Hugo Scott-Gall: Today I’m joined by two of my colleagues, global research analysts Andy Siepker and Monika Budyn to discuss the future of manufacturing in our next installment of our convergence series, which examines five growth themes that are shaping the future of investing. Today’s theme focuses on the technology that is making the factory digital: sensors, software, robots, and cobots, and connectivity. Andy and Monika cover industrials.
That’s what we’re going to be focusing on. I want to say welcome, hello, and thank you both for being here.
Andy Siepker: Hello, good to be here. Thanks for having us.
Monika Budyn: Yeah, thanks for having us.
Hugo Scott-Gall: Not at all. So, let’s get started and talk about the future of manufacturing. So, I’m going to ask you Andy, I hear you talk almost every day about the future of manufacturing. What do you mean?
Andy Siepker: I think when you think about the future of manufacturing, there’s a lot of really exciting things going on. It really is all about automation. So, not only do we think about this in terms of the physical automation, so thinking of the kind of the classic robotics, the movement of goods in a factory or the production of goods but also, increasingly, it’s about digitization, of designs of workflows. So, I’d like to use an example. Think of the modern automobile how it comes to market. So, it’s designed virtually, they simulate the performance of that product in a virtual environment.
They even design and test production facilities virtually before putting in the physical processes that are increasingly automated with more sophisticated automation techniques. And then even the validation of the physical product, comparing it back to the digital world is done as well. And the result is much better products for consumers. Again, sticking with the auto example, if you think about the quality of vehicles, we’ve all seen this over our lifetime, quite dramatic improvements. I think something that touches us all quite closely are the improvements of safety.
So, if you look at 20 years ago, vehicle fatalities on a miles-driven per-basis have actually improved over 35% over that period. So, a lot of that has to do with better quality products. There are also more safety features going into cars. But these are some examples of how automation in the future of manufacturing is evolving and benefiting all of us as consumers.
Hugo Scott-Gall: So, I guess the future is all about automation. But in a sense, certainly in my career in the investing industry, the future’s always been about automation.
So, why especially now? Why are we diving so deep into this?
Andy Siepker: I think that’s a great question. I think it’s kind of a confluence of factors that is leading to automation really becoming more prominent or more important as we move forward. I would just list out some of them. First being the need for productivity. So, if you think about manufacturing and you look at the time series of data in terms of productivity gains that we’ve observed, there was a period of time for several decades where we clipped along at about three to four percent productivity gains annually. Really, over the past decade, this has ground to a halt. So, we’ve seen an industry that’s really become starved for productivity gains.
At the same time, I think manufacturing has always been about efficiency, less waste, really from the beginning. But there’s been a shift from, obviously, more emphasis in society on doing things in the most efficient manner. So, thinking about limiting emissions and waste.
So, that’s shifted the business case or the priority in terms of some of these automation projects. So, it’s productivity gains, it’s trying to do it with less waste, and then also we have a social element or a workforce element where if we look at the U.S. alone, there’s some estimates that over the next decade we’re going to be short two million manufacturing jobs. So, there’s labor shortages. This is because the industry is naturally growing, but also there’s a graying in the workforce and we’re going to need to replace these workers in this aging workforce and we’re just not doing it fast enough.
So, you’re going to actually need automation to pick up and carry that work forward. And then also you have a case where a lot of the solutions that are coming to market or that are present now when we think about bigger automation solutions, so thinking more beyond just the physical automation. Some of these digital aspects are now proven in delivering very clear benefits for customers. So, we think about use cases that really revolve around software like production monitoring, predictive maintenance, and those delivering significant value.
I think the predictive maintenance is one that holds particular promise. Because if you think about the downtime for a factory in terms of the cost, it’s very high, in some cases millions of dollars per hour. To be able to have better up time is something that is clearly delivering value for customers. So, it’s sort of a combination of all those factors, I think, coming together to drive demand for these solutions.
Hugo Scott-Gall: So, what I’m hearing from you there is this is more than just incremental innovation. We’re talking about something bigger. Monika, I want to ask you, if we are saying we’re in — You hear different people say different things. But let’s say Industry 4.0, go back in time, I don’t think they ever called it Industry 1.0, but if you’re saying it’s Industry 4.0 now, do you agree with that? And is this really the future of manufacturing? Is this really a step change, as Andy said, is a confluence of things? Are we really talking about a step change, a meaningful change in the way that stuff is made? Is that too dramatic a statement?
Monika Budyn: No, I think you’re absolutely right. We think Industry 4.0 absolutely has the potential to unlock the step change in productivity. Many are calling this the fourth industrial revolution and we’re really seeing adoption picking up. With manufacturing software investment growing three to four times faster than capacity. Unlike physical automation, which is already quite mature in terms of technology, digital automation maturity varies quite a bit by industry with relatively high adoption rates in areas like autos, but still quite low in heavy industry like oil and gas or construction.
So, the key to Industry 4.0 is bridging that gap between the physical and digital worlds. That’s done through the use of digital twins. In the simplest form, a digital twin is a virtual model of a physical aspect. In practice, digital twins can be used throughout the lifecycle of an asset, from design all the way through post-production monitoring. So, sensors capture data from an asset and feed it back into the virtual world.
Their optimization can be simulated and fed back into the physical world creating a continuous feedback loop. An example of this is a sensor that picks up a deterioration of a part in an assembly plant, for example. That information flows into the digital twin, which can assess the severity of the problem. And maintenance can be deployed at a convenient time without disrupting production. So, that’s a fairly simple example. But digital twins can be applied on a much larger scale. Think entire production facilities with digital twin where the entire operation is in a constant optimization feedback loop.
All of this results in greater efficiency, shorter production cycles, improved quality, and overall better asset lifecycle management.
Hugo Scott-Gall: So, Monika, what does this all mean for business models? What does the successful industrial company of the future look like versus the past? What are the areas that we think are most attractive as you slot in the business model? More and more, is it going to be software driven?
Monika Budyn: We think there’s definitely an opportunity for new business models. We refer to these as a service where companies can really exploit all of the data that they’re capturing. They can offer new services such as data analytics, customization, and enhanced after-market offerings.
That last example is particularly important in industrial companies where after market is often a significant component of the profits. In an extreme example, like a razor razorblade model, like we see with airplane engines, for example, as much as 75% of a lifetime value of an asset can come from aftermarket. So, what Industry 4.0 does is it enhances the value proposition the service provider can offer such as predictive maintenance, remote monitoring, or guaranteed up time.
These new types of serve models can be especially appealing in industries where downtime can be extremely costly, just as in an example Andy mentioned earlier. So, think of the loss of production output in a manufacturing plant where a production line has to stop due to a part failure. Or even the disruption something as simple as an elevator failure causes in a commercial building during rush hour. These new models can help address these challenges and minimize the impact to operation. So, we think this creates an opportunity for both an expanded and customized aftermarket offering, depending on customer’s needs.
However, we signal that this is not an unmitigated positive for the service providers. As more data and connectivity can lead to more efficiency, and eventually to a deflationary market.
Hugo Scott-Gall: I think what I’m hearing there, and tell me if you disagree, is that switching costs are going to go up. Customers are going to be more tightly bound to makers because of the relationship. — This is obviously already happening. But the relationship becomes dynamic and enduring versus a moment in time. Do you agree with that?
Monika Budyn: Absolutely. I mean, if the service operator can provide 24/7 monitoring for the customer, that’s a very appealing business proposition. And it kind of ensures the relationship remains for the duration of the lifecycle of the asset and not just for the point of sale.
Andy Siepker: I think, just to add a bit, it’s really an opportunity and a threat. So, on the opportunity side, it’s the ability to be embedded even more into the customer in terms of now I’m selling them more of a service.
I have a product. I’m guaranteeing that it’s going to be available. You’re going to have uptime. So, the best companies will harness this opportunity and the use of data to deliver greater value for the customer, new solutions, better solutions. Whereas there will be some, though, that are at risk and don’t utilize this opportunity to get closer to the customer. So, I think what we’re talking about here is now if I’m running a factory and I have an automation component in the factory, let’s use the example of a compressor, and there’s data coming off that compressor. Now the maintenance intervals are now determined by more predictive analytics rather than just prescribed intervals.
So, you could see a scenario where the companies who don’t come with those new solutions, who don’t innovate in the right way, and really meet customers’ needs, because at the end of the day that’s what it’s all about, are at risk from, as Monika mentioned, deflationary environment or just, frankly, less parts going into these machines.
Because now instead of replacing it every however many cycles or however many hours, you’re replacing it when you need the part because you have insight into when that part is going to fail. So, it is a bit of an opportunity and a threat. We’re optimistic that the best companies in the world will actually find ways to deliver greater value, expand the share of wallet with these customers because of that.
But I think it’s important that we’re cognizant that companies can be complacent of it and it can be a threat, as well. So, a lot going on there. As Monika laid out, these aftermarkets streams are incredibly lucrative, very important to the business model. So, something that’s going to be really important to watch in the future as this plays out.
Hugo Scott-Gall: If software is so important, does that therefore mean that manufacturing hardware is commoditized? That is a change versus history of broad high-level statement.
Andy Siepker: Yeah, I think there’s quite a big misconception and particularly probably formed by our consumer experience with technology where things have become commoditized in a lot of cases pretty quickly. Hardware used in industrial applications is much different. This is highly sophisticated, highly specialized, a lot of IP, not only in the product itself, but in the production processes. So, these are products that are very hard to reverse engineer, play a critical role, in many cases, in the processes of manufacturers. So, high levels of precision are often a differentiator. The reason why these hardware companies or these industrial automation companies that are more hardware centric tend to have quite strong levels of profitability, really quite impressive.
So, I think that’s quite a misconception just versus a consumer setting where you do see disruptions happen faster. And also, keep in mind that in a manufacturing setting, you tend to have a lot of inertia in the sense that there’s not as much risk taking. So, you have proven processes that work. So, if there is a new offering that comes along, a competitor, these things tend to be designed in and there’s some hesitancy to try something that’s not as proven.
So, I think hardware being commoditized, we’re definitely not seeing that. It does have some variance across the different products, that’s the higher the IP in the product, the less commoditized risk we see or risk of commoditization. But I think it’s much different than consumer facing goods. And also, I would say hardware is critical when we think about automation. So, a lot of attention gets paid to software that’s opening up new solutions, and rightfully so, it’s very exciting, so that attention is warranted.
But these are really the building blocks, the hardware that we’re talking about here in terms of the automation. These are the arms and legs of a factory, very important. So, just as automation grows, these products will continue to grow. And, obviously, there’s incremental automation, as well, that prevents it from becoming commoditized. So, I think we are not seeing that, really, as a trend. And it’s very important in terms of automation solutions.
Hugo Scott-Gall: So, let’s get a bit more specific on automation because most people who think thematically or even, dare I say, write thematic research all say automation — you struggle to find someone who thinks automation isn’t a thing and they think it’s overstated and actually is about to enter a bear market in terms of growth. So, everybody likes automation. But, Andy, how do you think about winners and losers in automation?
Andy Siepker: I think that’s a very important question and something we think about all the time.
I think in the case of the companies who are supplying automation solutions, the good news is there’s going to be more winners than losers because these are big markets, they’re growing. Again, what we were just talking about, difficult to disrupt, particularly for the incumbents. If you do think about where the tech companies are coming at this opportunity from, they recognize that the new solutions that are being driven by software, they’re coming primarily from the enterprise level. Whereas the more traditional automation suppliers, they’ve grown up on the factory floor, they’ve been embedded in the processes, they have a lot of domain knowledge. So, they’re coming at it from a different direction.
Again, as we talked about, the disruption is likely to be much slower. Again, industrial processes are complex. They’ve been optimized over many years. There’s that high risk of failure. So, that inertia is there when it comes to slowing the adoption of new technologies. So, I think the industrial incumbents are in a good spot. But I do think what we are seeing is to deliver the full solution, you have to have the integration of hardware and software.
The automation companies that have really come up on the factory floor where they live are adding more software to their hardware to create more solutions, deliver more value for companies. Whereas again, the technology companies are coming from more of the enterprise level are generally partnering with the industrial automation companies to bring fuller, more robust solutions to customers. So, I think it’s going to be a happy future where a lot of these companies can coexist together because the opportunities are so big. There are so many niches. There are so many companies with strong competitive positions.
The solutions are delivering value for customers and that’s driving growth in the industry. So, I see disruption being less than people expect and there being a lot of opportunity for many players in the industry.
Hugo Scott-Gall: Okay. So, it just occurred to me that not one of us has yet said robots. And we’ve got to say robots, we’ve got to talk about robots. So, where should we look for automation growth? And please talk about robots.
Andy Siepker: Yeah, robots and airplanes are some of the most favorite topics of me and my colleagues. And you’re absolutely right, robotics is a very significant area growth. You can take it in a lot of different directions here. But I think if you think about the classic manufacturing setting, discrete manufacturing, so assembly of a car, that is more along the maturity curve in terms of robotics penetration. They were really the early adopters of that automation technology.
But still, if you think about emerging markets, there is a lot of growth even there from penetration and robots in factories. But probably more exciting on the robotics front is moving into new applications, new markets. And again, this is all about the innovation that allows you to get there. So, thinking about warehouses. So, picking goods in a fulfillment facility has been very labor intensive. Until recently, you couldn’t use robotics.
But now with the innovation we’ve seen in Vision, which is a very key building block that increases flexibility for machines because now you can see your environment, you can react to it, combine that with robotics, you can now pick and pack with automation. So, you’re seeing quite a bit of growth in logistics in terms of automation and on the robotics side, again with that Vision component.
And I think if you think further out, a massive opportunity, something we’re really just scratching the surface on is robotics in the service industry. We know service jobs, there’s tens of millions of them in the U.S. alone. These are not the most exciting jobs a lot of times. So, robotics, particularly what we call collaborative robots, so these are robots humans can work next to, have a lot of dexterity, there’s no safety cage, tend to use to automate some of these service jobs. So, this is really important and will be a big growth driver for robotics for many decades to come here. And if you think about, again, the need for, we’re going to have labor shortages in a lot of these service jobs.
Again, they’re not the most exciting jobs, so good for automation. I think that’s where you’re going to see a lot of growth in robotics in the future. I would also say, we talked about it quite a bit, but that industrial software piece, particularly digital twins of everything. So, assets, factories, products, the ability to simulate, optimize, have those feedback loops, that’s going to be an area of growth, as well.
It really is Vision robotics and industrial software that are the areas we’re most excited about.
Hugo Scott-Gall: Okay. Time for my favorite question of this series we’ve been doing around convergence, which is the moonshot question. I guess a little bit within the moonshot question is all the things we’ve just talked about, what does it mean for people? Are all of us going to see the benefits of this in our everyday lives? It’s really two questions but they probably are connected. So, I’m really interested in the kind of moonshot. But I am interest in the effects of what were moonshots but are now actual things.
Monika Budyn: I can start here. So, we actually see a lot of exciting opportunities in the consumer space. Not only will product quality improve, but a lot of these applications that we’ve talked about already are trickling down into consumer products. So, take the heartrate monitor as an example. It is essentially the first step towards a human digital twin. Next, Andy’s already talked about the service industry opportunity a bit. But it can also be expanded to use cases in the home. Think of a robot that can do the dishes or that can clean the bathroom.
Another exciting area are dark factories where you can essentially turn the lights off and robots pretty much run the factory. On a small scale, this is already being done. But think of an extreme example and potentially maybe a scary one where you could have robots building robots with little or no human intervention.
And kind of the last moonshot I’ll put out there is autonomous vehicles. This could really be a game changer. The technology for wide customer adoption is probably still years away.
But we see a lot of potential for robo-taxis being widely deployed within our lifetime.
Andy Siepker: I’ll just add, I agree. The future is really bright for society here. And it can be a bit easy to get carried away dreaming about what the possibilities are. But I do think manufacturing, automation in manufacturing, is going to lead to better outcomes in our daily lives on the services front. And even, as Monika mentioned, in a domestic setting. You think about robots doing dishes, for example. So, you can dream of a scenario where the housework’s done by a robot. Your car drives itself. And we all know how much time we waste in traffic, so that time is given back to us. And we all enjoy the benefits of safer, higher quality products that are made with a lighter environmental impact. Who doesn’t want that, right?
And then you think about the professional side, and I think the robotics, I guess automation more broadly, it’s a meaningful discussion but maybe on the negative side is people focusing a lot on what happens with job displacement.
And yes, there will be job displacement. But as we’ve talked about quite a bit already, there’s a lot of shortages in these industries. The jobs that are being replaced are important to think about, too. So, these are typically dull, dirty, and sometimes even dangerous jobs that are being automated. So, we’re going to be able to, as a society and professionals, redeploy those workers in the workforce into knowledge jobs that are more enjoyable and should, as a society, lead to greater innovations. So, very important for growth for all of us in a broader sense.
So, I think it’s going to be really, truly exciting to watch how it unfolds. We’re at this unique area where there’s a lot of innovation. And it will be exciting to see how it all plays out over the next couple of decades and exactly what the potential is. But we see a lot of benefits to people and society at large from these technologies.
Hugo Scott-Gall: That is a very good and encouraging to finish, I think. Lots of change and lots of positive benefits from it, broadly with society, and then, also, obviously, for the companies who are well positioned.
And as Monika described, the business models for the future. So, look, I just want to say thank you to you both. Thank you, Andy, and thank you, Monika, for joining me. This is the last in on convergence series. And it was a very good, upbeat, and exciting way, including robots, to finish. So, thank you both.
Andy Siepker: Yeah, thanks for having us. Our pleasure.
Monika Budyn: Thanks for having us.
