And so I think a lot of it as a company, by setting these ambitious goals, is forcing us to say if we want to be number one, if we want to be top notch in those areas, if we want to keep generating results, how do we get there. using technology? And it really makes us drop our assumptions, because you can’t follow someone if you want to be number one, you can’t follow someone to be number one. So, we understand that the path to this, of course, lies through technology and software, opportunities and investments, but in fact it is a sense of purpose. And if we look at these examples of how we create the technological infrastructure to support these ambitious goals, we ourselves must be ambitious in turn, because if we offer a solution that is also mine, it is an imitation that is not If we have there is no differentiation, it will not help us, for example, to enter the top ten supply chains. It just doesn’t pass the pattern.

So I think at the highest level everything starts with business ambition. And then from there, we can organize at the intersection of business ambitions and technology trends to have these very meaningful discussions and become the nexus of how we put together so many moving parts because we are constantly scanning the technology landscape for new advanced and emerging technologies that can be part of achieving this mission. And here’s how we set it up on the process side. For example, I think one of the things, and that’s also innovation, but it’s not talked about that much, but for the community, I think it’s going to be very relevant, how do we stay on top of data sovereignty and data localization issues? We have a lot of work to do to reimagine what your cloud, private, public, edge, on-premises hardware will look like in the future so we can stay ahead of the curve and competitive in each of our markets while meeting the growing guidance we receive from countries and regulators information on data localization and data sovereignty.

And so in our case, as a global company listed in Hong Kong and operating around the world, we had to seriously think about the architecture of our solutions and innovate in how we can design for long-term growth. but in a world that is becoming increasingly uncertain. So I think in a way there are a lot of drivers, like our corporate aspirations, our operating environment, which is still a lot of uncertainty, and that really makes us look very closely at what the cutting edge looks like. And this is not always a bright and brilliant technique. Being at the forefront can mean going to the executive committee and saying, “Hey, we’re going to run into a compliance issue.” Here are the innovations we bring to architecture so that we can handle not just the next country or regulatory regime that we have to comply with, but the next 10, the next 50.

Laurel: Well, to conclude with another concrete example, how R&D is helping to improve manufacturing in the software supply chain, as well as new technologies such as artificial intelligence and the industrial metaverse?

Type: Oh, I love this because it’s a perfect example of how much is happening in the tech industry and so much going back to an earlier point of applied curiosity and how we can try this. So, especially in regards to AI and the industrial metaverse, I think they fit very well with Lenovo’s natural strengths. We are a leading global manufacturer and now we are looking to move into services as well, but by applying AI and technologies like the metaverse in our factories. I think it’s easier to say the opposite, Laurel, that is, if we — Because, and I remember very clearly that we mapped this out, there is no area in the supply chain and production that these areas don’t touch. . If I think about the example, this is actually a very timely discussion. Just a few weeks ago, at the World Economic Forum, Lenovo was recognized as part of a global network of leading beacon manufacturers.

And this is largely based on the application of artificial intelligence technologies and the metaverse and incorporation of them into all aspects of our own supply chain and production network. So if I take a couple of examples regarding factory quality, we have implemented a combination of digital twin technology so that we can design for cost, design for quality much faster than before, where we can prototype in the digital world, where it is faster and cheaper, and fixing bugs is faster and faster. This way we can update our products much faster. We can have better quality. We have taken advantage of advanced computer vision so that we can detect quality defects earlier. We can bring technology around the industrial metaverse so that we can train our factory workers more efficiently and better using aspects of AR and VR.

And we’re also able to, one of the really important parts of an efficient manufacturing operation is actually production planning, because there are so many thousands of parts coming in, and I think anyone who listens knows how much uncertainty and variability there is. were in supply chains. So how do you take such a multi-thousand-dimensional scheduling problem and optimize it? This is where we apply intelligent production scheduling models to keep our factories running at full capacity so we can meet delivery times for our customers. So I don’t want to ramble, but I think the literal answer was that there is no place if you think about logistics, planning, production, scheduling, shipping, wherever we found AI and metaverse use cases that were able to significantly improve the way we conduct our business. And again, we do this internally and as such we are very proud to be recognized by the World Economic Forum as a member of the global lighthouse manufacturing network.

Laurel: This is certainly important, especially as we combine computing and IT environments in this growing complexity. As businesses continue to transform and accelerate their transformation, how are you building resiliency at Lenovo? Because this is, of course, another fundamental characteristic that is so necessary.