Siemens Limited (SIEMENS.NS) Earnings Call Transcript & Summary

That was a wonderful start to this powerpack day that we have today for all of you. A very warm welcome on behalf of the House of Siemens. I'm Indu Sharma, and I lead Communications for Siemens Limited. And this is a warm welcome for all of you who are joining me out over here. And we have a lot of guests who are joining us on LinkedIn live on different, different platforms. Thank you so much for joining with us and warm, warm welcome to all of you. Today is going to be a very exciting day. There's lots that is really happening, but I see broadly 2 purposes that we've all really gathered out over here. We want to be transformed, right? Transform with what, transform with knowledge and transform with the inspiration for action. Now what is this knowledge all about and what is this inspiration? This knowledge is about the digital transformation of how we can truly reshape Indian industries. And how does it inspire us? It inspires us to innovate, to adopt and to scale in this area of digital change, change that matters for all of us actually. And as each one of you really pivot towards a bigger and a better future for your businesses, Siemens is truly committed to be a partner for you in all areas that you really look forward to. And now it's my pleasure to invite Mr. Sunil Mathur, MD and CEO of Siemens Limited on to the stage to really unveil the transform. Can we have a round of applause for Sunil.

So start again. Good morning, and a very warm welcome to the fifth Innovation Day of Siemens. I am delighted to see a couple of familiar faces here. Some of you have been here to the various innovation days prior to this. So to those of you who've been here, welcome back. And to those of you who are coming for the first time, a very warm welcome to the Siemens Fifth Innovation Day. Now I think it is fair to say that over the years and particularly in the last couple of years, the pace at which technology has picked up has been unprecedented. For many, particularly in businesses, first, getting an overview of what technologies are out there; and secondly, being able to contextualize that to your respective businesses is becoming an increasing challenge. And that is what we are trying to do at our Innovation Days here is to really contextualize the latest technologies that are available out there and enable you to really see how you can find solutions to the most complex problems that you are facing. From an India perspective, though, I think I would -- I'd like to say we are in a very, very strong position, not only geopolitically, but also economically. If you look at our GDP, we've had a robust GDP growth, not just 1 year, but in the last 3 or 4 years in a row, post-COVID, growing in the range of 7% a year, 8.2% last year, the expectation is close to 7% this year. And then we want to grow at 7% plus in the years ahead. $3.6 billion of GDP already and climbing. Infrastructure in the country has improved tremendously. Renewable energy, we are talking about close to 200 gigawatts of -- or in fact, more than 200 gigawatts now on the grid, which is more than -- which is almost 50% of the total energy consumption installed capacity in the country. If you look at the railways, 64,000 kilometers of railways has been electrified. Now that is roughly 95% of the entire network in India has actually been electrified. We have the largest green electrification network in the world. This is just alone in the last 10 years. We have electrified in India more than or equivalent to the entire network of Germany. And this has come just in the last 8 to 10 years. Infrastructure industry. We are the second largest producers of steel and cement, the third large pharma producing country in the world. And dairy, food and beverage, chemicals are all areas where we are growing and becoming increasingly relevant in the globally relevant now. But digital leadership here has been something that India has been used to. We are digital natives. We have rolled out the fastest rollout of 5G in the world. We have over 1.1 billion mobile users, 954 million Internet users. We have the lowest cost of data in the world. And this is actually the basis and the foundation of the growth story of the country. In October, 17 billion payment transactions were done in India, 17 billion. That is 50% of the global payment transactions that were done in 1 month were done here in India. And these are the foundational footprints that Siemens really -- that the country really has that will be the foundation of the growth story here in the country. But the last 4 or 5 years, the growth story of India has been largely led by government spending in infrastructure and rightly so, rightly so because foundational infrastructure is absolutely critical for the growth in industry, for the growth in digitalization and for everything else that this country aspires to be as an economic power. In the last 4 years -- last 4 years has been cumulatively spent on infrastructure, roads, bridges, railways, ports, airports. And this has really had an impact downstream into the entire supply chain, which in turn has really contributed to the growth story and to the GDP here in the country. But if we are to sustain 7%, 7.5% growth in the country in the years ahead, the government has a very clear program to do that. First, energy will play a critical role. And we are very clearly in the energy transition phase. As I said, 200 gigawatts of renewables have already been created. We expect to get up to 500 gigawatts by 2030 and to 600 gigawatts by 2032, and we are well on track to do that. But that will have a knock-on impact on to the entire transmission and distribution networks in the country. As you bring more renewables into the grid, the grid becomes unstable. As you grow as an economy, you will need more grids, you will need a better distribution system. The country is looking at doubling not only its generation capacity, but doubling its transmission and will have to, therefore, double its distribution capacities in the next 5 years. And we are well on track to do that. When I look at public infrastructure, railways has already done a huge amount on the electrification. They are now looking at signaling and they're looking at rolling stock. If you look at locomotives for cargo, if you look at passenger trains, the intent of the railways is really to shift the cargo from the road to the railways. And this is not only a great strategy from a sustainability perspective. We have got -- we received an order 2 years ago for the supply of 1,200 locomotives. Over the life cycle of the project, we will have saved 500,000 autos or cars from coming on to the roads in terms of cargo shifting from road to rail. And these are the kind of examples that we have got. 50 new airports will be set up in the country in the next 5 to 7 years. We are looking at private CapEx coming in, in new age technologies, semiconductors, battery manufacturing, e-vehicles, pharmaceuticals, new technologies coming in there as well. But all of this is designed to make India an Aatmanirbhar Bharat country, self-reliant country, where we don't have to depend on any other country for our supply chains and where we can be responsible for our own growth story and control it, control our destinies in our own hands. Finally, private CapEx in more the conventional verticals, food and beverage, automotive, services, footwear, textiles and so on. These are areas that will pick up. We are confident of that. Schemes are in place. Demand has to pick up in a country as we get into a greater zone in terms of our GDP. But as we move in this direction, if we have to grow at the speed and at the scale at which we are planning to do that here in the country, there are going to be certain imperatives that all of us, all of you will be faced with, productivity and efficiency. How can we do all of this in a shorter time, much faster and less resources -- using less resources? Speed and scale will be absolutely fundamental to fuel the growth story. We can't -- we don't have the time. We will need to speeden-up the creation of our factories, the production, the time to market, the infrastructure development. We will have to make it much smarter. And finally, with regulations coming in and because of India's commitment at the COP26, which we've already reached and now we intend to go beyond, sustainability is going to be absolutely fundamental to everything that we build here in this country, whether it is infrastructure, private CapEx or anything else. And when you try and match the growth story of the country with the infrastructure and CapEx requirements and your individual business cases, the only way to do it is going to be through the use of technology. While we are in India, having an average capacity utilization currently in the range of 80%, but our productivity levels are at about 75% to 77% here in the country, there is no way we will be able to deliver the size and scale that I've just talked about just by upskilling and just by providing or doing more of what we've been doing right now. Technology will be the absolute enabler, will be the key imperative to take us to the next level. Now in 2022, in this very Innovation Day, we launched Siemens Xcelerator with the idea of doing exactly that, with the idea of enabling customers on their journeys of productivity, resource efficiency, energy efficiency, speed and scale. And in the meantime, we have expanded the offerings on this digital platform to multiple areas, whether it is buildings, whether it is utilities, whether it is industries, different industries and data centers. Globally, we have over 1,000 business cases and 1,000 references. In India itself, we have close to 200 cases, references already that we have got and that we are working with, with customers to answer really complex issues, across multiple industries, across infrastructure as well. We are doing this not alone. We do this together with the customers, but also with an ecosystem of partners that is ever expanding. But as I said, technology is moving at a pace much faster. And in the meantime, we have a whole lot at a whole host of new technologies that are acting as further enablers to make this platform even more powerful and who better a person to talk about this than Dr. Peter Koerte, Member of the Managing Board of Siemens AG, Chief Technology Officer and Chief Strategy Officer of Siemens AG, who was here at the launch of the Siemens Xcelerator, is here today. And he's flown in especially just for the day. He came in this morning, flies out tonight. But Peter is going to tell us how this technology is actually moving, where it's moving to, and what kind of an impact it can really have on your businesses to make it more relevant to make you and your customers more satisfied and more productive. So with that, thank you very much, Peter, for joining us today, and over to you.

Thank you, Sunil. Thank you, everyone, for joining us this morning. It's a great privilege to be here a third time and to talk with you and talk and discuss about how far we've come with, of course, bringing digitalization to India and making you successful. So in the next 45 minutes, I will give you a little bit of an update where we are, but then also engage in questions and answers that you may have so that we can discuss what it takes to bring technology to the next level. Sunil spoke about it. We see every week new models, new technologies coming our way, and it's very important to keep a good oversight there. So therefore, there's one key question that we have to start with asking and that is what if. What if is a very powerful question because it lets us think in different ways. Let me start with something very near and dear to your heart, which is actually also near and dear to my heart that is if you take some nice spices and combine it with black tea and a little bit of milk, you get to, of course, a warm delicious cup of chai tea, which I very much enjoyed also this morning, which is a great invention and innovation coming out of India. But who would have thought of putting these ingredients together? Well, we enjoy them all. I hope you all do on a daily basis. Now that's our daily life. We can do this also in technology. And the one that you know probably best is the one that you are carrying right now in your pocket. From an Internet browser to the MP3 player all the way to a phone, all of this came together because somebody said, what if? What if we combined it into something that we now call a smartphone? Now you may argue, well, this is our consumer, but then what if we think about the home and bring actually all the great technology together that we have at our disposal when it comes to illumination, when it comes to clear climate and heating, we can bring this all together with the push of the button and make the smart home a reality. So what if we can bring this to all the industries that we serve and that you are in here today? Because the world turns out it's not becoming simpler every day. If you look around, we see that there's quite complex challenges that all of us, including Siemens, by the way, is facing on a daily basis. We see broad sprouts, three things that we all struggle with and where we need to have answers to. For one, the world has become ever more competitive. Just think about China. 1/3 of all the companies today in China, they are losing money, which means they're going abroad, which means there's a lot of more competition on a global stage. Think about sustainability. Not sure if you all are familiar with the acronym of CBAM, Carbon Border Adjustment Mechanism. It is something that the Europeans invented and which is absolutely crucial if you are an export-oriented industry in order to serve this very market. And by the way, regulation for sustainability is coming in every single country around the world. So for you to stay up with all the challenges that comes with sustainability is very, very big. And then lastly, there's resilience. We've seen it last week. Maybe it's about your country first again, where there's going to be a lot of tariffs, and the world isn't becoming an easier place in that regard. So lots of challenges that we all face. We have to become more productive, more competitive, more sustainable, more resilient, all of it at the same time. So how can we change this? How can we make it such that we actually have simple solutions in order to make it work? And we, at Siemens, we believe in one fundamental thing, and that is by combining the real and the digital world by actually making the world a smarter place where you harness the power of data from your operations that you're creating on an every day. No matter if it is in infrastructure, for buildings, in particular, or grids, no matter if it is an industry or no matter if it is a mobility, we at Siemens, we wholeheartedly believe that we can help you to make this work. So why do you think that we are actually are so convinced of this? And the very simple answer is probably that in industry there's most of the data today on a global basis. So you see here the 2,200 terabytes that is a typical factory that is producing the amount of data on a monthly basis, that's equivalent to over 0.5 million Netflix movies. And you may ask, why is that so? And the very short answer is because the world is becoming smarter. Today, there's estimates that there's about 18 billion IoT devices, 18 billion IoT devices, twice as many humans, and it's growing at 15% every year. Now just think about what that will do to the amount of data we're going to see in the future. Much more of that. Except today, most of that data and industry in particular, is locked and is not being used as much as it should and as it could. And this is where we at Siemens come and say the Siemens Xcelerator, as Sunil spoke about. We want to help you to combine the real world with all the intelligence assets that you have at your disposal and combine it with intelligence out of the digital builds. In order to do so, you have to actually look at the full technology stack that is out there. You have to start connecting your devices, be it an AGV, an autonomous-guided vehicle or being at a robot or be it a PLC, we have to connect all these devices in order to make use out of it. But connectivity usually is only the first step. Next comes the conversation about how we get this from the feed sensors -- feed devices and sensors into an aggregated way, which means very often that you process it on an edge level, meaning you do it on site, but still you are able to communicate across different sites through the cloud. But then still, we can elevate the conversation to the cloud, and we can bring you the dedicated applications and the software in order to make all of this work. Combining the real and the digital world is exactly what we are doing on a daily basis. So let me give you a few examples of where we have demonstrated this over and over again. So what if you actually are looking to standardize solution to improve food and beverage production around the world. If you today in food and beverage, you're going to face a few challenges. One of which is there's a lot of increase in prices, energy prices, harvest prices, all of these are going up while your consumers are not willing to pay more. So sustainability, you have to prove that you're actually certified and that you can track and trace all the different elements that you're shipping. And then lastly, there is sustainability as well, where it's all about biodiversity. Your consumers want to have always the same taste by the input or the grain and the different materials that they're using is actually changing because of the different forces that we see in nature. So what if we can help you actually to standardize it and to make yourself life much, much simpler. What we've done here in this case is for dairy production. And this is where we used Industrial Operations X to help dairy producers to produce their milk powder that requires a lot of energy. So the way you produce milk powder is pretty simple, you take dairy, you apply a lot of hot air for a longer period of time and that outcomes the milk powder. But turns out, this is a very energy-intensive process. So what if we can help you actually to reduce the energy consumption by more than 10% and improve the throughput at the same time by 10%? And the way we did this is by building a digital twin of that very production. So we precisely simulated the entire production process step by step based on conventional but also on digital models, which enabled us to run multiple what-if scenarios and identify the key parameters in order to fine tune the model to make that work. And you can tell, obviously, it is paying off, not just from a bottom line with regards to the P&L, but also from an energy and sustainability perspective, this is very, very powerful. So let me keep on going and ask what if we can create greener and smarter buildings with just 1 simple application. And as you know, 1/3 of all the energy like in this building is actually consumed by buildings. And about 1/4 of all the greenhouse gas emissions are therefore coming from buildings, which means the fight against climate change is won or lost in cities pretty much where most of the buildings are. So the question is how can we make buildings more sustainable in a very simple way? And the answer is this Building X. Building X is something that Sunil and I also 2 years ago, we were proudly introducing to the Indian market. Now we can show you a few great results that are happening around us. Take, for example, a public school in the northern part of India that was actually grappling with increasing energy and maintenance bills. They were looking for a very simple solution out of the box that they couldn't implement in order to help them with one application to make them more efficient with regards to maintenance and energy prices. They found that with operations manager in Building X. And why is it so important? Because it is a SaaS, a Software as a Service application, which is very easy to switch on and off so that we can completely fit the needs. Because schools, as you can imagine, they don't have an IT help desk that helps you to make major IT projects work. So instantaneously, where we're able to do that. Today, that's school and the [indiscernible] had 3 school buildings that are using all of this, and the good thing is with Building X on a global scale. In the meanwhile, we've introduced it to more than 50,000 buildings around the world, and we've added functionalities such as the sustainability manager step by step by step. Now you may say, "All right, a public school. But what if we can do this also to hotel like this one. So what if we could do this with Building X to make an internationally renowned hotel chain make it much, much more sustainable where we can save a lot of energy and reduce, therefore, the CO2 footprint significantly. And here comes again the key insight. It's the domain knowledge together with the data that comes from daily operations that makes the difference. In this case, we realized in hotel, pretty much most of the energy consumed is where the chillers. So we have to look at the chiller and the chiller plants. It's not just a chiller alone that is important. It's actually all the air handling units. It's the secondary, the primary motors. It's all the way to the chillers and then the air cooling towers. You have to look at the entire plan in order to optimize it. And with that chain, we were able to identify all the critical assets, all the relevant motors that we're using energy on a daily basis, and we could significantly, of course, reduce their operations, thereby making them more sustainable and making them much more sustainable for the future to come. So all of these are great examples from buildings. But then what if about data centers? And probably everybody nowadays is talking about data centers in 2 different ways, because for one, they're part of the solution. There's an estimate study that says about 40% of all the energy can be reduced if you use actually data, so then data centers are part of the solution. But there's also studies that suggest that data centers are part of the problem because 4% to 5% of global greenhouse gas emissions are emerging out of data centers and the tendency is increasing because of all the large language models and the AI now finding its way into data centers. So therefore, then what if we could make those data centers more efficient, make it more sustainable, but also make it safer in that regard? And here, I would like to take you actually at this time, outside of India into a cold place called Estonia. And Estonia has built one of the finest data centers that is out there with Greenergy that actually is not only the safest, but also it's about one of the most sustainable ones. It is a data center that consumes 31 or 32 megawatts, which is quite substantial, if you think about it. It can power actually a small city in that regard. And what we realize is that about up to 40% of all the energy consumed by data center is in cooling and ventilation. So therefore, if you are able to create heat maps, literally heat maps of that very data center, if you can build a digital twin to understand where the power is disseminating, and what kind of cooling that is required in which part of the data center, at which point of the day, you can significantly reduce the amounts of energy that is being reduced. And of course, if you take that excess capacity on the excess heat and put it back to a heating company, then, of course, you can save a lot of money. And that's exactly what we've done that in order to apply that, we have to bring the sensors. We have to bring the digital twins into it in order to make it much, much more efficient. But that's not the only thing. Of course, we have to make it safe where you have a backup and a backup system, and of course, very strict surveillance and access control systems, which all comes together in order to make this not just a more sustainable, but also a much more safer place to be. So all of this can be done by connecting every time again, smart sensors together with the ability to put it into the digital world. Now if you think this all the way to the end, and we talked about it for those who attended last year, we think this will result into something that we call the industrial metaverse. Think of the industrial metaverse as a digital world where we can solve real-world problems just 10 to 100x faster. And it is driven not just by 1 technology, but it's actually driven by many technologies. And it's a little bit like if you remember your school times, it is if you fall behind like in math, it's very hard to catch up. And this is a little bit like that as well. We started with IoT, putting smart devices and sensors everywhere, then we continued with edge and cloud computing where we get the data and we made use out of it. Then we continue and we build digital twins out of it and now comes AI and of course, GenAI in order to harness all of this. As you can tell, at some point, you have to get started and then really to speed up through the deployment of each and every technology in order to make this work. Now the industrial metaverse is something that will not be switched on overnight. It will happen step by step because one of the key building blocks are those digital twins, a replica of the real world where we can run a lot of what-if scenarios, again, where we can simulate multi-physics with regards to how objects will behave in the real world. If I take this pointer, if I dropped it, I could already take a look of whether it would break or not, and we can simulate each and every piece with that in the digital world. And as you can imagine, we can do this much, much faster. So let me give you one example that I haven't touched on yet, and that comes from mobility. Sunil was talking about the great infrastructure that is being built now in India. And what if we can take actually all of that technology and make this really, really powerful, and that is for rail electrification? So what if we can actually combine the real and digital world and make our trains run smoothly and much more reliably? And for that, we need something that is called a static frequency converter, think of it as a conductor when you travel around the world, and you have to make sure that actually your laptop, your phones, actually are being charged and working. Think of it the same way for the railway industry, where sometimes you have different frequencies and you have to convert it. Luckily in India, you're having 50 hertz, same in the grid as much as you're in the railway industry, but you have different phases. So the grid is running on 3 and the mobility lines is running on 1, which creates a big, big problem for engineers. So you have to build plans in order to solve this. The traditional way of doing this is you have to do a lot of design. There's a lot of experts, but what if we can use actually a chatbot, a CoPilot that enables you to do that in your very natural language that almost a lay user can do what that is doing. So let's see what happens if we give the AI this prompt. So what the AI does, it checks the different parameters and give suggestions on how to proceed. It checks whether all the boxes are ticked and whether the site that you have been selecting can be really used for what you want to build, in this case, a static frequency converter. It not only can check where you want build this, but it also can automatically go to your library and then check what the layout of that would be in order to build that into your infrastructure. Let me tell you today, this is an effort that takes weeks over months in order to make this work. In this case, it's a matter of days in order to free up precious engineering work and to accelerate all of that. But it doesn't stop there because what we can do there is we can integrate it into the product life cycle management, and we can look at the very it's -- very plant that we want to optimize here and can make decisions faster based on the very specific circumstances that we're operating in and thereby significantly accelerate, of course, the design cycles that we want to deploy. So Siemens Mobility, bringing that to India will have a major, major contribution to bring these 2 worlds, the real world and the digital world together to speed all of this up. Now as Sunil has spoke about, to make this happen, it takes a village. And so therefore, you need to have a portfolio that is able to connect and where you get all the data together. You will have to have all the partners because nobody can do this alone. And you will have to have a marketplace where you can all find this because we know that in India, the 60 million of small- to medium-sized enterprises, they are in desperate need for easy, smart, deployable solutions to make them more competitive, more sustainable, more resilient. And that's exactly what we've done. Sunil spoke about the numbers that you've seen in India. On a global basis, we have more than 1,000 portfolio elements in the meanwhile. We have more than 400 sellers, and we have the 1 marketplace where you find all of that. But let me emphasize here, again, as we did the past 2 years, we cannot do this alone. That's why it's great to have all our partners here today also on the outside as you go outside of the meeting room. And you will find a lot of great examples where we collaborate, for example, where we make steel production much, much more sustainable. So let me conclude there that we, of course, want to bring technology to make our lives easier. And with asking what-if questions, we can turn complex challenges and to actually quite manageable tasks and distill them down. We want to build a more competitive industry, which is much more CO2 neutral and where our lives are becoming much, much better. It's quite simple. All what we do is we have to work together because in the end, it's not technology that makes the difference. It's the people that use the technology to make that very difference. And all what you need to do is by asking one very simple question, and that is what if. A big, thank you, and I'm very much looking forward to your questions.

Thank you so much, Peter. That was such an insightful session. But we are sure that there will going to be a lot of questions about what ifs and what is the possible basis that. So if anyone of you have any questions, please raise your hands, we will get the mics reach you. We have one here for a lady, can we get the mic here?

It's wonderful to be here. And I love the infinity loop that you have in transform because it's all about learn, unknown, relearn, cocreate, right? So my question is that you spoke a lot about sustainability and transformation and digital twins, et cetera. In terms of, I would say, what I face across the global market leading sustainability as a charter, is making the organization understand the significance of investment in the technology, and I'm sure everyone faces that. And how do we make this learning more outcome based for them -- so that it is easier because it's very difficult to explain technology to a CFO. My apologies, if anyone is a CFO here.

Thank you for your question. And indeed, it is, of course, a major challenge with regards to all the investment that is required. Usually, what we find is for those use cases that we all start where it's actually both where you improve the energy efficiency, but at the same time, where you save a lot of money because of less energy spend. That's the language a CFO very well understands. So all the cases that I showed you with regards to production in buildings and infrastructure, you can go and say, look, maybe we're not only going to make the planet better because we have less CO2 emissions, but we also save a lot of money on the bottom line. That's where usually these projects are being implemented quite quickly. You're right. As we continue to move on, you are starting to polish the asymptotes. So it's getting harder and harder. That said, though, for the most companies that we see today, there's plenty of opportunities in particular right now with regards to just having the mere transparency on where the energy is being used. We find very often that today, most organizations are struggling with having a comprehensive data set about like a Sankey diagram. So where is the energy coming from? Where is it -- how is it created? How is your energy mix specifically? And where is it being used specifically? And just by creating that transparency, we find that usually there's a lot of efficiency coming into it with regards to that. Start there, I suggest, and then we will see as we walk along. Thank you.

When you're planning to take your data centers to the Arctics, we talk about data centers which are running around in cold seas, or to countries like Estonia. Aren't you spoiling the fragile ecosystem of those places. We already have a fragile ecosystem there. Putin would never go to Siberia to take his oil because he knows that Siberian ecosystem can get spoiled.

Can you repeat the question for me?

You have to state the question a little more clearly.

When you're going to cold places like Estonia, aren't you spoiling the fragile ecosystem of those places just because you get concessions in controlling the heat.

So we don't build data centers ourselves. We provide technologies that can make data centers more sustainable. So if someone does decide to set up a data center in the middle of the Arctics, we will help that data center operator reduce the emissions and do it in a much more sustainable way. So we're actually contributing over there.

Okay. Do we have more questions? we have one here, please.

I'm from Tata Motors, [indiscernible]. I have two questions. One is the making sustainable energy solutions as well as the reducing the cost of energy. How AI will help us? Suppose we are having different bucket of energy sources, solar, wind, IGX and solar also from the outside as well as from in-house, wind from outside from in-house. So all these mixes, how we will optimically we can utilize to reduce our cost of energy as well as to maximize the RE100 that goal of the company? How AI and other technology can help us?

Yes. That's a great question. So usually, it depends, #1 is, of course, it depends on the mix of how you buy your electricity today, whether that is coal generated or already that is from green sources such as, as you said, wind or solar. But that is usually the way you purchase. Now it comes the question about whether you should be investing into energy storage linked to, let's say, PV, photovoltaic energy generation. And we have multiple capabilities to provide you with services that actually do the calculations in order to determine that return on investment, depending, of course, how much sun where your location is. we can identify of what that is. So usually, we do energy audits, we look at, of course, the energy patterns that you're having. We are looking at, of course, source capacity. We look at, of course, all the sourced generation. And then we run that model for you depending on the operations that you're in.

Do you or okay. You have a follow-up one? Okay. Do we have more questions? We have a question here, please?

This is Shivani from Tata Motors. So as the concept says it's transform, we have seen technology going from simple digital analytics of data to AI, ML and now to GenAI. Now what could be the next step do you foresee in terms of the data analytics part assisting and helping the OEMs to use technology in more better way for efficiency and improvements?

Yes. Well, thank you. And we have Dirk, who's going to be the next speaker, who's going to talk about this a little bit to you. But let me give you a few thoughts on this one, first and foremost, you're right. Data has been there for the longest time. As a matter of fact, at Siemens we are working on AI model since 50 years, it turned out. We just did the math in 1974, we started because there was obviously the idea you can automate a lot of things out in the digital space with regards to data. And of course, you know the history with, of course, neural networks, then machine learning and now with GenAI coming our way. We see that this has a lot of potential still. Right now, the focus is pretty much on language, so large language models. And we look at it in different ways. We look at it as bringing industrial applications. We don't need large models, but very often, we need to have small models, which means you don't need to have trillions of parameters, but it's actually, it's just fine if you have just 5 billion to 8 billion, if it is a small model, but therefore, very efficient, so that we can, for example, deploy it on the, let's say, edge device or on a field constrained device in order to do the inferencing wide at source wherever that is happening. So that is from large to small, if you like. The next one is about language. It's the second L and that is about, we, of course, deal a lot with language, in particular, we as humans. However, the 18 billion IoT devices I mentioned earlier, they don't. They speak in time series. So therefore, we have to train many of these models on time series data which yet again is a very different approach. And right now, we are experimenting of how best to use even large language models for that very purpose and making them multi-modal, right? So it's not just the language, but it's also time series. And then, of course, lastly, there's design data that we are very excited about. Last year, I showcased where we can use generative design, for example, where you can speed up the development process by having, of course, GenAI or GenAI support you to design whatever device we want to design much, much faster. So we have to teach a design data. So all of this eventually will come together. It's still very early stage. We have to see how that comes. And then lastly, all of this, of course, has to do with speed. Today, it takes a very long time to train these models. And then, of course, also sometimes inference time takes a longer time. And the question, of course, is what's next generation we're going to see there on the compute side, but that is -- that remains to be seen. But should we say, in the industry right now, we have enough already in that sense. The key thing is after all getting access to the data, having the right data is key. And it does scale very differently, which Dirk is going to talk about later on as well.

We have a question here, please?

Thank you for a wonderful presentation. I'm coming from Amul, and we are a dairy business company,okay. And every day, we process around 40 million liters of milk. And good to see that in your presentation, the question what-if you started with milk powder. So happy to note that. My question is, we are associated with Siemens from last 32 years in the automations, and the world is dynamic and so is the Siemens. So I think it's very dynamically, everything is changing so fast. So how to keep pace with these things, once we adopt this thing, after 2 years, we come to know a new thing has come. So how to keep pace and keep on adapting this thing. We know there are benefits of automation. We know all these things what you shared. How quickly we keep pace of these things and adopt to these things and also see our return on investment is maintained?

Go ahead

So thank you, first and foremost, and thank you for the trusted partnership that we have. So it's a very good question. Obviously, the digital world is working much, much faster. The way we believe is you have to experiment -- run the certain experiments and see what actually really works. In particular, the earlier question with regards to GenAI, it's still very early days. But what we know is if you are one of the first to deploy and see what is working, what is not working, you have to learn like a learning organization. It also goes back to the sustainability question, then actually you can -- you can make this work. And having us to work together also together with our ecosystem because we happen to work with all the major technology companies in the world from NVIDIA to Microsoft to Amazon and also smaller companies, quite frankly. This is my -- this is our daily job to identify what are technologies that are very important for you in the industry to be knowledgeable about and that we think may have an impact for you. So that's why AI is coming your way, but let me be very clear. Today, having a model does not do the trick really applying it in production and getting the savings and the efficiency, that's where the value is being created. And that's where we partner with all of you in order to make that translation, if you like, from technology into scalable industrial use cases work on a daily basis, and that's where we explore together. Sunil?

Yes, I would agree. I mean I think answering your question specifically, it is more an evolutionary process rather than a revolutionary process. And for every single development improvement, there has to be a business case. And unless you have that, you will not implement it. So as we have been doing with Amul over the years, every single suggestion, every new technology will provide you the benefit. There will be a business case for it and only then it makes sense for you to implement it. And I think finally, at the end, the technology is the enabler, but finally, you're interested in the impact. Where is actually the business impact for my business.

Do we have any more questions, we have 2 questions here, one here. Can we get a mic, please? There's one next to you.

I'm from [indiscernible]. Initially, I was working in a PLC controlled machines having a lot of Siemens instruments and accessories. And Siemens has a good result in the machines. Now I'm in training center, one thing I came to learn that your cybersecurity attacks. I am from Ministry of Defense, a lot of attacks from the cyber side that is from Pakistan ISI agents to the ministries. And we are facing a lot of challenges to it. How Siemens will help to avoid these problems?

So I think cybersecurity is an issue, and it is an even greater issue, particularly when you get into automation and remote monitoring, et cetera. Answering your question, I think it's -- what we can do is go specifically into the plants, into the areas, do audits over there, make very clear, identify for you where the vulnerabilities are, make that visible to you and then come with solutions that can actually resolve those risks for you. And this happens not only at a macro level, but right down to the machine level as well, individually, but also collectively. Going back to the point that Peter showed earlier, we are looking at Siemens Xcelerator, which is basically 1 platform that connects all the devices onto this 1 platform. And it is here when you have 1 central source of truth with all the data coming into it, that is where you can provide cybersecurity solutions there. And this is exactly what we can do across all the verticals, irrespective of whether it is a food and beverage or Amul plant or, for example, even a defense establishment over there.

And I would invite you outside the innovation hub, we have a couple of booths where we talk about cybersecurity, in particular about OT, so operational technology, cybersecurity because obviously, there's a lot of solutions for IT cybersecurity, but as you very well are aware that OT cybersecurity is very important as well. So combine it there and there we have a couple of solutions and approaches that we can share with you, thank you.

We have more questions there. Can we get the mic please?

Hi. My name is Sharath. I'm coming from Grasim Industries. My question is regarding the Siemens effort that I have seen with very good presentations. And my question would be where is Siemens now in this Metaverse the platforms? In the use cases, what are the sectors that we attack and where we have deployed our use cases in the maturity levels? And what is the target year? Like how many years it will take to get it to maturity as per the Siemens, where we can able to deploy in all the industries where we would like to have?

Thank you for your question. The industrial metaverse, as I said, is nothing that you switch on from today over tomorrow, but this is something that is emerging. That's the first statement. Usually, the use cases, that's exactly why we believe in the industrial metaverse, right? Industry because we have an ROI, so return on investor as opposed to if you take the consumer metaverse, which really hasn't taken off yet because who is willing to pay a lot of money just to be in a virtual world that doesn't do the trick. So you have to get some savings out of it. That's the P&L conversation. So the use cases we find is threefold. Number one, it's an engineering and plant design. So wherever you look at building greenfield factories where you can already simulate them in digital space where you can look at the specific lines and see what combination of machines in which flow implementations would they be organized best, you can imagine very easily of how much faster that is to be done in the digital world as opposed in the real world before it's even built. So you can run all these what-if permutations in the thousands as opposed to having to do it once. Second is with regards to down to the line worker, really simulate of how that is actually really working, material flow, the very respective things that are happening there. And then the last one is actually once you have built a digital twin that's up to date, you can use it for daily operations. So that's for troubleshooting. And in particular, bringing different people together, again, at the innovation hub, we're going to show you one example where, for example, if you have the local maintenance worker on-site and then the technician who's an expert from another country say, who's actually joining you in order and assisting you to rectify the problem in a very easy way. These are the use cases that are usually getting you better ROIs with better uptime, lower maintenance cost, better productivity. Those are the ones. The industry is, by and large -- to cover your second question that I am using that are used in that are the ones that have very high CapEx investments. So batteries, for example, pharmaceuticals, these are industries, if you think about their plants that they're building, they are massive. They are usually a couple of billions. Usually, they are under intense time pressure and -- but again, battery manufacturing, we need them now, not tomorrow. So therefore, if you can do it in the digital worlds, we can do it much, much faster, so you save a lot of cost because less CapEx. We can do it much, much faster. So these are the industries that we see the most emergent. But to be honest, pretty much every industry that we talked to, and we just had a report published where we asked 900 companies where 80% of them said they increased their investment into the industrial metaverse technologies, such as digital twins and so on. Usually, they are across all sectors, including automotive, electronics where that can be applied. Anything else?

Just to add semiconductors is a big one as well.

Yes. It's another very high CapEx element. Yes. Thank you.

Okay. Thank you so much. We are sorry we are short of time, so we won't be able to take any more questions, but our exports are there outside in all the exhibits if in case you have anything specific, some of them can be answered there as well. Thank you so much, Peter, for joining us today and answering all these questions as well. And thank you so much to everyone who joined us for the LinkedIn Live as well. It was wonderful talking to all of you. But now with this...