Jack Fiedler, the vice president for digital transformation of the global supply chain at Lenovo
Lenovo is ranked tenth by one leading analyst firm among a list of global companies with exceptional supply chains. Based on an interview with Jack Fiedler, the vice president for digital transformation of the global supply chain at Lenovo, the word “exceptional” certainly applies. I’ve not seen a company that does a better job of agile planning across an end-to-end, multi-tier supply chain.
Lenovo is a multinational company listed on the Hong Kong Stock Exchange. The company, which achieved $ 57 billion in revenues in its last fiscal year, is the leading global supplier of PCs. The high-tech firm is more than a manufacturer of PCs, tablets, smartphones, and servers. In their last quarter, the division selling personal devices accounted for only a bit more than half of global revenues.
The company has more than 2000 suppliers and operates over 30 manufacturing sites. Factories serve local markets. During COVID, this more agile and resilient model allowed the firm to grow their market share.
The following interview was edited for conciseness.
Steve Banker: Maybe you could start by talking a little bit about the Lenovo supply chain and what makes it distinctive.
Jack Fiedler: We’re unique in the technology industry. We run one of the few truly hybrid supply chain networks. We own a significant portion of our network, but we also work extensively with partners. A lot of our competition has largely outsourced their supply chain.
We decided 8 or 9 years ago that to create a competitive advantage, we really needed to control much of our supply chain. That has worked out well for us.
We’ve taken the same hybrid approach from a supply chain technology perspective. We have a lot of in-house solutions that we’ve built for our digital transformation, which is my area of expertise. I’m responsible for the overall digital transformation, including technology. But then we also partner with Blue Yonder and others.
We put a huge amount of focus on digitalization, as many companies have. But I think we’ve taken it to a more extreme level.
We invest a huge amount of time and resources into our people and making sure that we have the best digital talent in the industry and that we’re doing the most innovative things in the supply chain.
Banker: You mentioned an approach to digitalization that’s both in-house as well as being reliant on external software partners. Could you talk more about that?
Fiedler: I’ll start with Blue Yonder, because Blue Yonder truly is the foundational building block for our supply chain intelligence.
We’ve been using Blue Yonder for many years. We have evolved Blue Yonder from being a traditional demand and supply planning solution. We’ve done a lot of customization, with Blue Yonder’s help, to create a digital twin of our entire supply network. We’ve moved from weekly supply collaboration with suppliers to daily.
We have all our factories, both in-house and outsourced, all of our distribution centers, and our transportation network on the Blue Yonder foundational system. We now have complete visibility of our supply chain. And then we’ve layered our own AI on top of that, which allows us to simulate the entire supply chain.
We can run a plan simulation to maximize revenue, maximize shipments, maximize the customer experience, or minimize transportation costs. We’ve now built this AI capability to simulate the entire supply chain. This was a huge effort, but it has been very valuable.
We have continued to build on that foundation. Just last year we finished integrating the sales process into the end-to-end supply chain process. A seller, from the moment they engage with a customer, and all the way through the sales process, can get whatever information they need to communicate with a buyer on what we have available, and what the lead times are, and other similar information. This starts with the initial discussion about what kind of products are available and how the product will be configured. Then a simulation is run and we get an estimated date for delivery. Once a contract is in place, we have real-time visibility on the delivery status. This includes visibility to emerging supply chain constraints. During COVID constraints were popping up all over the place. An iGPU (integrated graphic processing unit) is a current example. Everybody wants to know what the lead time on iGPUs are, and what the alternatives are if they are not available.
We’ve used the Blue Yonder technology, and that digital twin of the network, and the simulations we run, to give the sales team full visibility as to what is available and when it can be delivered. The sales team can go have those conversations, with real-time lead times and even the factory the product will ship from, with customers.
This has been a real game changer for sales. It’s really reduced a lot of sales friction. It used to be that a customer would ask questions, then sales would have to go to the supply chain organization, and we’d have to get that information, and back and forth it would go.
We’ve connected the supply chain end-to-end and made it intelligent. That is what everybody’s trying to do, but we’ve done it from the beginning of a sales opportunity all the way to the delivery of a shipment.
That was made possible because of this investment we made with Blue Yonder and our investment in building our simulation capabilities in the digital twin.
The second thing we’ve done, and this is our most valuable asset, is that 7 years ago we made a big investment in our own intelligence platform we call supply chain intelligence. It started out as a traditional control tower. But then it very quickly evolved into a full intelligence platform.
We have benchmarked our SCI (Supply Chain Intelligence) solution; we looked at all the solutions in the industry. We don’t believe anybody has anything as comprehensive as what we built in-house. We run the entire supply chain from this intelligence platform.
We have full visibility. We have all the connected planning data we get from blue Yonder, all of the product data we get from the product systems, all of the shipment information that’s coming in from the carriers, as well as risk information from Everstream and other sources.
We have complete visibility of the performance of the entire supply chain in one tool. But it’s not just a visibility platform. It provides risk alerts, decision-making, and automation. As an example, if we have congested lanes, the system will automatically flag that we have a potential risk of delay based.
The platform will look at all the potential alternatives and the cost of those alternatives, and it will make a recommendation for a supply chain person to go in and look at the event. That planner can choose to reroute a shipment so that it doesn’t get delayed.
To build this took seven years and a significant investment . This was meant to be an internal tool for Lenovo. But we’ve now got customers that are starting to lease this technology from us.
We are continuing to invest in the solution. We are working to make the platform more autonomous. For example, we’re working on telling the solution that it has a budget. “You have a budget of $5,000,000 and here are some other parameters. Show us the best way to fix the freight delays!”
The AI looks at the potential alternatives and the trade-offs and then spits out an answer. That frees up the logistics team to go work on even more difficult problems.
When the chief supply chain officer wants to review the performance of the supply chain, we start with the KPI dashboards. Then, the tool drills down and looks at real-time performance on late orders or parts. It might highlight logistics jams, manufacturing capacity, quality issues, or procurement cost trends. Really, everything you need to manage the supply chain. This is so much more than a control tower.
Banker: Can you speak in a bit more detail about what you are doing around artificial intelligence?
Fiedler: We have built a number of AI use cases over the last four years that we’ve embedded into the tool. The first wave of those was made possible because of the foundational digital twin capability work that we did with Blue Yonder.
Advanced demand forecasting based on machine learning, for example, is a classic example of the use of AI in supply chain management. But we have taken machine learning further than this.
During COVID there were so many part shortages. We struggled to figure out what we could build and, then, beyond this, what should be built based on optimizing for either cash or revenue or customer satisfaction or other things as well.
Banker: Was this based on a series of Bill of Materials explosions?
Fiedler: Yes, that is exactly what it does. It takes the demand that we have, it takes the orders that we have, it takes the BOMs on those orders and then compares it against the digital twin of the supply chain and says, “What do we have right now? What can we make? And based on our objectives, what should we make?”
And this is not just a solve done at the plant level. A lot of companies can do that. This is a network solution based on the centralized supply visibility and management. It can involve moving parts from plant A to plant B, for example.
We are also using AI to help with customer allocation issues. When critical components are in short supply, it can end up being whichever customer screams the loudest that gets prioritized. That’s not a sustainable way to manage supply issues.
We used AI to create smart allocation. Basically, this allows us to say, “OK, if we want to reprioritize our order stack, what are the impacts if we move customer C from slot 8 up to slot 2? How will that impact other customers? How will it impact our supply chain?
It took a very chaotic area and helped create order. We can now have really good data-driven conversations. The sales team can now make better trade-off decisions involving their customers.
We also recently created a machine learning capability that helps us better predict when suppliers will make deliveries to us. During COVID, all of our suppliers got very conservative because all their suppliers got very conservative. The accuracy of the delivery dates we were getting went way down. Basically, we use AI to go say, “Who’s hedging?”
There was unpredictability during COVID from key suppliers on shipment dates due to the dynamics everyone was trying to navigate. Using AI, we were able to predict when the delivery would occur. This allowed us to plan our manufacturing capacity more effectively.
Banker: You know, if you were to talk to Blue Yonder, they would say they’re investing in the same sort of things that you’ve invested in. So why do it yourself?
Fiedler: A couple of reasons.
Lenovo is a large global business and with that comes some complexity for supply chain software solutions companies. We have many products, many different bill of material structures, and many different business models. We operate in many countries. Supporting the complexity of the business in somebody else’s tool is difficult.
And while supply chain solution vendors are building some of these capabilities, they can’t match all the things that we could do ourselves, or the speed at which we can do them.
We do use their technology and where it makes sense, where they’ve invested in it, we will leverage their capabilities. We practice a hybrid model – we use what the supply chain vendors are really good at, and then we add to it.
Lenovo has a huge research team. Thousands of AI data scientists work for us. Some of these data scientists are among the best in the world. We’ve got the ability to build this stuff very quickly with our own skills.
I’ll give you an example. If we want to change the machine learning algorithm three times a day, based on new information we’re getting from the sales team or suppliers, we can go do that. When you’re working with a partner, and using their technology, that’s much, much more difficult to do.
And so, I think just the bottom line is that the size and scale of our company allows us to make choices surrounding AI other companies can’t make. To be as responsive, as agile, and as innovative as we want to be requires us to use a hybrid model.
Banker: Jack, thank you so much. This is fascinating! I could talk to you for hours.
Fiedler: Thank you.
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