Fostering innovation through a culture of curiosity

When Lenovo set out to transition into a services-led company, they began by looking internally, says Art Hu, Lenovo’s senior vice president & global chief information officer. He also serves as the chief technology and delivery officer of Lenovo’s Solutions & Services Group. To offer products and services that provide valuable business outcomes rather than traditional one-off hardware delivery, the company evolved internal IT capabilities to provide solutions for their customers.

“Commercializing our internal capabilities is what allows us to create that environment or the curiosity because when we shift from delivering a pure technical service into thinking about how to make that really sing in a business outcome context, that’s what really brings this to life,” says Hu.

Making the IT mindset shift from simply offering a technical service to offering an outcome can be a challenge, though. It’s the difference between offering a customer a laptop and offering them the tools to create a workplace environment that empowers productivity, says Hu. Once IT teams make this change to focus on business language and outcomes, they can move in the direction of business value delivery and scalability.

Creating a culture of curiosity that values this shift requires a commitment to a long-term journey that prioritizes research and development (R&D) and finding the right business processes to unleash creativity among employees.

“As you know, innovation starts smaller,” says Hu. “It’s not possible that everything immediately is something that’s billions of dollars and thousands of employees and dozens of countries around the world. You have to seed these things.”

Effectively manufacturing new innovations, especially those that involve emerging technologies like AI and the industrial metaverse, is underpinned by this strong focus on R&D, says Hu.

“There is no place,” says Hu, “if you think about logistics, planning, production, scheduling, shipping, where we didn’t find AI and metaverse use cases that were able to significantly enhance the way we run our operations.”

Hu sees the continued potential of AI, how digital transformation will affect and contribute to the recent adoptions of hybrid work, and the continued adoption of as a service to improve agility within enterprises.

“I think done right, the adoption of as a service, which is underpinned by technology, will actually provide companies that strategic agility and ability to focus,” says Hu.

This episode of Business Lab is produced in partnership with Lenovo.

Full transcript

Laurel Ruma: From MIT Technology Review, I’m Laurel Ruma and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.

Our topic today is building better products and services. Enterprises have found success with internal experimentation—from idea generation to prototype to commercialization, and finally diffusion—because you can test out new ideas before bringing them to market. But connecting internal capabilities to eventual solutions requires a culture of curiosity.

Two words for you: internal innovation.

Joining me today is Art Hu, Lenovo’s senior vice president and global chief information officer. He also serves as chief technology and delivery officer of Lenovo’s Solutions and Services Group, or SSG.

This podcast is sponsored by Lenovo.

Welcome Art.

Art Hu: Thank you so much for having me, Laurel. Pleasure to be on.

Laurel: In 2021, Lenovo changed its structure as a company with an expansion of product, services, and vision. So how does essentially commercializing internal IT capabilities fuel the transition to a services-led company?

Art: So one thing you mentioned that was really relevant from the lead in is around curiosity, and I think of it as really shifting so that we can take the applied curiosity that’s inherent in building products and services within IT and applying that on a broader scale. What do I mean by that? First, within IT we also had to make a shift that rewarded curiosity to say that we’re not just doing a one-off transaction, we’re not just trying to deliver some technical capability, but to put it in a context of the business outcome that we’re looking for. Commercializing our internal capabilities is what allows us to create that environment or the curiosity because when we shift from delivering a pure technical service into thinking about how to make that really sing in a business outcome context, that’s what really brings this to life. And so at the core, that’s really where we got our start on commercializing the internal IT capabilities.

It fits really well with the corporate strategy because on one hand we take Lenovo IT that’s managing and delivering services that meet Lenovo group’s needs. On the other hand, we’ve got our Services & Solutions Group, SSG, that was created exactly to deliver and manage those IT services to our broader customer set. So it was very natural for them to come together and say, let’s have IT and SSG join forces to serve Lenovo not as a unique customer, but as one of many customers using our complete portfolio of services and delivery. So I think that’s the background around why commercializing the IT capabilities really helps with the corporate transformation. Maybe one example here just to help bring that and illustrate that is really around our AI operations, our artificial intelligence assisted operations where we can help our customers analyze the data about their hybrid cloud operations and make recommendations on how to optimize it for a variety of outcomes, whether that’s stability, performance or cost efficiency. And that’s something that we needed for ourselves that turned out to be commercially applicable.

Laurel: I think that’s a really great example because you’re showing the focused view of taking that emerging technology. Like you said, you’re learning it internally, you’re trying to apply it to your own systems and services, and then also you’ll know that your clients will need this as well. And that viewpoint of not being the unique customer is very different when you take it into how many lessons you could learn across your own clients to apply back to your own internal IT systems as well. So it really is a two-way street. It’s not just one way.

Art: Exactly. And I think the use of plural here is particularly important. This notion of going from one where IT and most IT teams are serving just the internal part of their company to go to “n” where we want to serve many more customers, really forces you to think more broadly around the points you said about how do you deliver outcomes that are standard because it’s actually not enough when you’re thinking more broadly through just meet one customer, it’s relatively easy or it has its own set of challenges of course. But when you think about plural customers and those customers you realize begin to span industries, geographies and sizes, that brings another level of complexity to the mix.

Laurel: So what are some of the other challenges that you see as well as opportunities of trying to align technology development with business?

Art: So Laurel, the first thing we already touched on, which is how to shift the IT mindset from just delivering a technical service into an outcome. And it sounds like a small thing because from a physical perspective, if we just take up something as simple as a laptop, if you think I’m here to hand the laptop off to an employee, that’s very different than saying I want to provide the right workplace environment for the employees to be empowered and productive. But that actually is one of the key shifts and one of the challenges into aligning technology development with the business outcomes. And it’s really thinking in terms of the value you’re delivering for the end user, because at the end of the day, it’s down to what happens on the front lines day in, day out for whatever business scenario that you’re thinking of. So that was one of the challenges.

And I think it’s also the opportunity because when you’re able to shift the team into thinking about, ah, I’m not just delivering a piece of hardware, I’m actually empowering the employee, I’m actually making it easier for someone to do their job. I’m making it easier for our partners to work with us and get a single pane of glass and look across the set of services that they’re getting from Lenovo, that’s when it really becomes much more self-starting because then the teams naturally ask the questions. It’s not just let me get something out the door, it’s how do I properly engage and stay engaged with our clients and ultimately the end users who are benefiting from the services that we are doing. The second aspect also I touched on, which is the notion of scalability. As you think about not just serving one customer as an internal IT team, but plural customers, then you also have to elevate your thinking about how you can start to have the concept of platforms and repeatable delivery and reusable solutions.

Here I think an illustrative example would be around our hybrid cloud offering, and it very much started as an internal, Hey, we are trying to navigate the landscape for Lenovo of how do we use public and private cloud in the appropriate places so that we get the right mix of performance, cost efficiency as well as data localization and regulatory compliance. And we did that for ourselves. And it turns out again, there was commercial interest in the marketplace from our customers. And so as soon as we understood other people had the need, we also had to say, well, what aspects of what we did for Lenovo on hybrid cloud are really relevant and what’s the core of what attracts customers to us for discussing our hybrid cloud solutions and figuring out how to make that repeatable?

So a quick recap on that, I think one is shifting the team to think in the mindset of business language and outcomes because that naturally gives an outlet and activates the curiosity in the right direction of business value delivery. And then the second outcome or the second aspect is really the opportunity to think more broadly in terms of scaling some of the innovation. It really forces you to raise the game and ask questions about what’s repeatable and how do you architect for that.

Laurel: That’s really interesting. And with this though, Lenovo has a long history of innovation, clearly with the products that you bring to market. But also, in general, there’s always been that long history of innovation coming from internal experimentations, although the way that you are describing it is a bit different. So how do you, as Lenovo, encourage that kind of internal experimentation, adoption of emerging technologies, in a safe area for employees?

Art: Yeah, what a great question. There’s a lot to unpack there. Maybe I’ll pick a couple of facets as we’ve thought about this and we’re by no means perfect, but I think part of it is the commitment to the journey. So the first one starts at the company level where as a technology company, we fundamentally believe the investments in R&D and in technology exploration, they’re what’s going to drive the long-term future. And so we know we made it one of the top-tier corporate strategic pillars. We’re very public that we want to double our R&D spending in the space of three years from last year. And we’ve made a very public commitment to hire more than 12,000 R&D employees across the company. And so right away, because from our chairman and CEO down to our executive committee, to all of our leadership team, that’s what we talk about.

Immediately employees have a sense that technology is the future. And as a company, we’re committed to this. So we’re putting our budgets, our resources, and we’re putting our money where our mouths are. And so I think that’s number one. So already mentally people understand it’s important, so that helps prime them to have the right mindset. And from there we just reinforce in as many locations and at many levels as possible. So for example, shifting the process, we want to enhance it within IT and my own team. We were traditionally rewarded on delivering large projects. So big transformation that would take multiple years, hundreds of millions of dollars, impact tens of thousands of employees, partners, suppliers across the world, and we still need that. And the insight and the additional step was, well, we don’t want to get rid of that. We also want to add on and shift the mix.

And as you know, innovation starts smaller. It’s not possible that everything immediately is something that’s billions of dollars and thousands of employees and dozens of countries around the world. You have to seed these things. And so we had to be very deliberate about creating processes and on-ramps that said, well, here’s a new way. If you want to try something innovative, we’re not going to put you through the same process of applying for $10,000 to seed something as we would for $10 million on a major corporate strategic initiative. And so that was another signal to the team of offering on-ramps to innovation that are much lower overhead and making it easier and removing barriers. Because what we found also as an insight is not that employees didn’t want to, but if you tried to use the wrong process, if you wanted to use a process geared for scale and volume versus for agility and speed and entrepreneurship, that doesn’t work.

And so not having the right process was an inhibitor. Removing that helped unleash the creativity. The other part I’ll talk about is culture. How do we value and give feedback visibly to employees and our broader ecosystem about this? So we started recognizing we had to not just put resources there, we had to spend time in our management system. And so we would talk up what were the latest innovations. I would create time during the staff meetings to review new initiatives. We would create incentives, and those are financial as well as non-financial, because sometimes it takes a little bit of an adventures award. Sometimes that gets people excited. Other times it’s the ability to have lunch with the business sponsor or with myself or the leadership team to give visibility and say, Hey, we care about this. It’s not just the big wins on enterprise-wide because we recognize the innovative things are the ones that will ultimately be the seeds that grow up.

And so I think we’ve talked about smarter business at Lenovo, but planting those seeds for the smarter business has really required us changing not only the financials, the processes and the culture at all levels to encourage people and help people not just intellectually understand, but see it in action that as a leadership team, we care about that. And so a few examples of things that we’re experimenting with and the word moving along really are around, for example, deep learning, using natural language processing and text classification to in a much more audit automated way, engage with our quality teams, help gather feedback from our global base of customers to improve not only the current but the next generation set of projects. And a lot of these things, the beauty of it when you get it right is you see a much bigger mix of bottom-up. It’s not someone at the top mandating top-down, please go innovate. It’s more, ah, we have the right orientation and it activates the teams to come up with these solutions and experimentations that ultimately grow into very meaningful business outcomes.

Laurel: I imagine it’s the same also with emerging technologies if you have that bottom-up culture of curiosity, people are excited to try emerging technologies like deep learning or natural language processing. So how can being early adopters of emerging technologies help provide a good customer experience and then enhance that trust not just with employees, but also with customers?

Art: Yeah, that’s also a really relevant question. And I think the technology adoption curve is a really good framework to think about in the sense of you have to be thoughtful about deciding where and when you want to really introduce some of the emerging technologies because it comes down to trust. By their nature, there’s going to be a broader range of willingness and acceptance to try new things. Implicit in the action of trying something new is that it may not turn out, especially if it’s emerging. Technology may not be as mature, it may not be the exact fit for what we’re looking for. And sometimes the exploration process means we’re going to find things that just didn’t work. And so it’s important to set the expectations upfront. There’s benefits as well as challenges to work through. And from there in terms of providing the right customer experience and enhancing the trust, a large part of it is making sure we’ve created the right preconditions.

And that means we have to set the right expectations about the likely range of outcomes, we have to be upfront and not over promise things that we can’t deliver. And typically in our experience, this works really well when we have longstanding trust-based relationship with our customers that they’ve seen over time working with Lenovo, whether it’s around or as a service offerings, or some of our professional services offerings and practices that they see we can deliver what we promised, that we’re looking out for their interest. And so this is actually quite interesting in terms of good customer experiencing enhancing trust. A part of it is bringing objectivity. And by that, I think a very specific way over time that you can build that trust with customers is by saying no, meaning… And I’ve had instances with customers where we’ve said, you know what? Lenovo has a great portfolio of products and services, but we’re actually not the right person to do X job. And so maybe we can help you find a partner, but that’s not really within our focus.

And so over time if you can, with a customer show that you can deliver what you can promise, be upfront about where you’re focused or not, and then helping them find the right solution, even if it’s not you or in this case Lenovo, that helps the customers build that trust. And that’s also what helps them be more open to experimenting and generating the learnings. Because ultimately, especially on emerging technologies, a big part of the outcome is learning. And so I think if we can put the preconditions in place, we typically are able to build on that foundation. Now here, I think device-as-a-service [DaaS]. So DaaS is a great example. Today it’s one of our fastest growing businesses at Lenovo, but it was just a seed just a few years ago.

And as we learned with customers, what we were able to do is prove to them we’re able to create value in delivering outcomes and better workplace experiences, better economic outcomes, better management outcomes in terms of their ability to focus on their core mission. And that learning and the willingness to grow with us to redirect more dynamically was really important. And so I think back to your original question of the good customer experience and enhancing trust, it’s really about setting the right context, choosing the right customers who are of one mind in terms of what we’re looking to get out of exploring technologies and adoptions. And from there we’re able to execute and learn together.

Laurel: I feel like some of your excellent answers really just lead up to this question as a natural one, which is how does your focus on research and development keep Lenovo on the cutting edge, willing to try out these emerging technologies as well as even develop in-house innovations?

Art: For us, that starts with the corporate ambition. We want Lenovo, and we’re a Fortune 500, but we really want to be a global technology powerhouse. And I start with that because that focus is the research and development when we have ambitious and aspirational targets of what cutting edge looks like. If you look at Lenovo today, we’re, and we have been the largest PC maker, but we can’t rest on our laurels. In the last three or four years, we’ve really grown multiple growth engines around our infrastructure solutions business, around our services and solutions business. We’ve created new billion-dollar businesses in small medium business, gaming, devices-as-a-service as I’ve talked about. And we’re consistently named in lists as innovative, sustainable. We’re a top 10 supply chain globally. I say that not to brag, but the point is, if we want to do that, we have to be world leading on research and development because all of that is enabled of course by excellent talent, but supported by the right processes as well as the technology and the tools.

And so I think a big part of it as a company, by setting these ambitious goals, it forces us to say if we want to be number one, if we want to be top tier in these areas, if we want to continue to generate results, how do we get there using technology? And so that really forces us to throw away our assumptions because you can’t follow somebody, if you want to be number one you can’t follow someone to become number one. And so we understand that the path to get there, it’s through, of course, technology and the software and the enablement and the investment, but it really is by becoming goal-oriented. And if we look at these examples of how do we create the infrastructure on the technology side to support these ambitious goals, we ourselves have to be ambitious in turn because if we bring a solution that’s also a me too, that’s a copycat, that doesn’t have differentiation, that’s not going to propel us, for example, to be a top 10 supply chain. It just doesn’t pass muster.

So I think at the top level, it starts with the business ambition. And then from there we can organize ourselves at the intersection of the business ambition and the technology trends to have those very rich discussions and being the glue of how do we put together so many moving pieces because we’re constantly scanning the technology landscape for new advancing and emerging technologies that can come in and be a part of achieving that mission. And so that’s how we set it up on the process side. As an example, I think one of the things, and it’s also innovation, but it doesn’t get talked about as much, but for the community out there, I think it’s going to be very relevant is, how do we stay on top of the data sovereignty questions and data localization? There’s a lot of work that needs to go into rethinking what your cloud, private, public, edge, on-premise look like going forward so that we can remain cutting edge and competitive in each of our markets while meeting the increasing guidance that we’re getting from countries and regulatory agencies about data localization and data sovereignty.

And so in our case, as a global company that’s listed in Hong Kong and we operate all around the world, we’ve had to really think deeply about the architecture of our solutions and apply innovation in how we can architect for a longer term growth, but in a world that’s increasingly uncertain. So I think there’s a lot of drivers in some sense, which is our corporate aspirations, our operating environment, which has continued to have a lot of uncertainty, and that really forces us to take a very sharp lens on what cutting edge looks like. And it’s not always the bright and shiny technology. Cutting edge could mean going to the executive committee and saying, Hey, we’re going to face a challenge about compliance. Here’s the innovation we’re bringing about 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, and to follow up with a bit more of a specific example, how does R&D help improve manufacturing in the software supply chain as well as emerging technologies like artificial intelligence and the industrial metaverse?

Art: Oh, I love this one because this is the perfect example of there’s a lot happening in the technology industry and there’s so much back to the earlier point of applied curiosity and how we can try this. So specifically around artificial intelligence and industrial metaverse, I think those go really well together with what are Lenovo’s natural strengths. Our heritage is as a leading global manufacturer, and now we’re looking to also transition to services-led, but applying AI and technologies like the metaverse to our factories. I think it’s almost easier to talk about the inverse, Laurel, which is if we… Because, and I remember very clearly we’ve mapped this out, there’s no area within the supply chain and manufacturing that is not touched by these areas. If I think about an example, actually, it’s very timely that we’re having this discussion. Lenovo was recognized just a few weeks ago at the World Economic Forum as part of the global lighthouse network on leading manufacturing.

And that’s based very much on applying around AI and metaverse technologies and embedding them into every aspect of what we do about our own supply chain and manufacturing network. And so if I pick a couple of examples on the quality side within the factory, we’ve implemented a combination of digital twin technology around how we can design to cost, design to quality in ways that are much faster than before, where we can prototype in the digital world where it’s faster and lower cost and correcting errors is more upfront and timely. So we are able to much more quickly iterate on our products. We’re able to have better quality. We’ve taken advanced computer vision so that we’re able to identify quality defects earlier on. We’re able to implement technologies around the industrial metaverse so that we can train our factory workers more effectively and better using aspects of AR and VR.

And we’re also able to, one of the really important parts of running an effective manufacturing operation is actually production planning, because there’s so many thousands of parts that are coming in, and I think everyone who’s listening knows how much uncertainty and volatility there have been in supply chains. So how do you take such a multi-thousand dimensional planning problem and optimize that? Those are things where we apply smart production planning models to keep our factories fully running so that we can meet our customer delivery dates. So I don’t want to drone on, but I think literally the answer was: there is no place, if you think about logistics, planning, production, scheduling, shipping, where we didn’t find AI and metaverse use cases that were able to significantly enhance the way we run our operations. And again, we’re doing this internally and that’s why we’re very proud that the World Economic Forum recognized us as a global lighthouse network manufacturing member.

Laurel: It’s certainly important, especially when we’re bringing together computing and IT environments in this increasing complexity. So as businesses continue to transform and accelerate their transformations, how do you build resiliency throughout Lenovo? Because that is certainly another foundational characteristic that is so necessary.

Art: Yes. And this really is about how we’re working to make businesses smarter while managing some of the volatility. I think the futures, as commonly understood, are very difficult to predict exactly. And so I think the first part is on education, which is thinking statistically and understanding the future is a range of potential outcomes with likelihoods. And so how do we help the company plan better so that we can simulate what that range of outcomes is likely to be and therefore have acceptable or discussions about the range of risk that we’re willing to take on? Because it’s certainly different across companies, and it’s also different within companies even by having the discussion about, well, what are the various outcomes that we could foresee that already stimulates the executive team to think about resilience, because it automatically says if this happens and if not, and I think we all see with assumptions shifting so constantly the ability to plan better is a very powerful tool.

On the architecture and technology side, there’s definitely things that we do under the covers as well that build resiliency. We can use dual live sites between private and public cloud so that we can have hot cut over and that improves disaster recovery of availability times. We’re able to have containerization technology and rearchitecting our business applications to have more dynamic scaling around when we have peak versus trough periods in business demand. So that’s another source of resiliency in working with an environment with volatility and uncertainty. And then maybe I’ll say something else about agility. I think it actually goes back to what you said, Laurel, about, because you can’t actually exactly predict the future, especially when it’s so dynamic today. And so in addition to modeling and thinking about the range of outcomes, inevitably there are going to be things you just didn’t predict or that are outside of the planning horizon or the planning range.

And so that’s where the agility comes in as a shock absorber for the company. If and when those things happen, how do we build that enterprise agility so that we can stay nimble, that we can scale up and down on the network, that we can go up or down on our budgets, and that we can right size our expenses with the business? And a lot of the practices that work at a technical level in IT. So thinking in terms of agile, working in squads, working in an iterative manner, those are things that we can scale up and apply analogous concepts at the enterprise level so that we can equip the company to pivot more quickly when something unexpected does happen.

Laurel: And as much as we can’t predict what’s going to happen in the future, what technology trends are you most excited about in the next three to five years?

Art: Yeah. And this one, again, it’s hard to narrow it down given the breadth, but I’ll pick a couple here. I think we can start with really around the next level of AI adoption and commercialization. And AI is simultaneously both new and old, because if you think about the origins of AI, it was actually in from a computer science and math theory perspective way back after World War II in the 1950s. So at this point, is AI emerging or not? I think that’s not the right question. It’s really what does the continuing path of adoption and commercialization look like? And obviously what’s been top of everyone’s mind in the last few months have been tools like ChatGPT and DALL-E and generative AI. And so I think we’re getting to the point where we are really starting to see broader applications and to see AI really infuse each part of the value chain and to also think about possibilities that weren’t possible until just more recently.

And so I think the next three to five years on AI adoption and commercialization and the use cases that it’ll come not just in general consumer land, but also in retail, healthcare and other B2B spaces will really make AI even more mainstream. So that’s one area. I think the other one, I’ll talk about digital transformation, but not in the way most people think about necessarily. I think again, digital transformation has been on the newsletters and it’s been headlining conferences for at least the last five years. So it’s not new in that sense. I do expect businesses will continue to adopt those solutions and approve their operational efficiency, engagement and revenue growth. But I think digital solutions and transformation have a lot more to go, especially at the workforce and workplace level in ways that can create avenues of value for consumers and enterprises.

Because typically we think about let’s build new business models, let’s build new capabilities. But now, especially as the world is adjusting to and finding its footing with what hybrid work looks like, I think there’s still a ton of possibility. And we’re going to be very much in the discovery phase of what can be possible in the future of work and digital workplace solutions, because there’s a lot more learning ahead. And when there’s learning, I think there’s a lot of opportunity. So I think this expanded notion of transformation, not just about the roadmap and the big project, but also fundamentally about what it means to run a knowledge intensive workforce in the future. And then finally, I would pick the adoption of as a service, because behind the premise of why I’m picking everything as a service, A, it’s a huge market. It’s going to be in the hundreds of billions with high double digit growth rates.

But fundamentally, why I’m excited about seeing the growth of as a service is I think it goes hand in hand with making companies more agile. When you’re able to consume standard things as a service, A, you’re able to offload that to someone else so that you can focus on the things that you do want differentiation on. And then secondly, that’s what also gives you the ability to scale up and scale down, the pay as you go. When you grow, you can pay more expense and if you need to reallocate, you’re also able to do that. And I think that’s attractive for companies of all sizes. And I think done right, the adoption of as-a-service, which is underpinned by technology, will actually provide companies that strategic agility and ability to focus.

Laurel: Fantastic place to wrap up there, Art. Thank you very much for joining us today on the Business Lab.

Art: Thank you, Laurel. Great questions and great discussion.

Laurel: That was Art Hu, Lenovo’s senior vice president and global chief information officer who I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review overlooking the Charles River.

That’s it for this episode of Business Lab. I’m your host, Laurel Ruma. I’m the Global Director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print on the web and at events each year around the world. For more information about us and the show, please check out our website at

This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a production of MIT Technology Review. This episode was produced by Giro Studios. Thanks for listening.

Learn more about Lenovo’s innovation here.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.


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