual representation of the object alive and provide a common single source of tools. And technology and industry convergence stand for emerging connections between different technologies such as sensor fusion, edge computing or cloud and between different industries such as prefabrication or industrial construction. No doubt, it's an exciting time. The shift from technology to opportunity leads to massive improvements in productivity and sustainability. Let's start with the power of connecting design and planning with the real world. Say you want to build a highway, as shown in the BIM model on the right side. We use special data from the surrounding environment and assets allow you to decide how to arrange your work and support the pending of your work. Combining our Hexagon Content-as-a-Service program with the Brexit cloud collaboration software and common data environment, creates immediate value during the preconstruction of a highway. Let's assume you have done your model to construct the highway using machine control. We are guiding and automating machines according to that design, these design models and ensure safety during the operations, all in 1 software and always connected. If customers do earthworks, [indiscernible], asphalt paving or any other activity in road construction, the collision avoidance solutions protect people and the critical assets. These safety solutions in construction have been adopted from the well-established mine protect portfolio of Hexagon Mining, a great example of technology sharing within Hexagon. But let's move from heavy construction to a large complex building construction side. The construction of the new CIRCLE Campus at the Airport Zurich shown on the right side, was a complex construction project, with a lot of field and office sensor and software involved. On the left side, you see an example of the benefits of modern field solutions such as Leica GS18 I, not only in the field but also directly in the office. No matter how complex your measurement or data capturing or verification tasks are, it is important to be aware of the progress of the project. Our field and office solutions offer you all the tools, the document and report on individual steps and final results, infinitely connected. Capturing in the field, preparing for data in the office and put these data then to work back in the field with a constant feedback loop is what we mean with smart digital realities. Construction is about boots on the ground and eyes on the job site. Construction cameras are taking yearly minimum 25,000 images of a job site. Using AI empowered insight makes it possible to take critical decisions faster using actual information. With our software and service solutions, construction professionals see activity levels in combination with weather other information. And can then see when, where or how the progress may be impacted by a shortage of labor hours or [indiscernible]. Also, AI insights monitor safety compliance by identifying and tracking the use of personal protective gear, or working at height. With the equipment tracking functionality, project managers look for large equipment and follow it around to check how it's being used. In summary, using artificial intelligence with visual data allows construction professionals to see trends and potential risks. This all into 1 sensor and Software-as-a-Service solution connects field and office and bring reality into the office. Hexagon's innovative SMART Build Insight is drafted to optimize design and construction by connecting the office and the field every step of the way. On the right side, you see the integration of the construction insights based on webcam technology as shown before, fully integrated. Visibility in project status with stakeholders, the ability to drill into details, enabling root cause analysis and faster course for correction. On the left side, you see a concrete example how to manage issues during the construction. In the dashboard, issues in that module, issues are indicated and then this allows you to zoom in within your 5G model. So you'll get directed to the imaging or getting information of the indicated area. And you can make visible what the issue actually is. So Hexagon SMART Build provides autonomy to the project managers to work with the data they need to take decisions and that into 5G, smart digital realities. Increased building performance implies to us the use of digital solutions to improve productivity and sustainability during operations. Let's take a look at the benefits of a digital trend of an existing shopping center. Within 2 days, the entire shopping center was captured and a complete smart digital reality created, which is connected to a computer added facility management system. All assets are [ in tact ] and can be maintained remotely with the relevant content and documentation. With the spatial anchoring technology, as explained by Burkhard, we are now also able to provide an additional indoor navigation functionality. Space and energy planning, renovation, predictive maintenance and many other use cases are becoming more traceable and productive. And now we are also able to bring reality capture to the next level. Burkhard mentioned already the exciting achievements, how we are bringing reality capture to the next level. We are combining GrandSLAM technology and autonomous perception, navigation and data capture for robotics with the BLK ARC. And we created a flying laser scanning sensor called BLK2FLY. Let's take, for example, the rail industry. It's about efficiently and safely capturing digital realities of the rail tracks and network environment to make more informed decisions whether it's about track clearance, asset management or infrastructure or train stations, check geometry -- track geometry or change detection. BLK autonomy gives you greater freedom to capture the world. It can go or fly where you can't, like dangerous or inaccessible areas. All BLK autonomy solutions can, of course, automatically upload the capture data directly to HxDR, Hexagon's Digital Reality platform. Working in smart digital realities is key if you want to put your data to work in real life conditions. HxDR provides own needed functionality for high-end visualization, sharing data among defined stakeholders and applying AI-based analytics to your data. Users cannot only upload their own laser scanning content or access data from the Hexagon Content program, they can also upload 3D BIM files to put models in context. HxDR brings all together in an advanced yet easy-to-use platform designed for dimensionally accurate and immersive 3D visualization and sharing. In summary, we are committed to making work easier, insights available and decisions better by putting data to work throughout the asset life cycle of buildings and infrastructure. We are accelerating our pace of innovation, and we'll continue to do so. Turning technology into opportunity and ensuring customer proximity will always be the essence of what we do. We are innovating for a sustainable future and expanding our opportunities. By enhancing our solution offering, we are providing more and more end-to-end solutions by taking advantage of industry and technology convergence especially within broader Hexagon. And by scaling, we are benefiting from our strong global footprint and local reach. All this directed towards empowering an autonomous future. We are continuing our portfolio transformation, strengthen our resilience through innovation, utilizing acquisitions as an accelerator and are disrupting with autonomous solutions. Our digital solution rollout is running at full speed with results in endless opportunities. Together with our strong and passionate teams, we will always find innovative ways to success as a journey towards an autonomous and sustainable future by having technology leadership with domain expertise goes on and on. And we are, have been and will be a strong contributor to that. Thank you very much. And now we open for question and answers.

Thank you, Thomas and Burkhard. We have a few questions from the audience that's come in. First question, can you explain how the BLK ARC will be sold and the relationship with Boston Dynamics?

Yes. That depends on the customer requirements. Take an example, a customer has already a spot and wants to make out of it a complete reality capture solution. Then we would provide the module and would help on the integration. But if customers want to do a project with us, an end-to-end solution, fully integrated in a software workflow, of course, we provide the full solution and the full integration, including support to them. So really depends on the requirements and requests from the customers.

Great. Thank you. Another question from the audience is HxDR only data storage and sharing and integrated machine learning AI type services?

HxDR is combines all of it. And HxDR is a cloud-based collaboration and data sharing platform but it has so much more. It's a cloud-native architecture. So we can run micro services in the cloud. And these microservice already today have AI capabilities like we have currently the automating, but also then in the future land cover detection and much more what you can do and detect and getting insights out of reality capture or Geospatial content data.

Great. And another question from the audience is can the BLK2FLY and BLK ARC address new markets you're not currently in?

I think you have seen in the beginning, Ola when presented the vision, a lot of interesting applications something we're addressing already is media and entertainment. We're addressing already the rail industry, as I have shown or we are going strongly into public safety. And all of that together with the colleagues in the other Hexagon divisions where there are enormous potential for new use cases and new segments, which we can further explore. And we get a lot of interest in customer requests right now where customers have great ideas what they can do with the solution.

And then a question around GrandSLAM. Is this something that is unique for Hexagon? And why is BLK2FLY unique compared to other reality capture drones in the market?

I think it's a fair statement to say that GrandSLAM is very unique and unique to Hexagon sensors. In the past, you had SLAM technologies, which means that you had it based either on a visual system like camera based on a LiDAR system, LiDAR-based. But visual systems are really great if you have a good contrast, if you have a lot of features, but what you do in a dim-light situation or what do you do at night, then normally LiDAR SLAM based systems have big advantages. But if you take both of -- best of both worlds together, combine them, tightly couple them, then you probably have the best solution in any of these cases and any of these corner cases you are able to safely navigate and really to capture in those situations. Coming back to the BLK2FLY, this is a perfect example of tightly coupled systems and sensor fusion, I would say, almost at its best. As I said in my presentation, it's not only our dual axis LiDAR that does the reality capture that we know also from the BLK2GO, it's the combination with the camera system. You have an all-around vision. And then if there's something when there's an obstacle, you cannot see or detect with a visual system, then you have the radar systems, helping the obstacle detecting and finding a path around this obstacle. So that's the uniqueness, and we don't consider the BLK2FLY as a drone. It's so much more. It's a flying laser scanner.

Great. I think we have time for one last question here. Can you touch on the analytics and AI capabilities that Hexagon currently offers?

We have a vast offering of AI capabilities. And you will hear throughout the afternoon, more and more in the different industry. Kalyn Sims will elaborate about the Smart assistive Advisor. But we are able to use AI in our machines in the sensors at the edge to detect certain scenarios. We can track prism devices and total stations, we can extract information out of point clouds and out of Geospatial content, be it, for example, airborne imagery, we can detect land cover classes completely autonomously using deep learning, machine learning on any form of artificial intelligence. We have a vast offering.

Well, thank you, Thomas and Burkhard, and now we will go on a short break. [Break]

All right. Hello, and welcome back, everybody. I hope you had a nice coffee break. It was an exciting session this morning, I thought. I mean, first, we heard Burkhard talk about some of the amazing technologies and the reality capture solutions we have. And then you saw Thomas talking about how do we apply that in the buildings and infrastructure space. Now I'm going to do the same, but I'm going to talk about industrial facilities. And then I'm going to be joined by Paolo, who's going to do that same thing in discrete manufacturing. And if we dig into things here, as a reminder, when we talk about the industrial facility space, this is a space where Hexagon has been a world leader for decades. We are, at least, in my knowledge, the only company in the world that cover our customers' workflow from A to C. Whether you talk about design, planning, materials, construction, fabrication, all the way to operations and maintenance we have the offering for our customers. And it's all connected in a data-centric way. What I also want to highlight on this slide is the latest box here that you see called Secure. It comes from an acquisition we did about a year ago of a company called PAS, which is a cybersecurity company that I'm going to mention a bit later in my presentation. Anyway, so when we -- what's the end goal of all this, you might ask. Well, it is to create what we call the ultimate digital twin. And what is -- What is that, right? So I think it's 3 elements that you need to have. You need to have data centricity. It's not a file-based win. It needs to be connected and interoperable. And finally, it needs to be autonomous and intelligent. And when you have those 3 things, then you have what Ola and Burkhard and others referred to earlier today as the smart digital reality. But rather than me trying to explain it to you in words that could be a bit tricky. We have prepared a short video to give you an illustration of what could such a facility look like. And some of the elements individual, you'll see we offer today. Some of them are a bit more for the future. But yes, I'll play it, and we'll discuss it afterwards. So here, we have our facility, and it's being monitored here by lots of different sensors. And of course, in this example, we want to highlight the BLK2FLY. So we can detect anomalies from the air, could be a machine going offline or something that's in a place that shouldn't be. We obviously can cover also and detect from the ground. So here, we have our friend, the BLK ARC, patrolling the facility, also trying to detect for anomalies. And in the scenario we built here, it detects a high vibration on a pump. And by closer inspection, as you can see here, using AR technologies, the operator finds out that there's a bearing that's broke down basically in this pump. He then queries the platform, SDx, which is our data platform, thus such a bearing exist in our inventory or how do we go about to get one. In the scenario here, replacement parts are out. So he sends an order to the 3D printing machine that goes ahead and executes the order and prints a new part. Eventually, of course, the part gets delivered. We put it back into place, and our pump and our facility is back to a safe and efficient operation. So pretty cool stuff, right? So but what does that mean if you start talking technology speaker. If you look at the graph here, there's a lot of words. But if I dumb this down -- this graph down for you, I'd say it's 2 ways you can go about to start your digital twin. Either you start with a greenfield project, right, and you start designing it, hopefully using SmartPlant because then you will get a data-centric model from the beginning. But maybe more interestingly, because we know most of the industrial facilities today, some people argue up to 90% have already been built. So most of the opportunities, most of the work today is in the brownfield area because there are, according to studies, more than 11,000 plants that are in need of investment just to keep their current production level. And we know from experience in PPM that our customers make tens of thousands of changes every year, either to the physical plant or to the design. So there's a constant need to keep this twin up to date. And we do that by something we call sustaining engineering, where we connect our design tools to our SDx, which is our asset management data platform. On top of that, I'm going to talk a little bit here today about autonomous data capture, how we use those technologies that you saw from Burkhard and Thomas to basically keep the facility alive, keep it up to date. So you don't get catfish-ed basically like all Ola was talking about, right? Anyway, and then I'm going to try to tie all of this together to use cases. What's the value? What does the customer do with this? And that's what you see to the right on this graph. Obviously we're going to get into some of those. Okay. So what's our approach? If we take a bit closer look at our customers' workflow. I'm going to take you all the way from the very conceptual design throughout the construction, all the way to operations and maintenance of the facility. And we're going to highlight what the customers do, what type of technology they use and how it's connected. We won't have time today to go through every step here, but I'll highlight what I think is the most important. So when you start the very first phase is something we call conceptual design. And here, basically, the customer will simulate a thousand different ways how to build the facility, partly from a cost perspective, of course, but maybe more importantly, by designing in different ways, we can optimize the way it's going to produce and be efficient in the future. Once you found the optimal design, you send that through to the detailed design stage and start designing the facility basically. And then you obviously see the scenario where Hexagon PPM has been, as I said, a leader for decades. So once you've done that, although Hexagon has a lot of different technologies, as I'm sure you agree. There are still other documents, other graphics and other third-party sources that the customer will want to connect. And I mean it could be simple things like Excel files or PDF files or more complicated sources like third-party software. And we have many ways to programmatically connect this into the twin. And we use a process that we call where we smartify and make them intelligent, and I'd like to show you a short video on how we can go about doing that. So this is a project that we call auto tagging, where we laser scan a facility, and we basically overlaid the scans with the P&ID so the schematics, I guess, in simpler words, and we can automatically tag all different assets in the facility. And this is a huge cost saving for our customers. We know today that roughly the cost of this, the manual tagging is roughly 7x greater than the cost of the software and the scanner. So big potential. So once -- now we have built -- we have designed the facility, right? And we brought areas, hopefully, through SmartPlant materials, and then it's time to start building this facility. So then moving into our various solutions we have here, whether we're talking about SmartPlant construction for the more called heavy industrial space or SMART Build if we're building an AEC facility. We also have products like EcoSys, which measures the progress of the project and not only 1 project, it could be a portfolio of hundreds or thousands of projects. And it also predicts how likely are you that you're going to hit the budget, et cetera, et cetera. So we have a lot of solutions there. I'm also trying to illustrate here how we, again, connected back to the sensors. So we can get an updated understanding of what's going on the construction site and make sure that our projections and estimates are as correct as possible. So we've now built the facility. What happens then? Well, the customer will hand it over to another customer, an owner-operator, somebody who's going to own and operate this facility for decades. And same on this slide, as you can see, they have a bunch of different systems and steps and procedures that they go through throughout the life cycle. And we at Hexagon cover all these different steps with various offerings. And I'm going to highlight again a few. The first one we're drilling into here is, again, third-party software for the O&M space. So what you see here in this slide is the customer using SDx but he's pulling data from other software providers. Could be OSI-Soft, could be AspenTech, could be SAP. But to the user he is an SDx pulling this information. So what's key, I think, is the single source of truth and really the single pane of glass, right, which SDx provides in a role-based view. Another thing I want to highlight, I gave you a teaser in the beginning about cybersecurity. So obviously, we want to connect this as well to this platform. First, let me give you a quick crash course in cybersecurity though. I think the most important thing to note on this slide is I'm not going to talk about IT cybersecurity. It's not about protecting your laptops or your mobile phones. I'm really here talking about OT, which is operational technology, meaning all the different assets you have in your facility, and there's thousands of them, right? And the first thing we do with our software is to, in an automatic way, map an inventory of all these assets. Secondly, we do a risk and a vulnerability assessment. And then we design a plan to protect them, but also how to recover and have a backup when you get it. And that's an intentional when, right? It's not an if. You will get it. How can I know this? Well, it's just to read the newspaper every day. These attacks are unfortunately increasing exponentially. I think the latest one that was big in the headlines was, of course, the cyber attack on the Colonial Pipeline, where we, me living also in the Southeast of the U.S., were basically out of gas for roughly a week when that pipeline got under attack. So it shows the vulnerability of these systems. And it also shows that the effects could be quite dramatic. And unfortunately, sometimes tragic, right? But it's also a business opportunity to be a bit crude, right. The IT cybersecurity market, which has been there for a much longer time, is -- was estimated to be worth roughly $30 billion this year, whereas the OT cyber market, as you can see from the graph here, is estimated to be worth roughly $800 million. but it's growing fast. So if these projections are true, which we tend to believe they are, the OT cyber market will be worth as much as the IT one in the next 10 years. Another area I want to highlight here is, of course, around EAM APM, the asset management piece. Why? Well, because as I'm sure all of you are aware, we are in the process of acquiring a company called Infor EAM. And if we start with saying what do these guys do? They manage the assets. So it could be a building, a facility. It could be capital equipment. It could be a fleet of vehicles. It could be process equipment. It could be railroads. It could be a network, right, all kinds of different assets. But what they also do is they manage and connect the business processes that the customers have to those assets, it could be simple things like work management and checklists and stuff like that. But it could also be a very complicated task like procurement, supply chain, cost tracking and things like that. And the end goal here is really to get from a reactive situation to a predictive one, a preventive one. And that's where we see the more advanced customers are already today. What I also want to quickly say about the software, it's a modern UI. It's cloud-based, and it's to the majority mobile because these customers, they don't sit at a desktop working with this. They need it at their fingertip in the field. So I've talked about a lot of different assets, right, how to protect your cybersecurity, how to take care of your installed base. But what about the human assets. Because in the end, it's people in these facilities, at least for now until Burkhard robots take over. But now we have human beings in there. What can we do to help them? And we have a product called Situational Awareness. It's really a management layer product to view and visualize what's going on. And in this video here, the example is around permit to work, work management. So basically managing the different workers based on, do they have the right training? Do they have the right permit, et cetera, to do the work? And by geofencing different areas of the facility, you can manage this in real time. But it could also be more dramatic examples, right, where you've had a gas leak or some sort of hazardous material or something like that going on. One example here lately during COVID was we had some customers using this technology to split up their facility in COVID safe zones and so on. So many different use cases. To think a bit bigger picture though, right, when you have a digital twin, what does it look like? Here's a customer. They have scanned their facility using SDx also they've tagged all the information. And you can see here they can basically pick any object, any asset, any tag and find out the information about that piece. We also show here how we have integrated it with the mapping the GIS technology. So the customer can then go to another facility, which has also been scanned basically do the same thing, pick any object, pull up SDx, find out all the different documents, again, whether they're Hexagon or third-party and use this to manage their facility. So when people ask me what is the digital twin materials? I usually show them this video because I think it visualizes quite well. Finally, if you've been paying attention, you might have seen in the middle of these 2 graphs, it says digital reality information backbone. So what is that? What sits at the core of all is connecting all this information? Well, in our world, it's back to SDx. ARC Advisory Group, which is our big analyst company in our space, they estimate and say that engineers today spend roughly 30% of their time looking for information. And that is the problem that SDx is trying to tackle. The spider web, you saw there, the information map, are all the tags that are mapped in this facility. And again, everything is connected there, whether it's the design data, the laser scan, the schematics, third-party sources. In the future, we will have the cybersecurity connected as well and of course, the Infor EAM information. So this is really at the core of our strategy here in PPM. So all good, right? Fantastic technology, but are people buying it? I'm sure you guys are asking. So far, I would say not to a great extent in the industry. Gartner estimates that only 4% of companies today have something close to this of their facilities. But they also, at the same time, say that 83% are in the process of creating a digital twin within the next 3 years. So I think it's safe to say that we believe it's coming and increasing. So what's been holding the industry back? If you've been listening to my presentations before, you probably heard me tell a similar story 3, 4 years ago. And we can talk about technical challenges or security challenges. But I think all of those, we are solving faster and faster, and the technology is certainly there. I think that the real problem, if you dumb it down is our own human ability to change. But we as humans tend to think that what we do today is good for tomorrow, but rather than alter the process completely. So why do I think it will change now? Why will it go faster this time? Well, I think it's really a case about survival. If you go back 30 years and you look at the S&P 500, the list of companies there, 52% of them don't exist today. And the average life expectancy of a company keeps shrinking. So if that trend continues, 1/3 of today's companies will be gone in the next 10 years. So I think -- that in itself is a stark reminder that company cannot survive without constantly reinventing itself. But even more dramatic than just a company survival, I think it's really about all of us, humanity. We are burning through the margin of error. Studies show that only 40% of inputs are converted into outputs. And we are, in fact, using the resources of 2 earths, it's not sustainable, right? So unless you tell me that we have another planet, I think the only solution to the problem is to be at least twice as good. We need to cut weight by 50%. We need to double productivity. We need to double efficiency. And I think this is what we can do with the help of Hexagon and all our technologies. If we put data to work quickly at scale across the enterprise. And we are committed to do that, help our customers overcome the barriers and finally kill the status quo, and create a smart digital reality for the facilities of the future. Thank you very much for paying attention. And with that, I'd like to invite my good friend, Paolo to take the next section.

Thank you very much. Thank you. Well done. Hello, everyone. My name is Paolo Guglielmini, and I run Manufacturing Intelligence, the division of Hexagon that is dedicated to discrete manufacturing. Over the next 20 minutes or so, I would like to spend a few thoughts on the adoption of smart manufacturing technologies in these target industry of ours first and then really talk about how Hexagon is going to play a decisive role in making sure that we can take these industries to the next level of productivity. So first of all, I want to go back to what Ola described earlier in his presentation, and it is really the gap in terms of digitization between some of the consumer industries and discrete manufacturing in particular. If we look at a typical sort of process of adoption for digitization technology, what ideally should look like. First, we want to be well connected to sensors, machines, the real-world assets and to the software stack regardless of where that data sits, we would like to connect seamlessly to that data. And first of all, connectivity is going to take us to the next level of visibility accuracy. We've talked about 30% of people spending their time researching information rather than doing something about it. Well, we want to make that process smoother. Then we enter into a phase in which advanced analytics helps decision-making. And they make these processes more predictive. We get to a point after knowledge capture that those processes almost become self-learning, self-aware until we drive towards full autonomy. The level of adoption of these technologies in discrete manufacturing is very dishomogeneous. So to try and know more about it, we have spent a lot of time researching not only our customer base but also tens and tens and tens of customers in different industries and regions that don't necessarily work with Hexagon today to really try and understand what these bottlenecks truly are, where are they? And we have clearly identified 3 types of patterns when it comes to customer groups and their dedication, their investments to smart manufacturing. So we've identified what we would call the pioneers, the embracer. So companies that are really forward leaning, companies that have deployed capital, and they have approached smart manufacturing across their supply chain, across the ecosystems, across their production lines, and they're really trying to have a more holistic view when it comes to digitization in particular. Well, of course, we're talking about automotive, aerospace and defense in that category. The reality is that the forward leaning sort of business leaders within those industries are in the light blue box that we see on the top right. I would say a lot of the OEMs and the Tier 1s that we talk to today, probably are in the dark blue category. So what we would call the followers or companies that are very well aware about the potential that sits with digitization, but probably they want to take a more step-by-step approach to rolling out these technologies. And the obstacles can certainly be in the level of knowledge that we have internally about those technologies, but also there could be regulatory sort of obstacle that kind of challenge the speed of adoption. Or simply, we want to take a more measured approach. So we take fully digitized processes when we launch new products, new programs when we design new platforms. And we want to take a more careful well-thought-out approach when it comes to existing processes to not disrupt them. Last but not least, we see a substantial portion of our actual and target customer base, and what we would call the traditional lists. So companies that are either challenged for lack of know-how or constrained in terms of CapEx or simply they want to see more clearly how tools that are -- or are not available in the industry might generate a concrete, measurable return on investment for them. The reality is that a lot of digital transformation technologies today have been designed for sort of OEMs and large complex sort of organizations that might be more difficult to adopt when it comes to players that are sitting deeper in that supply chain. So what Hexagon is going to do about it? Well, so first of all, we need to be kind of laser-focused on the why. I think every time that we attack one of these solutions for development or deployment with customers, we want as well as our customer be laser-focused on the why, the return on investment. The #1 reason why companies today go through a journey of embracing smart manufacturing is the competitiveness in the front end, in their marketplace. They want to be as responsive as possible to the needs and the changing needs of their customer base, and they want their time to response to shrink. The bottleneck to achieving that is quality typically. So how can we deliver that flexibility? How can we help customers develop more sustainable products, reducing their cost footprint, reducing the materials footprint, making the products more circular sort of economy friendly? Last but not least, it's about faster time to market, and it's about the labor content, whether that's the cost that is implied with labor or whether that's the availability or nonavailability of skills today and for the future. I would say that all of this is contributing to a very dishomogeneous sort of adoption of smart manufacturing in our target markets. What we want to do is to be able to cater for all of these needs and take our customer on a journey at their speed. What I would like to do today is really talk about 3 examples of smart digital realities, landing in the market of discrete manufacturing. First of all, we're going to talk about a use case in machining. We have today actually medical and others. And for a lot of these people, really, it's about adopting a solution that is tailored to their specific needs to make machining more productive. Second, we're going to focus on example of smart digital reality that is a little bit wider in spectrum. A problem, mining design, all the way to planning and engineering, all the way to machining, manufacturing and verification. So we want to start to broaden the spectrum and work towards increasingly an end-to-end solution, which finally we're going to discuss in our third use case from the world of renewable energies in which we also influence and optimize the way that they function in field. First use case is from the world of shop floors. Why is this important? We know that there's a long tail of factories in the world of discrete manufacturing today. The vast majority of those, more than 19 machining shop to be competitive in their own right, with a limited amount of resources, so how can we go about helping them. We also know that a lot of these shop floors are challenged in terms of competitiveness and profitability. There have been studies by Deloitte, Gartner and others about the timing that it takes to fulfill an open position in some of these machine shops today in the past and in the future. And we know that, that timing is going to grow wider. It's going to go longer. We know that some of these skills will miss certainly past 2025, but not way long past after. So that means that companies need to start to plan for it already today. Why is this a business opportunity for us? Because we are in that market already today. There are a lot of our point solutions that supply these machining shop floors already today with solutions for the world of production, production planning, for the world of free dimensional verification. So how can we tie these technologies together to deliver the next level of productivity? So let's assume that I was a, let's say, a Tier 2 supplier. I own a machine shop or I run manufacturing in a production facility. I have multiple production lines and manufacturing cells. I'm trying to achieve 2 goals. I want those manufacturing facilities to be as effective as possible. So maximum level of uptime and productivity and return on assets on my shop floor. But second, I also want to limit the level of waste and inefficiency that is involved with dealing with my supply chain, vetting incoming inspection, dealing with my customers on the front end. So I want to make sure that I maximize everything that happens within my walls and in my ecosystems. The reality is that if I am in charge of my manufacturing operations, I know that this is pretty much what's happening today in my shop floor. We spent overwhelmingly more time in tasks that are involved with costing, bidding, analyzing, planning machining operations rather than executing them. We want those components to have excellent quality. And therefore, we spend just as much time for inspection planning and setting up a measurement routine rather than actually verifying those qualities and doing something about the lack of quality. All right. What are we doing about it? Well, at Hexagon, we are deploying 2 types of technology predominantly to make sure that machining planning moves to the next level of efficiency, deploying digital twins, and that verification, metrology inspection moves to the next level of autonomy using artificial intelligence. So first of all, we have announced the acquisition months ago of a company called DPT Technology (sic) [ D.P. Technology ]. DPT Technology has the leading machining technology in the marketplace today. And what they have done is to release to the market last year a digital twin-enabled version of their manufacturing technologies that really makes CAM easily integratable to any machine type. So suddenly, we're going to have way more flexibility when it comes to moving machining of parts from machine to machine. And we take really stock of the physical performance, the physical properties of that specific tool. So that really enables the next level of productivity. When it comes to metrology, which, of course, is still our core business today, and this is where we have a leading position, and we're taking on the responsibility of moving the industry to the next level of development, we're using machine learning techniques to capture the experience of our own application engineers and define autonomously planning routines. So the customers are going to be able to plan for their metrology tasks quasi-autonomously already today and even more in the future. Now if we want to see those timers shrink even further and move completely to autonomously, this is where we have to really establish feedback loops in between the machining and the verification. What I'm talking about right here is either being accepted in the market or just launched or about to be launched in the first half of next year. So we are talking about commercial opportunities that we're going to be able to exploit in a very short time frame. Still I'm stuck with the problem of our teams spending a lot of time to satisfy customers, vetting design, tweaking design, making sure that those theoretical models are manufacturable. And then I spend a lot of time making sure that I collaborate along the supply chain. Possibly, I have multiple production sites that need to align and collaborate. But at Hexagon, we have building blocks that we can deploy and really tailor to the needs of the shop floor. We're going to do it working with the Infor EAM team once the acquisition is going to be sort of officialized and concluded. We're going to take their platform and really configure it to the need of the shop floors to develop a purpose-built asset management solution. And then we're going to use HxGN Connect that has been released to the market. It's a fully cloud SaaS-enabled solution, and we're going to make sure that people that operate in this supply chain can really collaborate and work together more effectively. So if we abstract from the world of machining and we start to encompass design. So we're going to look at a process that we want to cover from concept to design, from simulation all the way to actually delivering those components. The example that we have picked here is an example from the world of additive, and we could have talked about many other processes. In reality, every time that in an industry, we have an adoption, we have a new trend, we have a new type of material, we have a sense of urgency that drives these companies to change their processes, that's the perfect opportunity to deploy smart digital reality. When these processes are not fully stable, stabilized and known, this is really when you want to have not a plain digital twin, but a digital twin that is empowered and enriched by real-world data, by the single source of truth that sits with knowing what actually the output of the manufacturing process is. When it comes to additive, we all expect spectacular growth from additive in the future, but the reality is that a lot of the companies that want to deploy additive suffer from lack of knowledge. A lot of those companies are deploying additive components mostly in prototyping for repair, for maintenance, repair and overall services or in R&D, not quite yet in production. And that's because those processes often are not as cost-effective and reliable as we would like them to be. Today, we are already in this market. A lot of our customers use our point solutions from design to manufacturing and verification. We offered to the marketplace solutions that are best-in-class when it comes to generative design, when it comes to simulation of the process, when it comes to early-stage costing. We produce great tools when it comes to CAM for additive, and we can follow that printing process and really capture those components at the end of it through verification, reverse engineering and computer tomography. But there's more than we need to do. So we have started to release to the marketplace a workflow automation solution that starts to tie these disciplines and applications together. I'm convinced that the next level of productivity is going to be reached when users are going to be able to iteratively improve the quality of their models and their engineering choices by virtue of knowing if current choices are successful or not, if current methods are successful or not. And this is really what a digital twin empower by real-world data can look like. What are the benefits of this? Less material. Think of lightweighting in a multiplicity of industries, we want to use additive because it's highly organic in terms of the shapes that we obtain. But of course, we want to shrink, reduce the cost that is associated with materials. We want to reduce the energy that is involved with a lot of these 3D printing processes. When we talk about consumer applications, this is really processes in the order of magnitude of minutes. When we talk about hours implied with industrial processes, there’s a lot of energy that is engaged right there. Of course, we want to obtain cheaper prototyping. The return on investment is going to be measured in time to market. And of course, in reliability. We have scrap rates in the world of additive that are exceedingly way too high that we can work on. How and what does our sort of workflow automation solution looks like? What you're going to see on your screen right now is a full process that is starting with generative design. So this is the time at which we decide what is the environment that we have available, what are the connecting pieces for -- what are the connecting elements for those components. We optimize the choice of material. We probably simulate and we try to reduce, staying within the structural requirements of those components. Then we've had to design, and we help manufacturers print those components. So we turn a piece of design into G-code 3D printers can act on. Once the components are built through our computer tomography technologies, we know everything about what they look like, in terms of 3 dimensional properties, in terms of cracks possibly, porosity, inclusions, which naturally will happen in a 3D printing processes. The possibilities that we had at the end of the process is really to apply simulation and once again be able to tell whether those imperfections will be a problem or not while we use those components. And by the way, this is a strategy that we have adopted more generally for our design and engineering portfolio, in which we try and use simulation outside of the analyst communities and really use it for manufacturing properties. Let's move on to the third example. If we talk about renewables and wind, we know the wind has developed tremendously in terms of uptime, but we also know that the cost that is involved today with downtime implied particularly by mechanical components is extremely costly. It's extremely high. I believe 60% today of maintenance spend is consumed by unplanned maintenance jobs. So we have an industry that is highly reliant on the quality of mechanical components that is going to go through a tremendous rate of growth. And this is an industry in which Hexagon is extremely active already today. I believe we design, in the R&D department, 7 out of 10 of the largest turbines that are in the world already today through the technology of ROMAX. Based out of Nottingham, ROMAX has been acquired 1 year ago, extremely active, both in e-mobility and drivetrain design applied to win. Since a very long time, we are active in the world of verification for gearboxes and fan blades. And of course, then we tend to see those components during a planned maintenance phase where we want to measure if that -- if those geometries have changed after a certain number of cycles. What else can we do for this industry? How can we connect the dots of our solutions? And last but not least, really attack probably the most important source of savings and return on investment for owner operators and for wind turbine manufacturers. Well, we want to do that by following those components in field. So again, we will work with the enterprise asset management platform that we have just announced, that is best-in-class in its field and use the knowhow that we have about the industry, about the physics properties of those components, about the measured properties of those actually manufactured pieces, and then use portions of the [ Xalt ] sort of analytics capabilities to develop a highly efficient asset performance management solution. Great. So we’ve looked at these 3 case studies in the world of discrete manufacturing for machining, for additive and for wind. Why do we think that we’re perfectly positioned when it comes to the digital transformation needs in the world of discrete? It is because we have foundational technologies that really support customers on an end-to-end fashion. It’s because we have market reach, domain knowledge that is indispensable when you want to take your customers to the next level of productivity. And it’s because we are highly committed to this solution strategy and to really create new opportunities in delivering tangible value to our customers throughout the supply chain. Thank you very much. And I believe we’re going to move now to the Q&A.

[Audio Gap] areas of growth. When we think in terms of sort of macro in terms of industry trends. If we think of 5G on the bottlenecks to adoption of 5G, it is material technology. It is injection molding. Is the choice of the right material mix to make sure that those smartphones, it's more broad usage of simulation that can be made within manufacturing. So we want simulation to become not a virtual verification tool, but really a part [ performance ] prediction tool for the future.

Thanks. And another one for Paolo. Do you [Audio Gap] across design and engineering production metrology and service life.

Yes, absolutely. Plenty of those.

You can't mention any names, no?

I don't think I can. But I think what something I think is very important to understand, when we talk about these solutions strategy, of course, we are very interested in the processes and the technologies and how we're going to pull off this strategy. We need to think of it in terms of cross-selling. In a lot of these customers today, we deploy 1 or 2 point solutions. The fact of connecting these solutions seamlessly, delivering the next level of ROI is going to be the #1 reason why we're going to be able to [Audio Gap] customers to grow for the future.

Great. And this is for Mattias. What are the professional services and support requirements from customers in order to adopt and deploy your OT and asset life cycle vision?

Yes. Well, I would say I wish we could put requirement. I would say like this. The question is very good, right? I mean it's not just technology. Like I said, it's the human inability to change. So you definitely need a lot of services and handholding to do this kind of change. And we, at Hexagon, we provide professional service, right, the technological services. That, we do very well. But call it [Audio Gap] a lot of cases, we will partner with one of the big consulting companies to basically help us.

Great. So I think we'll take 1 last question. It actually is 2 questions that I'm going to combine. So how are you addressing the structural headwinds coming from the oil and gas industry? You can answer that.

Yes. I can maybe start with oil and gas. Yes, I mean it is true that we have and have had a rather large exposure to oil and gas, and we still do. But it's significantly less than it was 5 years ago. We've had a very dedicated strategy to diversify through or move into the owner-operator space. So we've done a lot internally, but I would say also we ride kind of on the journey of our customers. I mean our customers are themselves diversifying. A big company that, without mentioning any names, that might have built an oil rig in the past, they're now building for technology, right? So I think we're doing it ourselves, but we're also riding on the wave of the customer. And what's the second part of the question?

How are you addressing the opportunities within renewables, so.

Right Yes, I can take a stab at that one. I mean I can only say that we see a lot of opportunities in all of the areas of storage perspective. I mean we -- the beauty of the portfolio that we are building is that certainly comes with the knowledge that is involved with both the design and the manufacturing of components that are associated to sort of renewables. So yes, we work daily to strengthen sort of our understand [Audio Gap] storage hydrogen models across, of course, solar and wind that we just mentioned. I think it's also very important that, as a group, we are committed to making investments in some of these innovative energy sources because there's nothing better than using customers on the back end of your own sort of experience [Audio Gap] ROI. We truly know what that means, and that's part of the work that we're doing with our evolution and our investments there.

Great. Thanks. And now we'll go to a short break.

Okay. Thank you. [Break]

So welcome back, everyone. I'm Steven Cost, President of Hexagon’s Safety and Infrastructure. This segment will be about the sustainable society. Presenting along with me will Kalyn Sims, the CTO of Safety and Infrastructure; as well as Michael Ritter, President of Autonomy & Positioning of Hexagon. So it's been 20 years since 9/11 and safety and resiliency and all of that really came into crisp focus that day. And as Mattias talked about sometimes out of the ashes and out crisis comes change and 9/11 really was the catalyst for many safety and security policies. New York City adopted a new antiterrorism strategy, the New York Police Department, one of our large customers, deployed hundreds of cameras and sensors in lower Manhattan and spent millions and millions of dollars in search of real-time situational awareness. And out of this search for a smart city really came the concept of a smart city, from a safe city to a smart city. New York City’s former Director of Innovation, Jeff Merritt, said that the system that they built for public safety looking for the safe city really helped many other organizations move and gave rise to the concept of a smart city. Merritt also said that the adoption happened at a speed that otherwise would not have occurred in a normal environment. And so out of crisis, money was spent, funding happened and people were forced to make dramatic change. So where does that leave us today? Well, today, cities are facing another time of challenge and it’s that of the growth of cities. According to the UN, cities will grow over 2.5 billion people over the next 3 decades. More people in cities put a lot of stress on some infrastructure that’s been around for quite a while. It impacts policing, land use, power grids and the environment. And just like in New York City, 20 years ago, city leaders are turning to technology to deal with these problems. And we're putting Hexagon's innovation and experience to work every day to help solve the biggest challenges through autonomy by helping cities do 3 things: detect, analyze and act with greater effectiveness. And so for cities to became smart cities, they have several hurdles that are in front of them today and let’s take a look at some of those. The first one is siloed organizations. Cities as a whole rely on diverse organizations to deliver services from governmental organizations to businesses and to nongovernment organizations. And unfortunately, in many cases, cities work in silos and the people and the data and the processes can be very disconnected. And this lack collaboration leads to poor performance and really can threaten safety and security. Hexagon is enabling citywide collaboration with a new product called HxGN Connect. Kalyn's going to talk about it and show a demonstration of it just in a minute. The second thing is the data deluge. Smart cities are deploying censors and cameras to collect all of this data from social media post to streaming video, the data that's inbound can be overwhelming. Hexagon has the industry's first assistive AI technology to help public safety agencies. It's called HxGN OnCall, and it provides dispatch, records event management and analytics, all with assistive AI built in. Coupled with that, we’ve talked about a lot today is Hexagon’s 3D surveillance systems that are really revolutionizing how incidents are detected. The Leica BLK247 is a smart 3D surveillance system that uses edge computing and AI to autonomously detect and report possible threats. Next is data ownership. It also creates a lot of challenges in today’s environment with all the privacy considerations. Take for example police records. Much of that information is private and can't be shared with other organizations. Another one is health records. But in an event, in an emergency, a lot of information needs to be shared across these agencies and organizations. And the other thing is internal politics, which also prevent data sharing in many cases. This brings us back to HxGN Connect that will allow data collaboration on an as needed basis and you can share parts of the information, redact some of it and really allow the data to be shared while really retaining ownership of the sensitive information. Mattias talked about cybercrime, talked a little different about cybercrime. This is a big challenge for cities. In 2018, Atlanta, Georgia, Atlanta was attacked with a ransomware and for a week police had to use paper reports to process things. The archived video that they had, just terabytes of information was completely lost. The same thing also happened in New Orleans just last year. And so we're helping with Hexagon Solutions to help manage this disruption. And many customers have now begun to move to the cloud to really take advantage of the security. According to Gartner, the government trails the private sector in cloud adoption and the failure in government adoption of the cloud when they attempted is 3x that of the industry average. Much of that is the unwillingness to change and to stay in the old ways in the workflows. But the benefits of moving to the cloud are immeasurable, right? Expanding to Software-as-a-Service ensures your systems are up to date and with update security fixes keeps cybercrime at bay as much as possible. At Hexagon, we’ve moved many of our mission-critical solutions to the cloud. New Orleans, which I mentioned earlier, has selected HxGN OnCall records for their new system. And HxGN Connect, we talked about it. It's cloud native, hosted in Microsoft Azure to take full advantage of all the cloud security and scalability. Well, data collection is important but taking that information, taking that data and turning it into meaningful information, it really has a growing need for us to create this digital version of the city that mirrors the physical one. 3D views of location data, coupled with real-time information needs, cities can create dynamic digital twins. Our HxDR solution that you can see here can seamlessly take in and visualize any type of reality capture data and moving that along with M.App Enterprise and Luciad. You can also monitor city assets and moving objects to understand patterns and visualize these results in 2 and 3D. And so we're making digital twins a reality within the cities as well and giving decision-makers a virtual city at their fingertips. So where does that lead us? Well, cities are faced with many challenges and they can increase autonomous operation and provide better services. And this ultimately gives you a safe, connected and sustainable environment. Beginning back in 9/11 and keeping citizens safe and secure is foundational to a smart city, but safety also includes the reliability of the critical infrastructure. For connectivity, services and departments must collaborate. They need this connected information. Cities also need to support citywide sustainability to manage the critical infrastructure, the services and the resources. So how does Hexagon successfully make this digital transformation? Well, Hexagon is empowering the autonomous capabilities that enable safe, sustainable and connected cities. A smart city ultimately is an ecosystem of technologies, data and capabilities and the technologies that we have are key: assistive AI, data connectivity, the digital twin, real-time location intelligence and cloud deployment. Ultimately fusing IoT with 3D increases the situational awareness, pairing AI with real-time analytics improves the decision and support and deploying cloud-based collaboration helps organizations work together. And at Hexagon, we're delivering these capabilities through our more key products: HxGN OnCall, the BLK247, HxGN Connect, M.App Enterprise, Luciad and HxDR. I'd like to ask Kalyn Sims, the Safety and Infrastructure CTO, to come up and give some examples and show some situational cases. Kalyn?

Thank you, Steven, and welcome, everybody. So ensuring effective response to an emergency is absolutely fundamental to a safe city. Call takers and dispatchers must quickly collect all relevant information and then immediately dispatch the right resources. To ensure officer and citizen safety, first responders need to receive accurate details about the people, the places and the incidents before they actually arrive on scene. They need the right tools and capabilities at their fingertips to manage these high stress situations. Our OnCall solutions meet all these needs, supporting faster, more coordinated response to public safety incidents. Let's take a look at a scenario that begins at an emergency operations center, a call comes into the center and a caller reports that a driver has collided with a gas meter near an apartment building. Several minutes go by and then a second call comes in to yet a different call taker, and they're reporting a strong smell of natural gas at another location. Seconds later, a third call comes in to a different call taker. This caller is reporting hearing an explosion and seeing smoke. For each of these calls, different call takers receive and enter the information into computer-aided dispatch system, or CAD. They independently assess the situation and determine the proper response for the specific incident reported directly to them. Ideally, the call takers would determine these incidents are linked. But they're operating in real time, and they do not have the luxury to stop, compare notes with other call takers, analyze the incident. This is where HxGN OnCall CAD is different. Our systems' superior capabilities, integrated workflows and intuitive user experience already provide dispatchers with built-in advantages. But OnCall's assisted AI, which Steven talked about, is what really transforms this scenario. With OnCall real-time assistive AI is continuously working in the background. So in this scenario as soon as information is entered into the CAD by the dispatchers, the assistive AI analyzes the data and automatically issues an alert to the operation center supervisor, letting her know there's a very high likelihood that these 3 events are in fact related. So thanks to the help of assistive AI, the supervisor is able to quickly recognize the car accident led to a dangerous gas leak. And she knows this situation could rapidly escalate. So she initiates the appropriate coordinated response. Now typically, this type of response involves one or more emergency services: police, fire, EMS. But imagine having the ability to bring together information and people from different organizations across a city to truly collaborate. The future of smart cities is in connected data communities, enabling users to work with diverse people and information regardless of their organizations and regardless of the operational systems they use within their organizations. For connected cities, we offer true citywide collaboration in the cloud with HxGN Connect. The use cases for HxGN Connect are vast and diverse. I mean they come -- new ones come across my desk daily. And I’ll go through a few examples. Regional operation centers can use HxGN Connect to coordinate response to an emergency that requires multiple police departments like in the case of a police vehicle pursuit that's crossing across jurisdictional boundaries. Real-time crime centers can use HxGN Connect to gather actionable intelligence from multiple disparate data sources. Steven spoke about the day-to-day [ leash ]. Using this intelligence, analyst can coordinate a response to incidents as they’re unfolding in real time, such as in the case of a child abduction. Additionally, with access to such a rich array of data, these analysts can also identify potential threats and hopefully prevent tragedies from occurring in the first place. Cities planning a major event like a festival or a parade can use HxGN Connect to collaborate between city government, public safety, street vendors, bus companies, all kinds of agencies, security agencies, and this can occur before the event for planning, during the event for situation awareness and after the event to debrief. Utility companies, another great use case. They can use Connect to link together all their various systems, devices and centers to provide a single view of their current operations. Department of Transportation can implement advanced traffic management systems using Connect as the underlying platform. So I could go on, but I won't. So let's pick up from the previous scenario to give you an example of Connect's versatility. So in addition to dispatching the emergency services, the supervisor now knows she needs to coordinate action with other city agencies like the Department of Transportation and the local utility company. Within Connect, these different organizations are already connected, and additional organizations can join on demand. They can be at it with little effort to Connect by simply subscribing to Connect as a service in the cloud. So in this scenario, the supervisor sees sensor alert in Connect indicating a drop in gas pressure from one of the city's main gas lines. The alerts are tied to the same general vicinity as those calls for service that were coming in, in the beginning of this scenario. Using Connect, the supervisor pulls live traffic video to get eyes on the situation. She sees traffic jams developing in multiple areas of the city. Immediately, the supervisor create what’s called a working channel in Connect such as a Facebook group. And this includes leaders from public safety, the gas utility, the transportation department, hazmat, alerting them of the possible gas leak. And within this group channel, action can now easily be coordinated in real time with all respective parties. As a result, the hazmat team arrives and secures the scene, evacuating residents from their homes. EMS, first responders transport multiple victims to hospitals. They can even view hospital bed availability and trauma centers directly on the Connect map, saving them precious moments from having to make phone calls around to the hospitals. The transportation department creates detours around the scene of the accident and the explosion. These road closures are all shown on the map, again, so all participating responders can see them. Then an alert from a Leica BLK247 surveillance camera shows up on the Connect map, indicating that a perimeter set up by the police has been violated and it's surrounding the scene of the explosion. So the CAD supervisor knows she sees the alert and dispatches the police to the scene. The utility company generates a work order and dispatches the most appropriate field crew who use the EAM mobile app to get their work order and go on scene. The locations of the responding crews, again, are displayed on the Connect map informing all organizations that the utility company is on-site addressing the problem. Once the gas supply is stopped, all organizations are notified in Connect. The field crews at the scene of the explosion continue to work. They use their Infor EAM to understand the condition of assets in the building. They determine a recently replaced valve could have caused a leak resulting in the explosion. This assessment, again, is posted in the Connect channel. So hopefully, you can see the scenario shows the real power of HxGN Connect and collaborative organizations can bring to a city. So in addition to safety and connectivity, sustainability is key to ensuring the city's future. Sustainability is a big topic in smart cities. You've heard my colleagues already talking about it this afternoon and it plays a role in all aspects of a city’s health. At Hexagon, we believe our products and solutions play an important part in ensuring sustainable outcomes. Today, I'm going to be focusing on sustainability and transportation within the city. So consider the following. Enhancing the air quality in any city can play a major role in improving life for all citizens. Thankfully, there's been a tremendous leap forward in air quality [ scent team ] for smart cities. It’s also possible to better monitor energy and resource use, consumption and waste which can provide critical insights for developing sustainability policies. Smart parking is gaining traction worldwide. It enables tracking and monitoring of parking spots and garages and on streets, and it also helps reduce traffic and pollution and provides a much better citizen experience. I think we can all attest to that. Better transportation monitoring and alternative mobility options are also transforming city infrastructure and fleets. Smart city transportation is all about fully optimizing the movement of people. To support sustainable cities, we deliver dynamic 3D digital twins that fuse the real and the digital worlds, providing a real-time location intelligence and better resource planning and management. So let's take a look at an example from the city of Munich. The goal of this project is to optimize mobility and reduce the overall carbon footprint through micro mobility. According to a recent McKinsey report, car-based mobility dominates Munich as it does in many of our cities. Cars account for 50% to 60% of all kilometers traveled and more than 3/5 of those are by private car. The city's excellent public safety transport system handles 30% to 40% with walking and biking making up the remainder. However, micro mobility is gaining traction. In fact, McKinsey estimates micro mobility trips will represent 8% to 10% of all trips in Munich by 2030. And if Munich were to invest in more micro mobility infrastructure, this number could jump to 15%. To support this vision, Munich’s Department of Mobility has deployed a smart monitoring system to better manage micro mobility providers and to understand the impacts of shared mobility services in the city. The first of its kind in Germany, the SaaS solution can track, visualize and analyze IoT data from e-scooters, bikes and cars, all from different providers. It can also analyze commonly traveled routes, giving planners the information needed to implement roadway safety features. The solution is powered by M.App Enterprise, which aggregates, visualizes and analyzes the data. And Hexagon's Luciad product supports the 3D visualization within the system, including city meshes from Hexagon's innovative HxDR application. The solution delivers a dynamic 3D digital twin in the city and its micro mobility. It allows transportation planners to fuse the real and digital worlds and receive constant updates. With this smart monitoring system in place, the city can guide future mobility strategies, all based on data. Of course, cities are not divorced from the larger ecosystems in which they operate. Cities are parts of regions and nations, and the need for safety, connectivity and sustainability do not stop at the border. The networks that connect people, organizations, infrastructure and digital assets continue well beyond the city limits. Cloud native solutions like HxGN Connect and HxDR provide the collaboration and digital twins across any landscape and locale. Hexagon is providing autonomy within a city. And we're also powering the autonomous solutions that feed cities literally. So with that, I'm going to hand it over to Michael Ritter.

Thanks, Kalyn.

Thank you.

Good afternoon. I'm Michael Ritter, I head up the Autonomy & Positioning division in Hexagon. And if there's one thing you can take home today, that is you can actually make money with autonomous mobility today. You don't have to rack up hundreds of millions of cost and not make money. If you look at the technical foundation for sustainability, autonomy plays a big role. Everybody knows this, and I will go through an example where sustainability will almost not be possible with autonomy and as well our history is in precise positioning, navigation and timing. And positioning and timing supports not only autonomous mobility because you really need to know where you are if you want to be autonomous and you need to know where you're going. But a lot of infrastructure needed in the future for sustainable cities like 5G networks, like banking systems and other things would not work without precise positioning and timing technology. So it supports sustainability directly but as well it supports autonomy, and then autonomy supports sustainability. So like in everything we do, at the moment, we start small. So more and more new infrastructure is put in place, more and more autonomous solutions are rolled out in the mobility space. And the environmental impact is maybe relatively small today, but on one example I will show that in a few years, the environmental impact is tremendous, if we deploy these solutions today. In our part of Hexagon, we operate in all kinds of different markets that support autonomous mobility, on-road mobility, trucking and the last mile like robotaxis. But today, I want to move your attention a little bit to off-road autonomy, something that you read very rarely about on the press. And today, especially as an example in agriculture. But we have a lot of work in the mining space, in the marine space and around material logistics of airports. But if we go to agriculture, agriculture becomes more and more important. The world is growing really fast. We need to feed the people, but we have to do it in a more sustainable way. One way, we've gotten very productive. And agriculture was to use a lot of chemicals, use a lot of fuel, use a lot of labor, and that's something that's not sustainable. So if we want to go and be sustainable, we need to employ more intelligent solutions. We need to reduce the chemicals we use. We need to reduce the water we use versus kind of the scarcest commodity in the world these days. We need to prevent erosion of soil. And we need, of course, to make sure that we don't need a tremendous amount of labor for this because, really, nobody wants to work in agriculture any longer. So we have a long tradition of supplying position technology to the agricultural industry. And over the last 3.5 years, we have invested heavily into the perception component. Very similar to what you saw earlier this morning, but in perception in -- like, for example, agriculture, what we need to do is we not only need to identify the objects, we need to as well predict what they're going to do. Is this dog running in front of my tractor? Is this person that's having a little break at the side of a field, is he going to get up and walk into my tractor? And we have, of course, 2 things like distinguish between. That's a crop I want to grow. And now this is a weed I don't really like. So those are the kind of things and perception that we work on and combine them with the precise positioning to have a good solution for our customers that build farm equipment. Why is this a good thing? That's something I want to go through a little example here where we use a little bit of precision and autonomy because we can't afford the labor get to a very good or better use of our resources. So let's assume we have a blank slate. In reality agriculture is cyclic, but now it's fall or autumn in parts of the world. We start with a clean slate. But we know next spring, we want to plant corn. So in an old traditional way, what we have done, we would have fertilized our field today, the entire field. But with modern technology, what we're going to do is we're going to plant corn in spring. Hey, it grows best when we have it at 30-inch spacing. So we actually bring down fertilizer today, but only there where we're going to plant corn in the future, so in a small row and not a broad application. So when we come back in spring, we plant our corn because we know exactly where we fertilized, we planted exactly where we fertilized. So now spring is going. The plants are growing. And in a traditional world, we would now go back many times and apply pesticides and herbicides and drive this field 6, 7 times. But if we use a little bit of intelligence, we can use the perception to identify where is the weed where is no weed, and then we can go and apply a little bit. Or if you are in the organic production, we can use a mechanical reading device or ultraviolet light or fire, there are different methodologies to only eliminate that one piece of weed. And we get through our spring and growing season. Now it comes fall -- okay. Now is fall, and we harvest our crop. Because we want to be more sustainable. What we actually do is we let the corn stalk stand. We're no longer plowing or tilling our field. If we don't do this, we don't lose as much water, we don't have as much soil erosion. And because the stalks are still there and the roots are still there, the soil is protected. But we want to protect our soil more and we want to improve our soil more, create more organic matter. So what we do is we plant what's called a cover crop. We plant serial rye. And now if you notice, we have our corn stalks already still in the field. Now we need to go and plant the serial rye that grows best if it's roughly 7.5 inches space, have to go and plant that, get really precise. So over the winter, the cover crop grows, it covers the field. We don't have erosion, we retain a lot more water because it doesn't vaporize as much. And we protect the ground from sunlight basically and the weeds don't have a chance to grow. So next year, we don't have to go and apply hopefully, any chemicals to our weeds. But now, of course, comes our production. We want to plant soybeans this year. We want to make sure that we use the nutrients in the soil right and not plant the same crop twice in a row. So we do want to plant soybeans. Now we have to go and hit, even though the field is covered with rye, we have to go and now space our soybean seeds right in the middle for proper growth between the rye we already planted, but we can't see where the roots are. So again, we need the precise position to steer our tractor to go and exactly plant the soy right where we want it. So we already know we saved fertilizer, we saved herbicides, we saved pesticides. There is a lot more complicated crop rotations to do for today, but we can look at fuel. Just by being more effective on how we work with the farm equipment on the field, we estimate with generally published formulas by academia that the Hexagon equipment already in the field today roughly saves 190 million liters of diesel fuel a year, and we're saving roughly half million tonne of CO2 because there's not that much equipment in the field. But if you look 10 years ahead, just looking at fuel again and just looking at those solutions, we expect that we will be saving 4 million tonnes of CO2 in the year 2030. That's the emission of 1 million cars on the roads or the total emission of the city of Stockholm. So yes, we start small. We have a small impact today. But only in 10 years' time, we have a tremendous impact with just one part of such an autonomous mobility solution in agriculture. But that's not all. Tractors will be used. And if you are in Australia, in Canada or in North America, where fields are really, really large, large autonomous tractors will always be used. But in other parts of the world, we will use very small autonomous machines, specialized machines. Those are a little bit in earlier stage in development. Semiautonomous tractors exist for at least 10 years, they are mainstream for 2, 3 years. But now there's other stuff that needs to get developed, robots for vertical farming, for example. Other applications for drones, not just to survey buildings and make a good 3D model of it, but to go and fly over fields and detect differences in crop grows and deal with it accordingly or differences in wheat grows and deal with us and all these things that need to get developed. So every year over the next 15 years, new solutions will enter the agricultural market. Why would the agricultural market adapt those? Because there's 2 big problems. Nobody wants to work in agriculture and the world needs to get fed. So the reluctance we had earlier in some industries about adopting these new technologies is kind of taken care of for us by those 2 really urgent needs in agriculture. So why do we think that we are best positioned in this market. We are really good in Hexagon in sensor fusion. You heard already about part of it this morning, but we really know how to take satellite signals, how to take inertial systems, how to take LiDAR, radar, cameras, how to put them all together and make a very robust and very, very fast solution. Because if you run a big machine like that tractor on the picture, by the way, that tractors tire is taller than I am. If you run that, you have only split seconds to make all of your decision because you don't want any accidents. So we are really good at this. We have the engineering for this, and we are very good in sensor fusion. We do that for a lot of applications. The other thing is everything if you're out in a farm field positioning depends on GPS, global positioning system. If you have seen the news the last 2 years, that's a fun system to attack. People, attack it for military reasons. Kids attack it with something they downloaded off the Internet because it's fun. We need to protect this. We can't afford such GPS positions being denied or falsified. It's a cybersecurity problem as well because everybody knows timing and banking or stock trading depends on GPS time. So yes, that's fun to go and try and spoof that, how we call this, so create something that's not really true. Fortunately, we have a long tradition in doing these kind of things for the military sector, and we have now made these same technologies foolproof, export free and easy and cheap to use in the civil sector. So we have run it through many tests done mostly by military and departments of homeland security and authorities like that. We have not been able to be fooled once. But like virus scanners on the computer, that's a game that's never ending. We have to stay ahead of it because the bad people try to go and stay ahead of us. So we have to stay ahead of them. We are very much like computer virus. And thirdly, everybody that has navigated with their car or their cell phone knows GPS on its own is not that precise. We are quite happy if we get in front of the right house, yes. But you saw in this example, we have to really be 2, 3 centimeters precise with the tires of that huge machine. There's a technology often used in survey called RTK. That's geek speak for real-time kinematic. That's a way on how you improve the GPS position but it's quite local or regional. So it has quite a lot of costs associated with it, a lot of CapEx, a lot of operating costs. So we've been fortunate that we could develop a technology that we call RTK from the sky where we use very little infrastructure and provide the exact same improvements globally in the entire world, doesn't matter if you're in Antarctica, maybe you wouldn't do agriculture there, but you do other things or if you're in Europe, if you're in the U.S., if you're in South America, you can just expect part of the same signals that come from the GPS satellites or near the same signals a correction to your position that gives you instant accuracy, in most cases better than 2 centimeters, but we say, usually always better than 5. So that depends if you use one signal, 2 signal , 3 signal, but they are very accurate so that we can support not just agriculture autonomy, but autonomous mobility in all kinds of applications around the world without racking up hundreds of millions of infrastructure costs. So that's the third technology in this portfolio that makes us unique and stay ahead of the game. So of course, as I mentioned, it's not just agriculture. It was today's example, applications in mining and construction and some in shipping happen right now, and we're working on all of those. And we are definitely positioned to help everybody to have a better and nicer sustainable world. So with that, we move into Q&A. So if we can invite my colleagues back on the stage, please.

Okay. So we will start with 2 questions for Kalyn and Steven here, I think. And the first one is, what has the customer feedback been from OnCall and connect. And the second one is how important is SaaS for your strategy?

Let me take the first part. So I would say that OnCall has had a good beginning. We've had it launched now for a little over a year. Most of the implementations last 18 to 24 months. As we've announced, we have Danish National Police that is being implemented currently as well as the London Met. And so really big opportunities that are underway. But the pipeline continues to be good and so I think the reception has been good. We also do have one customer that's of significance that's live. I can't divulge the name of the city, but their daily call volume approaches that of New York City. So, so far, so good. Do you want to talk about Connect?

Sure. So HxGN Connect was officially launched just this past June. And I'm happy to say our first customer is going live. It's a transportation customer next month. So that's exciting for us. We are probably doing demos 4, 5 times a week across all vertical markets, public safety, transportation, utilities, construction. So, so far, the response has been very good. And as far as the SaaS, that's obviously very important to HxGN Connect because one of the challenges is, as I just talked about, it's integrating data from multiple organizations and bringing together in a collaboration space multiple people from multiple organizations. The only way to make that happen is to do that in the cloud and to make it easy for them to join by subscribing as a service. So Hexagon is managed by Hexagon in the cloud and it's born in the cloud, native cloud application.

Okay. Thanks. Next question is for Michael. You've spoken about autonomous agriculture today. Can you speak about autonomous opportunities in other industries?

Yes, sure. Off road autonomy, as I mentioned, is something that's happening right now. So in addition to agriculture, we work with very large mining companies on automating dangerous transportation processes in the mining industry. Really can't divulge customer names here, and we work with them on saving them a tremendous amount of hustle saving lives because it is very accident-prone environment. And I'm pretty sure these solutions will be fielded. They fielded a prototype right now fielded in production around 3 years' time. But we're running with these customers several prototypes 24/7.

Okay. And a follow-up on that, where do you think you can make the most money now?

Agriculture, for sure. So for semiautonomous tractors, we supply every day to 2/3 of the large manufacturers in the world is kind of equipment. So that's happening right now.

Okay. And another question here, which is, I think, connected to that as well. Is your strategy to address the OEM market in ag?

Yes, we actually only deal with the OEM market. So we don't deal with end customers. We make our customers, which are the machine manufacturers or the agricultural technology manufacturer successful. We have done that for a long time in the positioning space, and we do the same now in the autonomy space or semi-autonomy space. And in addition, we actually work with a lot of smaller startups that have specialized solutions that will see real production in the, say, 1-year to 3-year time frame, helping them to be successful. Autonomy is expensive. So not everybody can develop all the technology for themselves. They will not survive. So they come to somebody like us, to give them the building blocks to create their specialized solution.

Okay. And I think this is for Steven and Kalyn. How do you address privacy when addressing AI in your industry?

So one of the important things with the public safety industry and where we initially applied AI that I showed in this scenario and then again with HxGN Connect, I'll start with the public safety side. Our assisted AI is not using personal identification data. It's comparing the nature of the incident, what type of incident occurred, what is the type of suspect, what is the type of vehicle. So it's linking things by metadata that's not associated with personal information. On the HxGN Connect side, a lot of our effort has been involved in developing a framework for data sharing in order to get the different agencies to come on board, and be willing to share data in a collaborative manner. They need to know that they own their data and they control what data is shared with whom and under what business rules. So they have complete control through the tools we've built into HxGN Connect to enable the data sharing based on what they're comfortable with.

Great. Thanks. And with that, we'll go to a short break. [Break]

Okay. Welcome back. Good afternoon, everyone. I'm Ben Maslen, Hexagon's Chief Strategy Officer. I'm going to spend some time this afternoon talking about the strategy process at Hexagon before handing over to Maria to talk about how we embed sustainability in that strategy process and everything that we do. So to recap, Ola talked about Hexagon's vision, bringing together our sensor and software capabilities to create smart digital realities across all the industries that we serve. The clear takeaway for us and I think from today is that as end markets demand more real-time or autonomous solutions, you're going to need a much tighter integration between hardware and software. And between the phases of data capture and transfer, visualization and analysis, taking action and then feeding that back into the real world. So we're going to look today at how we take this vision and turn it into operational plans to deliver on our growth and profitability targets. Firstly, we need to break the vision down into clear strategic priorities that can drive Hexagon forward. Basically, where do we want to be? Now some of these priorities have been explained in the earlier presentations that you've seen today. Burkhard talked about launching disruptive products to become the world leader in autonomous reality capture. Kalyn talked about moving into a new market for us, situational awareness with the launch of HxGN Connect in June. And Michael talked about taking our autonomy positioning and perception technologies into the world of precision agriculture. So as you can see, across the group, there are many exciting opportunities for growth in the future that we want to capture. Secondly, you need a strong process to deliver those strategies. But how do we get there? So what we do, we build business cases that look at each opportunity in detail, the market size, the state of the competition, what resources we have and what we lack. And we always consider whether it makes more sense to do R&D and develop a product organically or to try and accelerate the strategic push by doing an acquisition. So should we make or should we buy? From there, we execute the business plan, we review progress at regular intervals, and we feed the results and lessons learned, good or bad back into the next iteration of the strategy. So as you can see, our process is very much a feedback loop itself, and that's made easier by Hexagon's light corporate structure and a constant internal review process, which brings both speed and flexibility. So let's look at some examples. As Thomas has outlined, we see a great opportunity in using reality capture sensors to increase efficiency and improve safety on the construction job site, and also through the life of the building, build and update digital realities of the built asset. So for this strategy, in terms of make or buy, given our existing leadership in laser scanning, it made more sense to develop ourselves a whole new range of autonomous reality capture sensors, both to make sure we got exactly the products that we wanted, but also to make sure we had a seamless integration into HxDR and other software products across the Hexagon Group. And as you saw, the BLK2FLY and BLK ARC are the latest additions to the family. Now we complemented this last year with the acquisition of OxBlue, which Thomas also mentioned. And this brought the group technologies that we didn't have, video and time lapse cameras as well as a very strong distribution channel in the U.S., AI algorithms to detect progress on the job site day by day, and whether workers are using the correct safety equipment, hard hats and vests and so forth. And it also has a very attractive hardware-as-a-service subscription business model, all of which have very strong synergies and read across with the existing business. And what you can see in the bottom circle there is the OxBlue cameras. We currently have positioned monitoring our orchid on a solar plant down in Southern Spain, which is the first R-evolution investment that we've done. In another example, Paolo talked about the opportunity to expand into renewable energy markets like wind. And here, we've already done the development to take existing products that we use in discrete manufacturing and refocus them on new segments like wind. And in the top circle here, you can see laser trackers being used to measure wind turbine parts as they're assembled on site. We complemented this last year with the acquisition of Romax, which Paolo mentioned, a market leader in simulation software for rotating technology, including wind power gearboxes. And it is the market leader in that field. This acquisition adds to the simulation products we already had for wind markets within MSC and allows us to build out a more end-to-end and comprehensive workflow for that vertical. And finally, as Mattias has outlined, we're focused on moving downstream from the design and build phases of large industrial assets into the operate phase of their life cycle, which is a much longer period of time. Here, we've built our own platform for asset life cycle information management, SDx, which manages all the plants engineering information right from initial conceptual design through to decommissioning at the end of its life. Now around this platform, we deliberately added a number of acquisitions to increase our presence in the ops and maintenance field. Last year, we bought PAS, a software platform to map plant for operating assets to detect and resolve cybersecurity risk, to keep the industrial facility up and running. And as you know, and you've seen across all the presentations today, we've recently announced the acquisition of Infor EAM platform, a solution to document and manage all the assets in a plant, predict when they like to fail, dispatch work crews to resolve issues and ultimately feed any changes or corrections back into our smart digital reality of the industrial facility. And to pull the exposure of EAM together after all the presentations today, it's not just industrial facilities that it's relevant for. We see great opportunities for this SaaS platform across all the end markets that Hexagon is exposed to, tracking and maintaining roads in cities, assets in a building, CNC machines and other machines on the factory floor, heavy mining assets, mining trucks and so forth, railways, utility assets and so forth. Basically, it's a great fit with the whole of Hexagon. Similarly, in terms of technology, we see great opportunities to link the platform to technologies that we already have in-house. HxDR and Michael's positioning technologies to locate and visualize your assets, APM, as Paolo mentioned, to pull in live data feeds to get real-time updates on your asset performance. BIM so you can visualize your assets in the context of a building. Dispatch to manage your work crews. And as we've seen autonomous reality capture sensors like BLK2FLY and BLK ARC to digitize your assets and keep your digital reality updated. So across Hexagon, we see great opportunities for end market and technological synergies, and that feeds into the USD 100 million synergy target we put out for 2026 when we announced the acquisition. So to conclude, it starts with a vision. We have a very strong process from that to break down strategic objectives to drive the company forward, turn that into business plans and to execute the strategy. We always consider whether it makes sense to make or buy M&A activity, which is my responsibility, achieve 4% contribution to growth on average over the last 5 years. So that's in line with the targets that we had. And I can say that we have a good pipeline going into 2022. And then finally, we embed sustainability into everything that we do in terms of our strategy from start to finish. And I'll now hand over to Maria, who's going to explain that in more detail.

Thanks, Ben. Okay. So I am going to talk about how we integrate sustainability and incorporate it in our strategy. And as you see here, it's really supported by both our vision and our mission. And when we incorporate sustainability, we look at our strategic focus areas and where our risks are and where our opportunities are and how to address this. And we do this -- when we do this, we look at this in 2 different ways. The first way is the change we empower by our own solutions. And the second one is the change we create by our own actions and operations. And here, we look at our own environmental footprint, driving sustainability in our supply chain, promoting diversity and inclusion in our workforce and also giving back to our local communities. And I'm going to focus on the first part here because this is where we believe we can make the biggest difference. And to explain this, I want -- we have to go back to basics and talk about what is Hexagon all about. And we put data to work to drive efficiency, productivity, quality and safety in different industries, processes and workflows. And these are all essential parts of driving sustainability. And the customers we serve are in some of the most vital industries to drive a sustainable transition. And all of these industries also face both challenges and opportunities when it comes to sustainability. If we look at manufacturers, buildings and infrastructure, they are focused on reducing waste and using less materials. Cities are focused on connectivity and creating smarter cities that reduces emissions. And farmers are focused on producing more output with less input and less land. And the focus on electrification and green steel is transforming the energy and auto sector and also increasing demand for mining minerals. So how is Hexagon then positioned to solve these industries' challenges? Well, if we start with looking at what our portfolio looks at -- looks like and our solutions within design, build and operate, with our computer simulation and design solutions, we can make better use of materials and increase energy efficiency. We can also optimize quality inspection that reduces waste and rework. And we can increase the live span of assets with our solutions in operations and maintenance. And you've heard Thomas, Paolo and Mattias all talk about this during the day. If we then move on and look at our geospatial portfolio, where we have advanced solutions to monitor, analyze and visualize changes on our planet and we can make better use of natural resources with precision agriculture, which Michael talked about today. And with our mining solutions, we can also optimize mineral extraction and reduce waste. And the third part of our portfolio is about monitoring events, and we can design real-time warning systems for collapse of dams, slopes, bridges, and glaciers, saving thousands of lives. And we have operational safety solutions in critical processes like power and energy and mining, which Mattias has talked about and also solutions for safer and smarter cities, which Steven and Kalyn talked about. And with Hexagon's technologies, we can also expand within these newer growth areas. And for example, Paolo talked about the wind energy sector and take wind and solar, which are expected to grow from 10% today to 40% in 2030. While Hexagon can help these industries increase output by more than 30% by the use of our solutions in the whole life cycle from design and engineering to operations and maintenance. And in the auto industry, electric vehicles are expected to represent 1/3 of the market by 2025. And Hexagon's simulation solutions can optimize and increase the range of an EV powertrain. And another interesting growth area is within carbon capture where our geospatial solutions can monitor and measure carbon things like tree cadasters and aquaculture. And as a catalyst to capturing these opportunities, we, this year, launched a new business venture called R-evolution, which is focused solely on accelerating the transition to a sustainable economy. And we do this by running profit-driven investments in green tech projects. And we also want to use Hexagon's technology in these new sustainable industries. And our first investment was in a 16-megawatt peak solar park, which Ben showcased today. And here, we are using our technology to extract more energy and more yields. And with the cash flow we generate, we will then invest in other projects. And the first set of projects will be within renewable energy and ecological monitoring because this is where we already have a footprint. But the next set of projects could be in energy storage and carbon capture and then further on also projects which in -- within water projects, lab grown protein and sustainable land-based fish farms. So to summarize this, as you've seen throughout the day, sustainability really is an integral part of our strategy. And it's something that creates value for Hexagon, our customers and the society. And it really drives growth opportunities and profits for Hexagon. And with that, I would like to hand over to Robert and Ola for the last session.

Thank you, Maria. Okay. Good afternoon, everyone. My name is Robert Belkic, and I'm the Hexagon CFO. And as Maria said, this is the last session of today, and I'll take you through the financials, and then I'll turn over to Ola for him to review our financial targets and also give you a glimpse into the future. So let's start off with this slide then. Looking at the organic growth of Hexagon during the period 2008 and the second quarter of 2021, in the last CMD in 2019, we talked about how our transformational journey with more solution selling would make our business more resilient. And unfortunately, due to COVID, we've got the chance to prove that last year. So looking at 2020 in isolation, and we still saw an organic growth decline, as you can see in this graph, mostly in the more cyclical hardware business. And at the same time, the software and services business was still quite solid during the year. This graph, I think, does a great job showing the strength and the resilience of Hexagon as of today compared to the financial crisis back in '08, '09. It shows the power our portfolio transformation has brought us these last couple of years. And this solution selling approach has also led to other impressive financials as well. So looking at these numbers, comparing 2009 to 2020, we can see that the gross margin has increased with 10 percentage points to 63%. We have improved our operating margin with 5 percentage points to 25%, and we have lifted the recurring revenue from 15% to 40% of revenue. So the transformation and the focus on the solution selling has also increased our software and services business as well. So let's take a look at those numbers. Okay. So what is evident from this slide is that the revenue from software and services have increased from 15% to 60% during this time period. And if we split the total revenue, that is then divided into 40% software, 20% services and 40% hardware. And if we dissect the software portion, it's evident that 30% are perpetual licenses, 5% is SaaS, 22% is subscription and 43% is maintenance. Okay. So we just covered some very impressive Hexagon numbers. So let's now look into one of the drivers behind this solid development by scrutinizing one of the divisions, namely Geosystems. Okay. So Hexagon acquired Geosystems systems in 2005. And at that time, Geosystems had an operating margin of 9% and recurring revenue of 8%. 15 years later, the operating margin has increased to 29%, and the recurring revenue has increased to 26%. So a truly impressive development indeed and an excellent example of how the individual divisions are implementing and executing on the Hexagon strategy. So how did Geosystems go about achieving this. Well, in 2005, Geosystems were highly dependent on a few profitable product lines, one of which you can see to the left, which is a total station for surveyors. And these product lines were delivering the KPIs you saw on the previous slide. The journey since then has been on portfolio of transformation and solution selling to capture the opportunities the technology brings us, exemplified by the various digital reality capture technologies from hardware to our software platform, HxDR, which you can see on the right-hand side, and which you also could see during Burkhard's presentation. So it's easy to get stuck and solely focused on software, but that's not what's going to lead us to our vision because to create autonomous solutions, you need to have solutions that can integrate workflow and put data to work by combining sensors, software and solution. And this is exactly what Geosystems has been doing. So the Geosystems success comes from continuing to invest in R&D, for innovating existing product lines, adding new products and also entering into new segments with the vision of connecting hardware and software to create autonomous solution. And it's this mindset that will continue to take Geosystems and Hexagon to new heights, we believe. Okay. So going back to Hexagon then and looking at another impressive KPI, the cash conversion. So looking at this graph, the transformation of Hexagon has also had a very positive impact on our cash conversion from around 90% 10 years ago to 123% in 2020. The transformation of the business will also continue to improve our working capital to sales. So as is evident from this slide, we are currently at record low level of 3.9% working capital sales. And as we add more prepayments and subscription to the business model, the less working capital the business ties up, and this is exactly the trend we have seen during the last 10 years. Okay. So looking at the transformation and what kind of impact it has had on the debt level of Hexagon. So the -- we have one financial covenant in our bank loan documentation today, and that's net debt to EBITDAR, which stipulates a max of EUR 3.5 billion. And that was really the level we were at following the acquisition of Intergraph in 2010. And as is evident from this slide, we have since then deleveraged rapidly. You have 2 spikes in this graph in 2014 and 2017, and that's when we acquired Vero Software and MSC. But very fast thereafter following this acquisition, we continue the deleveraging journey by -- facilitated by the strong cash flows of Hexagon. And now we will acquire EAM. And if we look at the net debt-to-EBITDAR ratio as of end of June when we close the books, it was 1.32. If we do a pro forma -- a Q2 pro forma calculation, including the debt we will incur by acquiring and closing EAM we will end up at 1.66. So a slight increase, but far from a dramatic one. So despite us having made the largest acquisition in Hexagon's history, we will still have substantial headroom for more M&A. So to summarize this section then, the business transformation we've been on these last couple of years has not only helped us improve our business, but it has also made us more resilient when in time of crisis. We have continued to improve our cash conversion and working capital to sales, both being at record levels today. And despite having done the biggest acquisition in Hexagon history, we still have a large headroom for further transformative M&A deals. So on that note, I want to say thank you, and I will hand over to Ola.

Thank you, Robert. Well, it's been a very informative day and you've heard a lot of interesting business opportunities that we believe that we can deliver. So our time -- our best time is actually yet to come. And as customary, we shall review the targets that we set 5 years ago. 5 years ago, in December 2016, we said we're going to have an average total growth per year of 8% to 10%. It's going to consist of 5% organic growth, 3% to 5% acquired growth, 0 FX impact. And by doing that, we can achieve an EBIT margin of 27%, 28%. At that time, we did EUR 3.15 billion in sales, and our EBIT margin was 23%. And if we now look at what the consensus estimates are together with the pro forma forecast Infor EAM. If we consolidated it from January 1, we will achieve 7% growth over the past 5 years. And that is built up with 4% organic, 4% acquired and a negative 1% FX headwind. So we will definitely hit our EBIT margin target. And without FX, we would have hit our sales target. And as a colleague of mine said, no one mentioned, no one forgotten. Had we had positive FX headwind, we wouldn't have mentioned it, but now it's negative. So we do mention it. It's time to set new targets, and it's time to step into the future of an autonomous future. And we believe that we're going to see an acceleration in organic growth for Hexagon's portfolio, simply because the world is more mature, the world is more ready for us. And therefore, we've set a target of 5% to 7% average organic growth per year. And we still believe that we can add 3% to 5% acquired growth. And all this together will sum up to 8% to 12% total growth per year. And we believe that the EBIT margin will be above 30% by December 2026. And how are we going to achieve that? And what trends do we see that matter for Hexagon. Well, first of all, we're moving rapidly from purchase to subscription. The subscription model is more mature now than it was 5 years ago. And here, it's exemplified by our airborne sensors, where in the past, we used to sell very expensive cameras. It was a lumpy business. We still do, but we also have huge business selling content. Another trend that we've -- has been obvious today is from digital twin to smart digital reality. You will hear many companies talk about digital twins. But as we've proven to you over and over today, it's not enough with the digital twin, a pretty picture, even though it's in 3D. It needs to be updated. It needs to rely on real-world events, and that is the thread that you've seen throughout all the examples today. From automation to autonomy, automation is great if you move in a straight line, but we're talking about solving problems that are not linear where chaos exist. And when chaos exists, which it does in the real world, you need to have autonomous robust systems that can deal with the unknown or the things you don't plan for. And finally, one great trend and one big trend for the next 10 years is going to be our move from the fossil society into the renewable society, and Hexagon is poised to use its technologies to facilitate this transition. And it's going to be a great business opportunity for us. So at the end of the day, we are at crossroads. We will have a 2-speed world for the next 10 years. We will see companies thrive and grow, and we will see companies go under. And our intention is to be on the top curve here and develop and evolve. And with that, we come to the final point in this very informative day. We're going to take questions from you that you've submitted. And I wish that Ben and Robert, could you join me on stage, and we'll do the Q&A. Guys, come on.

Okay. Great. A few questions then. We'll start with one around M&A. Your target is to acquire 3% to 5% revenue growth per year, in which division do you see the strongest potential M&A contribution going forward? And will it be hard to reach now that you're at sales of about 4.5 billion?

I think the -- we ask all the divisions to build M&A pipelines, and I think you've seen today, they all have great strategies for growth. I won't go into specific targets or areas that they're looking at, but they're obviously in line with the areas they've talked about over the course of the presentations today. So as I said, the M&A process is very much tied to the strategy, which my friends have run through today. In terms of can we hit 3% to 5%, I think we can. I think that it becomes a little bit more difficult, I guess, as the base gets bigger. But as you've seen today, Hexagon is moving into lots of different new markets, new areas, and that opens up potential for acquisitions in those spaces, too. So yes, I think that we're happy we can do 3% to 5% as we did last time.

Thanks. And another question here, how will the cost base for Hexagon change post-COVID?

Should I take that? We've seen a reduction in travel and entertainment. It's sustainable. It's about 100 million per annum, and we don't think 100 million is sustainable. But we do think we're going to bounce back maybe to 60%, 70% at full capacity. And that is the biggest chunk of cost that we've seen has changed materially apart from the reductions in personnel that we did last year.

Okay. And I think this may be also addressed to you. In your view, will digital realities, autonomy, robotics and AI, et cetera, trigger GDP growth long term or instead risk to trigger massive structural unemployment and stagflation?

That's a very interesting question. I personally believe and this -- anyone can believe whatever they want, I think these robotic solutions are going to force people to leave their employment with traditional jobs such as transportation, basic service jobs, security jobs, assembly line workers and so on. And only to produce combustion engines, we have 60 million people working worldwide doing that. So of course, it's going to be dramatic in the labor market. But once we're beyond that, I believe that we're going to see increased global growth because then the system is in balance again. But it's back to this curve or the 2 arrows we showed. It's going to be change, negative change and positive change like always.

Okay. Another question here. How much does voice of the customer feed into the strategic planning process to help formulate new applications and business models?

Yes. No, that's a good question. I mean if you remember the little feedback loop we had on the process, when we look into these business plans, we do look at all the end markets, we do surveys and research with customers as to what they actually want, how the technology is changing. So it's part of that process. If you buy a company -- Hexagon tends to buy good companies that aren't 5 years out, they maybe make money. They make money now. They're profitable. So the customers have already voted effectively. We know what customers want. For an R&D project, we often have a lighthouse customer and work with them to refine and develop the products to make sure it's right before we take it to market. So it's a big part of the process here.

Okay. Thank you. How important is the transition to more software and SaaS to reach the targets in 2026?

I can take that. It's not driven by software and SaaS. As a matter of fact, most companies would vote for that. We see a merger between well-run hardware businesses and well-run software businesses. And typically, you reach a gross margin of around 75%. Software businesses used to have higher margins, but with the cloud delivery, you actually have the cloud operator taking a bit of that margin, lowering the software offerings gross margin. And as we've seen from the example from Geosystems that Robert showed, you can do very well indeed, if you have good designed hardware. So I think it's not a question on SaaS or mix, I think we will do it by developing our solutions.

And a follow-up on that. Can you please discuss the drivers of margin expansion. So it's a bit similar to what you just...

The driver is typically and has been for the past 15 years, it's been that the next-generation products are more efficient and have better gross margins than the products they replace. So over time, we gradually upgraded our product mix. And then at the same time, as you saw, we lifted -- in the past 10 years, we lifted our gross margin by 10% and our EBIT margin by 5%. So you need to invest more in sales and R&D, and that's what we're doing. So it's going to be a twofold process where the gross margin is going to grow, but the OpEx is going to grow too. But the net result is an EBIT margin increase.

Okay. Now the question around M&A. Do you expect doing more strategic transformational M&A deals? And if so, will it be mainly focused on software or can hardware fit in here as well?

Yes. I mean I think, as Robert showed, the balance sheet is in good shape. We have the capacity to do something, if it came along. But I don't think we need to do something large to hit the targets. I think we can get to 3% to 5% with the kind of small- and medium-sized acquisitions that Hexagon has done historically, and we did one yesterday. But if something comes along that fits and by that, I mean, it generates the kind of synergies you need these days to justify the valuation, then yes, we obviously have the capacity to do that. And then is it more like to be software or hardware. I mean I think if you look over the last 4 or 5 years, you can see that the larger acquisitions have lent towards software, but it's not exclusively so. If something came along that helped us hit the roadmap and was hardware-based, then we'd obviously could look at it.

Okay. And another question here from the audience. Could you please give more color regarding the R&D budget allocation to serve Hexagon's target? Will it need to increase?

Yes, it will increase as a percentage of sales over time. Absolutely.

Okay. And let's see here if we have any more questions from the audience. Could you speak to how you balance the new target growth and margin within your new guidance?

I don't understand that question.

No, not -- me neither really. I think maybe the question is, how do you prioritize between growth and margin?

Well, it's not a conflict because, as I previously stated, the next-generation product typically is more optimized than its predecessor. So we automatically get a gross profit lift by doing that. The fact that we want to invest more in R&D and sales is simply a reflection of -- that we're going to touch different industries. We're going to do more solution-based sales, and we need more R&D.

Okay. And here is a question on China. What is your view on the demand situation in China now and going forward?

China has been fantastic for the first half. We've seen unprecedented growth rates in China. But one has to remember that in the first quarter and the second quarter, the Chinese society was in lockdown. So it's quite easy comps that we had to beat in the first 2 quarters of 2021. Our long-term view is that this is now going to come down, and the government of China predicts 6% GDP growth, and we typically grow a little faster than that. We typically say twice the GDP growth. And I think that's what we're going to see for the remainder of the year.

Here is a question on ESG. You have a target to run sustainability audits on 100% of the high risk suppliers by 2023. Can you talk about how you are doing the audits? And how you define high risk supplier? I can answer that one. Well, we define a high risk country by the definition of that the United Nation has and they include human rights, environment and corruption and so on in their definition. We're looking at it. And how we conduct it today is that we use both self-assessments and on-site visits to do audits today, and we've also joined the Responsible Business Alliance, which will give us also additional tools to conduct supplier audits and reach our target by 2023. Okay. So another question here. Any guidance of where the gross margin could end up 5 years out?

No, we don't give -- we won't give a forecast on the gross margin, but as I previously alluded to, it's probably around 75%. That is the maximum that we can achieve with the current business model, but not in the next 5 years.

Great. And here is a question about component shortages. Can you elaborate on how you have been affected by component shortages, cost inflation and logistics disruptions?

Yes. We've seen freight costs going up, and that has hurt us. We've seen cost inflation for labor, and we've also seen component shortages primarily in the A&P and the Geosystems divisions up till now.

Thanks. And there are no further questions from the audience. So I think we can conclude the day, Ola.

Yes. Thank you, everyone, for listening in.