Walmart Inc. (WMT) Earnings Call Transcript & Summary

Good afternoon, everybody. Thanks for joining us. My name is Edward Yruma. I'm KeyBanc's Internet retailing analyst. We're really excited today to have this fireside chat with Suresh Kumar, the Chief Technology Officer and Chief Development Officer for Walmart. I know many of you are familiar with Walmart, but I think this is a fascinating business that really has been about innovation since the inception. They've innovated with concepts like the Superstore with innovations internationally and now really, in our opinion, becoming a real innovator in use of technology and being an omnichannel leader. Suresh has a fascinating background. And I think as you guys are going to hear with this fireside chat, is going to bring a lot of energy to the business. There is the standard disclaimer that's provided, I think that is also on the IR website. [Operator Instructions] We would ask though that this is really a technology-focused discussion today and that we not touch on the quarter right now. So with that, Suresh, thank you very much for joining us.

Thank you so much for having me. Really excited to be with you virtually.

Yes. That's great. We'd love to hear a little bit about your background. I know we saw you at Analyst Day and some of us have heard your background, but maybe for the broader audience, I think your background as a technologist at heart, is super interesting and important asset to Walmart. Would love to hear a little bit about it.

Sure. I've been with Walmart now for about 2.5 years, really loving it all here. I've been in technology all of my career. I actually did my PhD in aerospace engineering and then being on the -- on -- in computer science ever since then, started off first with IBM, then spent a bunch of time at Amazon. Then I managed the cloud infrastructure for Microsoft for a few years, for about 5 years. And then I was at Google when the Walmart opportunity came by. It was so compelling and so interesting that I decided to come be at Walmart. And I've been here ever since, I manage all of the technology for Walmart across all of its segments.

I guess just to start, and certainly, I think it is a good segue from your background. You guys have made some significant shifts, you moved to cloud. Can you talk about your overall data lake and cloud strategy? And then kind of broadly speaking, how should we think about your data center footprint?

Absolutely. So look, the cloud is central to our digital strategy. It's the foundation on which we are building our customer experiences. It's foundational to our data and analytics. And it's based on which we are building all of our ML and AI models, which are really impacting every aspect of our business. So if you actually take a step back, there were a lot of changes that are happening in retail. Many of them are disruptive. In fact, I like to think of this as sort of the third inning or the third disruptive cycle in retail. And its technology is there. And we really want technology -- we want to position technology so that Walmart is a leader in this retail disruption. That's not only already happening, it's actually accelerating because of COVID. And cloud really becomes a central partner. It's a foundation, like I said. We have actually built a very unique hybrid cloud. We have got our own private cloud, and we combine that with sort of the best of public cloud. And we've also got a very extensive edge network. And we bring it all together in this layer that we call WCNP, the Walmart Cloud-Native Platform that allows us to be able to take workloads and to be able to seamlessly move them around this mix of public and private cloud. And so we believe that this is something that gives Walmart a very unique edge, because it's purpose-built for what we are trying to do. We talked a little bit about data. We've actually moved over 150 petabytes of data into the cloud. And this is allowing us not just to go a lot faster and to get deeper insight, but it's also allowing us to unleash the potential of AI and ML on all aspects of the business. So it's very, very exciting. Cloud is really the underpinnings of all the digital transformation that we are pushing to.

Can we click down on that a little bit more and kind of thoughts around public versus private cloud? And then maybe just stepping back, I think you guys have publicly disclosed that Sam's and eCom have moved to cloud. I guess what's still left for international and U.S. superstores?

Right. So the way to think about public and private cloud is that ultimately, we want to create an environment where we take our workloads, whether they are data-intensive workloads, whether they are ML workloads, whether they are customer-facing workloads. And we want to put them in those environments that are best suited for that particular type of a system or that particular type of a workload. So we use the best of the public cloud for things like elastic capacity to be able to burst up and down. We are actually getting into the holiday season, so we need a lot more capacity. We use the public cloud to be able to do that. We also use the public cloud for a lot of the best of breed SaaS capabilities, like specialized hardware for ML and AI as an example. And then we use our own private cloud to be able to run a lot of the steady-state workloads, the static workload. And we use edge to be able to push all of the latency-sensitive workloads. So that's how we think about sort of the difference between edge, private and public. And in terms of my -- question on ongoing -- it's an ongoing process. You're right. All of our e-commerce today runs on the cloud, all of Sam's runs on the cloud. The main focus really is to start building out a lot of new capabilities on the stack. And that's why we are really focused on making sure that our entire data estate lives on the cloud because we can then use that to run advanced analytics. We can use that to run ML and AI. That whole thing is going to be done by the end of the year. And then beyond that, we are going to be looking at opportunistically, what are the things that really need to reside on the cloud because we don't necessarily want to move everything just for the sake of moving it.

Yes, and to that end, I believe at Analyst Day, you were kind of highlighting some of the early wins with machine learning. I think you talked about markdown optimization, I think you highlighted facilities maintenance. I guess just stepping back from that, though, how can you create a more personalized consumer experience with machine learning? And then over time, do you think that, that more personal experience will drive better sales and profitability for the business?

Yes, there's absolutely no doubt about it. I think ML and AI are going to profoundly change the way in which we not only serve our customers and the customer experiences, but it's also profoundly changing the way in which we actually do business on the back end. So for those of you who are not there, the 2 examples that I talked about around using ML for markdowns, that one particular effort alone, saved us over $30 million. And that was really an example of ML and AI helping us do our business better. Same thing with facilities maintenance also. And that particular thing actually saves us over $40 million a year. But when it comes to personalization, I think one of the power of ML and AI is that it can allow you to create personalized experiences at scale, something that we had not been able to do even just a few years ago, right? The kind of things that we are now able to do using ML and AI, using the models, this would have been unbelievable, even just 5 or 10 years ago. But I think really thinking what makes it powerful, it's not just the models, right? So we can -- I'll give some examples about sort of the personalized experiences that we are able to create. We do something called predictive basket. So grocery customers, typically, they go -- they buy 30-plus items, right? So sometimes when I go to shop, I forget a few things. And then my wife says, hey, you forgot the avocado. I actually don't eat avocado, but my daughter does. But this is where ML and AI actually come in because we can look at your history, we can look at the preferences, we can know the fact that you typically shop for avocados. And then predictively, we can create this quick add-on experience. It's all possible not just because of models, but it's possible because of the power of the data. And Walmart is uniquely positioned more than anybody else, because we have sort of that end-to-end view of the data, right? So we know you as a customer, your shopping habits not just online, but also inside the store. And we are in a unique position to be able to pull all of that to create a personalized experience that is tailored for you, that actually cuts across all of these different channels. That is where really the power actually comes in. And -- but it's the model also. For example, we just announced that we bought a company that is into virtual fitting. So just think about it, you can take a piece of clothing and an apparel, and using ML, we can virtually drape it on different types of models. And in fact, you can put your own photo and ML will actually drape the clothes on you. It uses similar technology to terrain-mapping. But it becomes powerful because you combine that with Walmart data. And I think that is the exciting part of it. It's going to have a very profound effect -- no, it's already having that, and it's going to continue to have that going forward.

Doug has always impressed us with his embrace of technology and being kind of forward thinking. But as a technologist, is it hard to get buy-in from your other operating partners, given that so many of them are merchants that have worked their way up to the ranks? Like how do you help them balance kind of the art of retailing versus the science? And particularly as you start thinking about things like AI?

Yes. I think the power of AI is to actually help you, whether you're a merchandiser or whether you're an operator, make your job that much more effective and that much more efficient. So I'll give you an example. We are starting to build out the ability to be able to do assortment planning in an omni way across -- just think about the complexity of this problem, right? So hundreds of thousands, in fact,millions of SKUs that you now have to figure out which product needs to be in which location, how many of them for phasing, and then how do you manage that in a much more dynamic way. Of course, with the art of retailing. But what ML and AI allows you to do is to bring all of that information together and to be able to synthesize it and to be able to gain insights into that. That you can act on. And I think that makes our merchandises that much more effective and that much better at what they're doing. And they love it. We are starting to grow on our tools and experiences. We rolled out something called Me@Walmart for our associates. We're doing something very similar for other corporate associates as now. And as people start seeing the power that these systems can bring them, they just become better at the jobs that they're doing.

Zooming out a little bit and thinking about it from a senior management perspective, how do you think technology and data tools have enabled you and the other senior managers to better manage the business? And I guess, we think a lot about agility. Do you think that this is helping Walmart become more agile?

Absolutely. I think we have been able to unleash the part of data, not just to better serve our customers, we are able to make a lot more decisions faster. Ultimately, we have a lot more -- we operate a lot more efficiently. I told you about the Me@Walmart, this is an all-in-one mobile app that we have rolled out for our store associates. It combines ML, it combines voice, it includes camera and vision. And it basically simplifies tasks for our associates so that they can spend more time helping our customers. So this is out in the field, and this is one example of how we can -- we're using technology to go faster. But it's not just over there. It's in areas that normally would not think of. We are now closing our financial book in 3 days, almost half the time that it used to take us before. And you can imagine the amount of complexity that we have got across Walmart, right? So being able to pull all of that together and to be able to close our books basically means that we get better insights into our business, and we are able to make decisions a whole lot faster. So efficiency, productivity, leading to better insights, I think, ultimately is making us be a lot more nimble and we can react and we can serve our customers a whole lot better than what we were able to do before.

I'd love to dive down a little bit into the tech stack. I would love your perspective on an e-commerce software strategy, in particular as it relates to kind of what you want to do in-house versus your partnerships and your examples of like using ATG or VTEX and LatAm? And then kind of broadly speaking, your push to integrate other e-commerce providers, software providers in the Walmart marketplace, Shopify, BigCommerce, Adobe Commerce?

Right, exactly. So look, we have built a world-class technique. We want to make sure that we build all the strategic parts of the technology all by ourselves because we believe that, that -- competing -- that's a competitive differentiator for us. So as part of leading this retail disruption, we have been building out our technology organization, all of our U.S. e-commerce business is on our own platform. We talked about the whole core platform. So this whole notion about build versus partner, it really comes down to a few things, right? So given our scale, we want to build and we want to focus our tech on areas that are core to our business, where ownership actually gives us the ability to be able to adapt the software to our business needs, and especially where there are really no good commercial automates. So on -- the converse is that when rolling out our own software is prohibitively expensive in some areas or markets because they have got some very, very specific market requirements. Then we'll leverage commercial software and assuming of course, that the software can actually scale to what we need. So -- but having said all of that, where we are taking the technology stack is that we are building our software in such a way that we build these as reusable services that can be leveraged in multiple markets. So Spark Shopper is one example. This was built as a software as a service. It was actually deployed in Mexico first. And then it was used in the U.S. We have now rolled out a brand-new customer-facing app that combines sort of the traditional e-commerce shopping with the online grocery shopping and pickup, all in a very seamless way. And that platform, that foundation is now going to be reused and leveraged and customized for Mexico and for Canada. So the technology stack that we are starting to build out is more around modular services. And by the way, you've talked about external partners, that is what allows us to actually take our technology and now offer it for others as well. The Adobe partnership that we announced, very, very exciting, is something that I'm particularly very excited about, not only is a brand-new revenue stream for us because we are now taking our technology and we are now offering it for others. But we have done it in such a way that through the Adobe partnership, not only other retailers can make use of the technology that we have built for order online, pick up inside the store and those types of omni solutions, but that also allows other retailers to quickly come on Walmart marketplace and to participate in the Walmart product marketplace. So it's not just about building our technology, and it's not just about taking the technology, modularizing it, servicing it and making it available for others, but it's also about kind of creating the overall ecosystem. So everything kind of builds on itself and everybody ends up benefiting from that.

Clearly, COVID has changed all of our behaviors. So many of us are working, shopping from home. I guess what are some of your priorities in transforming your consumer experience management systems? Are you trying to engage with consumers more through social media? And then how do you gauge kind of consumer sentiment and usage of digital services?

Absolutely, COVID has changed a lot of things. As we -- but our focus really in terms of listening to our customers, that has not changed. And clearly, what has happened as we went through -- as we have been going through COVID actually, is that the things that our customers particularly care about, whether it is around great merchandise, value, convenience, those things don't change, right? Whether COVID or no COVID, customers really want great merchandise, great value, and they want convenience. The thing that has become more important as we have gone through COVID is that customers also care about safety. And they want to make sure that the place where they shop and the ways in which they shop, safety becomes an important part of it. So our focus and through technology has really been in terms of listening to our customers, also to provide them mechanisms where the safety aspect of convenience also gets highlighted, right? So whether it is using the payment capabilities for our -- for the fuel pumps, we roll out more Scan & Go in the Sam's Clubs. All of these things, we have pushed our capability to be able to do pickup for pharmacy. These are all stuff that we have heard from our customers in terms of things that are important for them. And so we keep constantly listening to our customers and we use that to close the loop in terms of the features that we roll off. And we do that every place, right? So it's not just listening to customers when they shop online, it's not just about listening to customers when they shop inside our stores or our clubs. We look at what's going on outside of Walmart properties as well. We look at trends inside social media. And again, it's a part of data, right? So we collect all of that, we synthesize it. We've got models that run over it. And that informs us in terms of what the next thing to do is.

One of the questions we received from the audience, if you could talk a little about your data commercialization initiatives and how you can monetize the data. Maybe just zooming out even a little bit more, amortizing that was a big deal for the business. We heard Doug talk about that a lot. How does the relationship with Trade Desk work?

Absolutely. So advertising is a key component of our flywheel, right? Our strategy is actually to offer performance advertising that is very, very unique to our advertisers. And it's unique because we are the only place where we can combine insights from -- in terms of what our customer preferences are and our customer behavior is, not just online, but also offline inside of our stores. Nobody else can do that, right? And what this allows us to be able to do is to be able to allow our advertisers and our suppliers to be able to connect with our customers and to be able to draw insights in terms of their shopping behavior, what products don't work in base, but nobody else can do. And that -- and so that's the reason why advertising becomes a very important part of how we allow our advertisers to be able to connect to our customers. And you talked a little bit about DSP and about Trade Desk. Trade Desk is our -- is where we are launching our demand-side platform, or DSP, with Trade Desk. And this basically allows advertisers to be able to reach customers on properties outside of walmart.com as well. And so think of it, let's say, that you are Pampers you want to be able to reach your customers. Your typical customer is a young mom with a small child. She might be going to some other location like Scary Mommy. And so you want to be able to reach out to your customers through that and so we enable that through things like the Trade Desk partnership. Data obviously, I keep talking about it, it becomes a very, very key part of being able to do all of this. And our data insight are very key for our advertisers and our partners, our suppliers to be able to figure out the shopping -- the needs of our customers and to be able to then also figure out how to better craft their products to be able to best serve them. And so that's how it's all coming together, and it's really just part of the omni flywheel, if you would.

How hard is it to attract top technology talent to Walmart? And how do you become kind of high in the stack of employers' choice?

We are already very high in being a top talent attractor. We are able to attract really great talent from pretty much all parts of the industries, different locations. And I think the main reason why we have been very, very successful at being able to attract really great tech talent, is that people get excited about the commitment of -- to the purpose of save money and live better. But it's also about the scale, coming -- being a technologist at Walmart means that you get to work on problems that are very hard, that are -- I keep talking about data, ML, all of these things. These are not just hard problems, but we have problems where working on those can have huge impact and we can have a huge impact at scale, right? And you combine that with purpose, which is really about save money, live better. That combination is magic. And I was attracted to it. That's the reason why I came. And that story is very, very compelling. We can attract, and we continue to attract, talent through all different -- from all parts, right, whether they are data scientists, whether they're full-stack developers, whether they are front-end developers, you name it. Walmart is a fantastic place to come and work, and we are seeing that all the time.

In one of your comments, you mentioned Walmart Pay, I know I use it. You guys were kind of early in implementing digital wallet in store. I guess just assessing it though, kind of what's worked and what hasn't? How can you increase usage? How does the firm fit in? And would you ever use Apple Pay?

So look, I think when it comes to whether it's financial instruments, whether it's payment instrument, the primary thing that we focus on is what do the customers want. And one thing is very clear, our customers want a lot of choice, right? And that would -- and some of them want to be able to pay immediately, some of them want to be able to pay an installment, some of them want to make use of different payment instrument. So that is the reason why we offer Walmart Pay, we offer a firm. All of these things are ways in which we serve our customers in terms of what they want. So overall, we continue to keep looking at opportunities based upon what our customers want, but it also needs to make sense in terms of the overall ecosystem that we are trying to build. And largely into the business strategy that we continue to follow, which is really starting with the customer, focus on the customer and make sure that it also works in terms of the larger strategy. So you will hear us as we continue to evolve, we'll continue to make changes to it. And as we make changes, you will hear about it.

You also touched a little bit about in-store checkout technology. I know you guys were also early in using mobile checkout. I remember doing this at the Sam's prototype a number of years ago. I know in some instances, if a superstores as Walmart+, you have mobile checkout. I guess what prevents you from using it more broadly? And then I guess, do you think that cashierless stores are the future?

So again, I think the main thing is really about listening to our customers and reducing friction. And as far as checkout is concerned, we are trying to make checkout as easy as possible where the customers want it. So taking customer-first lens in technology, whether it is in Sam's or in Walmart, one thing became very, very clear, customers don't like to stand in long lines at the checkout line. So that's the reason why we deployed, we built and deployed Scan & Go. And it solves a very, very big customer pain point, which are available in Sam's Club and is also now available for Walmart+ customers. And you can use this to check out as you are shopping. And then when you come to the checkout line, you don't have to stand in these long lines. It's a great benefit to our customers, they love it. Not everybody wants to always use all of the different technologies. And so when you think about cashierless stores versus hiring cashiers, different customers end up having different preferences. So the excellent -- that mobile options, checkout options resonate, those things, we are making it available. There are other options that still involve cashiers and we are trying -- we will have that. We are making our associates more effective so that they can spend more time helping out our customers, we will continue to have all of these things.

Can you talk a little bit about blockchain? I think you guys even touched on that at a shareholders' meeting or it was the Analyst Day, but how has the use of blockchain helped with supply chain? And then where else in the enterprise can you apply blockchain technology?

So blockchain is another technology that I'm very, very excited about. We use it primarily in terms of food transparency. It's actually for leafy greens during the production phase. And basically, what it allows us to do is to be able to transparently track the entire -- from production onwards. And so if there are industry recalls, you can very, very quickly identify if Walmart received product from the impacted source. And so during our investigations, recall, we can narrow the scale, we can narrow the scope on those customers, and we can very quickly take action. So that's a very common area, and we will continue to double down on that. But we are also starting to look at blockchain in multiple different areas as well. Anywhere where we can look at blockchain as a mechanism to be able to automate the transactions between suppliers, carriers, logistics, those are all areas where we'll continue to use blockchain. Regeneration is another one, right, so where we can calculate the carbon footprint. Sustainability is a big thing. Factory audit, sourcing around ethical sourcing, circular supply chain. Lots and lots of different areas where traceability, transparency and ability for us to be able to chain together multiple different events around a particular product or a particular item becomes very, very important. Blockchain is going to continue to evolve over there.

One of the questions we got from the audience is about how has digital transformation changed your technology choices in data and analytics? Are more of your databases and analytics moving to the cloud or shifting to newer types of data architectures?

Absolutely. I told you, right? Data is one of the key things that we are actively moving to the cloud. We've already moved 150 petabytes of data. We want to make use of the capabilities that cloud allows us to be able to leverage. So in particular, by moving data to the cloud, we can run our normal antics a whole lot faster, 23% faster and gives a better experience as well. It's -- because it's scalable, it's elastic, it costs less because we don't need to have these massive data footprint that we don't need it. But the most important thing in my mind is really the fact that we can do advanced analytics, and we can run ML workloads on it a whole lot better than we can do it on a monolithic on-prem database instance. So that's why we are kind of all in, in the sense that all the things that -- where we need to run advanced analytics and ML workloads, we are moving all of that to the cloud.

I know this is kind of a critical time at your business, heading into holiday and the retail analyst community were all focused on markdowns and near-term conditions. But I guess just I'd love to get your longer-term position. Thinking -- putting on your technologist hat, when you think about what will be the most disruptive technology over the next 5 or 10 years, what do you think it will be? Will it be voice? Is it AR? And then probably just as a final question for me, how do you help ensure that Walmart can have the foundational work done so that you're ready to meet some of these new challenges?

Yes. So I definitely think that any technology that ultimately reduces friction for our customers, makes it more convenient for them, in the end does more trust, make it safer, these are the technologies that are going to continue to have an outsized impact as far as retail is concerned. That's on the customer experience side. And any technology that helps us be more efficient, be more nimble, will allow us to generate insights faster and to be able to act on them, those are the technologies that are going to continue to have a big impact when it comes to how we run our business. So if you think about it in these 2 axis, on the first one -- in fact, on both of these, I think, ability to handle large amounts of data and to be able to reason over that data and that's where ML and AI comes in, I think that is going to continue to happen, right? So there is no girth of the kinds of use cases that we can have with advanced ML and AI models. When it comes to reducing customer friction, making shopping easier, better, even more enjoyable, certainly, voice is a very natural extension, right? So we started off with desktop. And now we have got really, really powerful phones. But even that, I think, over a period of time, the most natural way in which you are going to interact with a system that's out there, including for shopping, is going to be through voice. And voice is going to continue to become a very important part of it. We are already seeing that with our Sam's. We rolled that out for our associates. And our associates just love the feature where they can -- whatever information they want, they can just ask, right? So they don't need to go to the backroom and type something and try to find an answer for it. On the shop floor, they say, hey, how many items are there in the backroom, and it will just tell you and you know what to do about it. So friction -- anything that reduces friction is good. And voice reduces friction. Therefore, I think that's going to continue to have a big impact. Yes, VR is very interesting. I think AR, we are already starting to see the impact of that with our associates, right?we deploy something where it helps our associates, it guides our associates in terms of how to stock, restock items on the shelf. And it guides you to which shelf and which location of the shelf. So it's again about reducing friction and creating efficiency. With our customers, I think the example that I gave you in terms of virtual fitting. That's another example where you don't have to actually go buy an item before you figure out how exactly it's going to work. Think about AR for furniture, right? So you can take the furniture and you can place it in your living room. Let's say, you're trying to buy a tent and -- for your next vacation, you want to see how good it is. You don't want to actually buy it and try to set it up and then find out that it's not working for you. AR/VR becomes very important for that. So I think these types of technologies are going to continue to evolve, but I look at it primarily from, is it reducing customer friction, is it making it easier for them to shop. And on the back end, is it allowing us to drive insights better and faster and be able to reason our data more effectively.

Well, with that, we and others, I'm sure, on the call, hope that your app and your analytics capabilities and all these great things you have in technology stack allow us to get all the toys in our kids' Christmas list this Christmas without hassle, without friction, as you guys always do. So Suresh, thank you very much. For our audience, thank you for the questions. If we didn't answer your question, please feel free to e-mail the Walmart IR team. And thank you very much for your time this afternoon.

Yes. Thank you so much for having me. It's great talking to you and to be on the call with you. Thank you.

Thank you.