Diego Pantoja Navajas: 0:03

It's exciting to see is the reaction from our customers when they understand their, their vendor lead time, predictions, or the, when they see rebalancing capabilities. For us that those recommendations and, and explainability will continue to be key for our success. So, you can expect us to see a lot more investment in that area.

Tom Raftery: 0:25

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Digital Supply Chain Podcast, the number one podcast focusing on the digitization of supply chain, and I'm your host, Tom Raftery. Hi, everyone, and welcome to episode 364 of the Digital Supply Chain Podcast. My name is Tom Raftree, and I'm excited to be here with you today, sharing the latest insights and trends in supply chain. Before we kick off today's show, I want to take a moment to express my gratitude to all of our amazing supporters. Your support has been instrumental in keeping this podcast going, and I'm really grateful for each and every one of you. If you're not already a supporter, I'd like to encourage you to consider joining our community of like minded individuals who are passionate about supply chain. Supporting the podcast is easy and affordable, with options starting as low as just 3 Euros or Dollars a month. That's less than the cost of your latte, and your support will make a huge difference in keeping this show going strong. To become a supporter, simply click on the support link in the show notes of this or any episode, or visit tinyurl. com slash dscpod. Now, without further ado, I'd like to introduce my special guest today, Diego. Diego, welcome to the podcast. Would you like to introduce yourself?

Diego Pantoja Navajas: 1:41

Thanks Tom. Thanks for having me. It's a pleasure to be here. Sure. My name is Diego Pantoja Navajas. I am the VP and GM for AWS Supply Chain, which is a cloud native application that we have launched to the market last year at re:Invent 2022 and GA, or General Availability in April of 2023

Tom Raftery: 2:00

Okay, cool. Congratulations. Brand new products in the market, six months or so. Nice. So tell me a little bit about it, Diego. Start off I guess, by telling me the kind of genesis of the application, you know, what was the thinking behind creating this application?

Diego Pantoja Navajas: 2:20

Yeah, definitely. So as, as you know, AWS Supply Chain was focused on trying to provide customers a different way on how we solve supply chain problems. Basically, we build a cloud based application that provides our customers with a unified view of the entire supply chain data. One of the biggest issues that we have seen in supply chain over the last years or decades has been There's a lot of data silos in supply chain. We have used different systems. So, supply chain data is scatter across a vast network of systems from ERP applications to warehouse management systems, transportation management system, POS data and others. So what we wanted to do is build building application with a data first approach to really help customers onboard and be able to get all that data into a unified data model, a canonical data model and then move all that information into a supply chain data lake that is the foundational component of our application. And then allow us to build modules or features and capabilities, leveraging the information and the data that we have harmonized and, and, and brought from all these network of, of systems and to provide our customers that unified view. One extra benefit of our application is that we believe that in supply chain and of course in many other areas new applications have to coexist with legacy applications.

Tom Raftery: 3:47

Mm-Hmm.

Diego Pantoja Navajas: 3:48

So we are an application that really sits on top of all these other existing applications that customers might have in their in their solutions. And we leverage them and, and leverage the data, and we are able to connect with them and associate that information in a very simple manner. And in that way, we allow customers to think about their own pace in terms of how fast they want to upgrade or update, depending on where they're coming from. If they're coming from a legacy system, they might need, might need to really upgrade to a cloud app-based application if they're in some other cloud applications, how they can continue to update into that newer version of that, of that system. So we really want to complement what they have. We sit on top of of those applications and we help customers to really be able to achieve, those goals. Correct. So we we're excited that customers are reacting, in a very excited way about our application. We have seen customers telling us that, you know, with our application, they can build a new generation supply chain tools and leverage of course the experience that we have Amazon experience that we have in supply chain. And also leveraging our AWS infrastructure to provide the scalability and security that our customers also want to make sure that a, a solution like this one can continue to support their most critical supply chain issues,

Tom Raftery: 5:11

Okay. Interesting. And it, it, it does seem kind of logical. I mean, Amazon have this history, this tradition of taking something that they're already good at, like selling books and then going, okay, we figured out how to sell books and we figured out how to have an online shop. Why not go beyond books? And similarly, okay, we figured out this cloud stuff, why not open up AWS to everyone else? And this seems kind of like a logical extension as well. Amazon has been doing supply chain stuff, as you said, for 30 years and you know, leading the way in a lot of ways because it was, you know, next day delivery wasn't a thing that you could have expected until Amazon made it kind of defacto the norm. So Amazon in supply chain have been there and doing really interesting stuff for quite a long time. So now it seems like that this is Amazon taking what they're already well known for and exposing it to everyone else. Is that a fair comment?

Diego Pantoja Navajas: 6:08

Totally. And, and, and that's our approach when, when we build applications or solutions. Correct. If you see how AWS. Started, correct. Started as a service that was providing to our internal for our internal consumption, correct. To support amazon.com. And then we realized that, hey, a lot of other companies in the world might need these, these capabilities, might need this cloud, they might need these services. So why don't we externalize that for our customers? So you, you, you're correct. So in this case, what, what we realized is, especially in the last five years and post Covid, is that a lot of companies and customers came by and say, Hey. We really would like to learn how you guys being able to navigate and all these different you know, events that happened over the last five years that really have affected supply chains. Correct. We, we have seen from a, you know, trade wars between the biggest economies in the world being, being one of the reasons why some of the, some, some supply chain got affected. We saw many disruptions by natural events. We saw disruptions by human reasons too, you know, what happened in the Seuz Canal or we, there's multiple events. So, and what, but what, one thing that has been consistent over the years is that Amazon has been able to deliver your products at your door at the, at the right time, at the right place, where customers want it. And, and, and that speaks very highly about our capabilities of managing and leveraging our assets in terms of infrastructure, not only the cloud, but al also our warehouses and others that we, that we have and be able to serve our customers. So customers are coming to us and say, we really would like to learn. We really would like to understand how you guys are managing your supply chain. Because after doing a very extensive survey with a lot of our customers, three topics came out of that, that analysis and that we do, you know, you were, we're very, we're very customer centric, and we work backwards from our customer's needs. Correct. So, customers were telling us, you know, today we have global supply chains. We're seeing disruptions and vulnerabilities. We need a resilient supply chain. We need to increase the inventory visibility. Into multiple tiers of our suppliers. And also make sure that whatever inventory that we have in, in our facilities It stays there, to make sure that it's meeting the demand in that region, in that zip code, in that area. We need technologies that can be automated that can accurate make decisions for, for the user in this case using machine learning. They want solutions that are environmental friendly. And also can meet our, our customers sustainability objectives and that also are demanded by their customers. And also we wanna make sure that we have a solution that can be used without having to deploy multiple resources or can be implemented in just in a timeframe that is very reduced that can use repetitive process. And at the end of the day, we can provide our customers . Are are also a very clear roadmap on how we're gonna continue to use advanced technologies to make sure that their supply chains continue to run more efficiently. So, all those points came out of that survey. So we took them and say, Hey I think we have all these different building blocks that, that in, in our company. So we can leverage that. We have the knowledge, we have the expertise, we have the technology. Let's put it together and let's offer this application this cloud native application. and, and that's what what we did. So we're, we're excited about the start that we had. And we have seen how customers love. Eh, it is, it is early days for us, but the customer's reaction has been really positive for us. So we are very excited about that.

Tom Raftery: 9:44

Great, great, great. And you mentioned of course, legacy systems, because most companies will have a legacy system in place already. How well do you play with those legacy systems? You can take in information from 'em, can you transmit information back? Or, you know, how, how do they, how do they work together?

Diego Pantoja Navajas: 10:02

Yeah, look we, one of the first keys, and, and value proposition that we offer our customers is we're really going to extract and transform and load the data into our canonical data model. We we're doing all the heavy lifting for our customers and helping them to make sure that we can get data from all these disperse systems. For us, it doesn't matter where the data is coming from the source, it can be like I said structured data coming from structured systems or structured data or unstructured data. We can leverage and now we're leveraging more than anything capabilities related to Gen AI so we are building onboarding agents that are gonna help us to help even further our customers, to bring that data into our sup supply chain, canonical data models. So, we can reduce the amount of friction that exists when you are trying to associate data from two different systems. And if I am being very, very peculiar here to talk about associating data versus integrating data. You know, we, we, we've been talking for many years about how can we integrate data and it's being very, very difficult for many companies to, to, to integrate that information because there's a lot of mapping. So with Gen AI and using large language models, what we trying to do, or we will do to help our customers to understand the data that is coming in and how we can associate that data into our canonical data models. So once the data is, is dropped into an S3 bucket, for example, we can take the data and, and leverage all this technology to, and make it sure that it goes into our into application in a very simple manner. And, and just by clicking a couple clicks.

Tom Raftery: 11:39

Nice. Nice. And is this a solution that's extensible? As in if, if I'm a company, a client of AWS Supply Chain, can I get a developer portal and add on bits and pieces that are relevant for my company, or is it completely locked down?

Diego Pantoja Navajas: 11:56

Well that's a great question. So . No, it, it, the, the, and there's, there are really, there are things that we can do to help you extend the application. So for example we, we, we do have the capability for our customers to leverage the data in our supply chain data lake to help them use that data for other purposes

Tom Raftery: 12:18

Mm-Hmm.

Diego Pantoja Navajas: 12:19

So the, the data is there. We do all the, all the work to bring the data from all these different systems, and at the end of the day, customers can leverage that information and build any type of pipeline, if you wanna put it away. To move that data to, to feed other systems or to leverage in a, in, in, in a different BI or in a different tool that they want to use for their own purposes. And also we want to make sure that the backbone that we have provided, because it's really a backbone, a cloud native a application. That we, we, we wanted to make sure that the backbone of that, that the infrastructure that we providing to customers can leverage for them to really continue to expand that data for if they wanted to in that in one case, build capabilities that we're not gonna offer in our roadmap in the next six months. They can leverage that data and build them themselves. And the good thing is like we're using the same technology that from AWS that you will use to create a new techno, a new application? Correct. So you can like I said, you can leverage the data in our supply chain data lake to extend the capabilities for application if needed.

Tom Raftery: 13:25

Great. Super. Super. And from a practical perspective, what functionality are you offering to your customers today and, and, you know, coming down the line, what's, what's coming on stream?.

Diego Pantoja Navajas: 13:38

So when we launched the product this year, in GA we were offering our customers first than anything to get inventory visibility across their entire supply chain. That was the number one request that we got from customers is we have customers that say, Hey, I have, multiple number of hearts of, or ERPs, like they say, some of them. All of them are in different versions. All of them are, or, or coming from different vendors because my business really expanded by acquiring other companies over the years. And we really didn't do any, any, consolidation of all these data under one ERP. And it really is a difficult, well, more than any, anything, the difficult, it takes time.

Tom Raftery: 14:21

Hmm.

Diego Pantoja Navajas: 14:21

And sometimes companies want to avoid those steps. So what I'm trying to say we, we, we helping customers to bring all that data from all these different systems, get them a, a complete view of their inventory, being able to use them to balance the network, like I said, balance their supply chain network with the right product at the right place, at the right time based on how we're sensing demand. So one first module that we launched with this application is demand, demand planning. So based on where we're seeing and, and getting this demand for, for these products and sensing the demand, we're, we're at the same time providing insights to our customers to move product, or balance the network to be able to serve those, those, those that demand that is coming from our demand planning application. So a lot of that also has to do with machine learning models that can help you to, to decide if you're gonna have to keep seven days of inventory in one location or 21 days of inventory, or you're gonna have to move inventory from, let's say from the northeast to the southeast because of you're seeing better demand there for that type of product. But at the same time, we do the analysis of making sure that the amount of inventory that we are leaving in, in the area or location where we, where we're putting the inventory in, is going to serve . Or it's gonna give them enough bandwidth to, to, to meet their demand for the next couple days or 14 days, whatever is the period that they decide. So we take in consideration factors like sustainability, CO2 emissions, cost, transportation time, and others that are part of the, the, the models that we have to make sure that when, when we provide a recommendation to our customers in terms of how we do the rebalancing we're, we're, we're looking all these different variables and customers can add other variables as needed based on the, their own analysis as well. And with that, we provide that. And then also one of the biggest issues that customers asked us at the beginning was we don't manage our vendors very well within our first tier we talk about second or third year later, but within our first tier, we don't manage them very well. You know, some, some of them when, when we start looking in terms of vendor, the vendor lead times the vendor lead times that we have for vendors have not been updated in all the time. So the information that we have is outdated. So for a vendor that it's a, a high, high, high vendor or somebody that I need to make sure that I have good information, we have created a machine learning model that is allowing us to understand the performance of these vendors not only in terms of when they arrive or how consistent they have been being, how consistent have they have been in arriving or, or getting the products in within our network, but also going down to, to, to the specific SKU because one vendor can be really good on bringing me one SKU, but really bad on, on another set of SKUs or another set of family products or product family. So we're able to manage all that information. So, by region, by warehouse, by SKU we can we can understand how we going to manage those vendors better. So once the inventory is in, of course that's gonna have a, a significant improvement in terms of a, a, how we fulfill orders because we will have the right product, like I said, at the right time to to make sure that orders and product arrive almost at the same time. And, and, and we can help our customers to make a better order fulfillment processes for, for, for their customers.

Tom Raftery: 17:45

Okay, and are you helping them with shipping and visibility across that as well?

Diego Pantoja Navajas: 17:50

No, we we're not yet in the execution side. That's something that or we, we first wanted to make sure that we provided, the more analytical perspective or help to our customers. We wanted to make sure that we wanted to see the benefits of making that supply chain more, or, or if you wanna say more efficient, smarter understand the data. We, we, we always say that we have taken this data first approach to make sure that we really help our customers to understand where the data is, where are the bottlenecks, where can get the best insights? How can they reduce inventory across the network, and how they can collaborate better with their suppliers. So that has been the focus. That's where the, the customers have been working with us. You know, we will, we will continue to work closely with our customers and if we see that customers wants us to help them in the execution side that's something that we will evaluate at the right time. But for now, we're just focused on, on that, on that, on that end on, if you wanna say, within the enterprise, we're, we're not doing downstream processes to fulfill orders.

Tom Raftery: 18:57

Okay. Okay, cool. You mentioned of course, as well Generative AI and the fact that, you know, you're using it for things like associating data. Are there other use cases of it within AWS Supply Chain?

Diego Pantoja Navajas: 19:11

Yeah. So Gen AI is evolving, you know, very fast. Every day you learn something that's new model or new capabilities. And one of the things that we, we have done at, at launch this year is we provided a layer of ML power explainability, for the insights that we generate. And that has been very powerful for our customers to contextualize the data that they're seeing for the first time. They're saying, oh, now I get it. Now this number, you know, means this because of that. And that was very important for us. You know, and we think that by extending to and innovating with new language, large language models and leveraging Amazon Bedrock models that are plugins we think that with Gen AI we are going to be able to help customers answer questions about what is happening in the supply chain. Why is that happening? And, and at the end of the day, going back to simulating with what ifs, correct, what if I do this versus that? And then that evolution is something that we're very excited. We, we we're working very closely with customers on on providing on working in, in, in those capabilities. So, we, we are gonna see a lot of that coming soon. So that's, that's, that's very exciting. Features that we're we'll target to help customers reduce cost, improve productivity, and at the end of the day, going back to some of our initial hypothesis, accelerate, the data throughput through their supply chain so they can make better decisions and, and, and that's resonating really well with our customers. So we're, we're very excited about, about that.

Tom Raftery: 21:24

Cool, cool. And if there are two hot topics in supply chain today, I would say they are AI and we talked about that. And then sustainability is the other one. And you, you alluded to that. Can you tell me a little bit more about sustainability solutions or ways you can help your customers with their sustainability goals?

Diego Pantoja Navajas: 21:45

Yeah definitely. So what, what, what we have seen in terms of sustainability is, it's very important to understand how our suppliers, or how our customer's suppliers are, are, are, are meeting their goals or how their suppliers are aligning to our customers sustainability goals. Okay. Or ESG compliances, if you wanna just encapsulate all that, all that topic. And we have seen, we have been working with several customers that have asked us in terms of how can we help them to capture supply chain data that is related to sustainability. Correct. Like your packaging, your transportation, . The type of products that you're using or components that you're using to manufacture certain products from electronics to others. So there's a lot of, and, and as you know, the sustainability industry is still evolving, right? There's, there's, there's, there's a lot of policies that are being implemented in the European Union or in the US or other areas.. Some of them are consistent, some of them are not consistent across the board. So what we're trying to do first is help our customers, to receive and to be able to get data relevant data related to the product, and related to those sites, or countries, or that will help them build a much better information and will help them provide the right explainability to the customers in terms of how can we, how can we assess if this vendor is, aligning with our supply chain or su supply chain and sustainability goals So we're using the same underlaying technology in terms of how we use LLMs and how we use machine learnings to extract that data and connect suppliers. Eh, eh, so we we're very excited that we see that there's a big need for right now providing that type of solution for our, for, for our customers.

Tom Raftery: 23:53

Okay, cool. And seeing, as you mentioned customers, have you any customer success stories you can talk to.

Diego Pantoja Navajas: 24:02

Yeah, we, we, we, you know, not going directly into specific customers, but we have seen our product being very, very well received since day one from customers in, in the energy, energy sector, and the retail sector, CPG we're seeing a, a lot of companies that want to really, manufacturing too, that really want to understand their data. I, I think that one, one thing that has been consistent across all these different industries is the lack of understanding of their data, the lack of understanding of where all this information is, is coming. What is the explainability about this information? How can I leverage a, a better my, my resources, my assets? Where do I need to invest versus not invest? And then so, we're very excited that our initial hypothesis that AWS supply chain can serve across multiple industries, is really being a reality now. And, and we're working very closely with customers in multiple in multiple industries. And you, you will see some of those success stories pretty soon in our,

re: 25:09

Invent conference in November. And we we're gonna have a bunch of customers working with us that are working with us on stage, talking about how they're being able to leverage these capabilities either to reduce, you know, transportation costs or to, to reduce inventory across the network or to improve their vendor relationships with better data and, and, and, and working closely with them to improve their, their accuracy and, and, and product availability. How we being able to provide them with better demand forecast. And all that is, is is exciting because we've been very careful about how we position this product in the market as a pay as you go model. No big upfront investments, or no long contracts. Customers love the fact that, hey I get the benefit of the product from day one versus having to worry about the, the initial investment that I did, and how I'm gonna am amortize that investment over the last in the next three years. So a a lot of, a, a lot of goods is coming from, from, from that business approach that we, we, we started. So, and there's more, more things that we believe we're gonna be able to, to, to do for our customers in, in the, in the next 12, 12 months as well.

Tom Raftery: 26:18

Okay. And. It's nice that the pay as you go model is, it makes it easy to get people on board, but would I need to hire a suite of consultants to come in and do all this work at the cost of hundreds of thousands of euros or dollars or how does that work?

Diego Pantoja Navajas: 26:38

Yeah. That, that is, is, is an interesting question. And we have seen . We have seen customers that they needed to bring external help, because the fact that they have a very complex supply chain. And, we have customers, like I said before, they have multiple ERP systems. Some of those ERP systems have a lot of customizations that were built on customizations that, you know, why are there and people in the room say, well, I don't know. I just came to this company two years ago, or three years ago, but we were operating in that way over the last X number of years. So some big companies that are working with us are requiring additional help. And that's great. But what we are seeing is that we're working in a much more efficient way with you know, global SIs and, and, and, and making sure that those projects are taking less time to, to, to evolve because of the capabilities that the system provides. And, you know, once, once you're able to understand these data components once we're able to, you know, hey, let's, let's take this data and put it in an S3 bucket and see how the system behaves and and takes that information and translate that information into our canonical data model. And then we're able to use and run these models and, and see the information that is being contextualized. Then customers can say, okay, great. So we're moving faster than be, than, than what I have seen in, in before. And that's exciting and that's exciting for our customers. Some other customers don't need handholding. Some customers are very simple to implement. They come in, they, they get their environment provision ed, they start loading data and, we have seen, you know, I will say double digit customers that we are not aware that are using our application, suddenly using the application, you're saying, oh, great, that, you know, customer X is generating a demand forecast. And we've seen a lot of activity. And that's exciting because we were not involved with them, but we, we, we see that they're, they're, they're getting the results from, from our application and, and, and when our customer service team or, or our sales team or business development team en engage with them. We hear a, a lot of really great stories that continues to help us in developing a much better roadmap and understanding where we need to go with the application as, as we see a lot of self service tools that these customers are leveraging to use our applications so that, that's, that's that's great for us.

Tom Raftery: 29:20

Cool. And that leads nicely into my next question of, you know, where to next, what's, what is on that roadmap? Where are you gonna be with this product in 2, 3, 4, 5 years?

Diego Pantoja Navajas: 29:31

Look, Tom, we have a really great, exciting roadmap. We, we've been working very closely with our customers. One of the great things about working for AWS is that we can connect with many companies from many industries. We've been able to sit down with them over the last eight months and in terms of where we want to go next. And I think my, the exciting in my, in my face is that we're gonna have a lot of great pre announcements at re:Invent this year. So I really invite you and, and your audience to participate on, on, on that event or listening to our releases because we are going to, to show a lot of new capabilities that are gonna be exciting for, for customers and and it's coming pretty soon. So, stay tuned and we'll be able to provide a lot of new information about that. But we, we definitely believe that there's a lot of opportunities, in the upstream processes in supply chain, and that's where we believe a lot of the hanging fruits are. And I think we can do help our customers a lot in, in that area. So, there's a lot of work to do in, in, in, in that part of the supply chain.

Tom Raftery: 30:40

You're gonna be kept busy. Good, good, good. Okay, great. We're coming towards the end of the podcast now, Diego. Are there any questions I haven't asked or any topics we've not covered that you think it's important for people to be aware of?

Diego Pantoja Navajas: 30:55

I, I think that a maybe one, one, there's, there's a lot of other, you know, a processes that happening that ba they're based on, on supply chain data. Correct. And I think one of the things that we keep seeing all the time is, how can we help customers improve SNOP processes for our customers? How can we help our customers be more successful on, on insights? So for example, one thing that I, I said it but maybe didn't reinforce or dive too much into that topic is our Insights module and capabilities. I think what. It's, it's exciting to see is the the reaction from our customers when they understand their, you know, their, their vendor lead time, predictions, or the, when they see rebalancing capabilities. For us that those recommendations and, and explainability will continue to be key for our success. So, I think you can expect us to see a lot more investment in that area. A lot more investment, for example, in bringing that data outside of if you wanna say a computer, a laptop, and making sure that that information becomes accessible to customers through mobile devices and others. So they can be a much better interaction. And, and yes, I think that there's gonna be a, a lot more in terms of other technologies that we might use. And also we're, we're trying to leverage other investments that exist within AWS in the applications world. So, there's a lot of synergies that we're starting to see between joint customers across other AWS applications. So we, we we're starting to understand how we can better work and collaborate to make sure that our customers can, can come to us and find a solution for all those issues that, or opportunities that they see within their business. So a a lot of synergies. I think my point is there's a lot of synergies within AWS and our applications and that we're starting to see. And, and we, we believe that are differentiated enough and will continue to delight our customers in, in the coming years.

Tom Raftery: 33:10

Cool, cool. Diego, if people would like to know more about yourself or any of the things we discussed in the podcast today, where would you have me direct them?

Diego Pantoja Navajas: 33:20

I think the best place is is LinkedIn. You can ping me there more than happy to, to collaborate with, with your audience and and any questions that they might have or comments about this podcast. And yeah, looking forward to it. So LinkedIn will be the best, the best place for us to, to connect.

Tom Raftery: 33:39

Okay. And about the AWS Supply Chain.

Diego Pantoja Navajas: 33:43

You know, you can go to AWS Supply Chain as simple as that. And then you will find us. And then from there you can connect with one of our team members and they will be able to guide you in terms of how to start working with us. Or if you want to do it on your own, you can just start, start from there.

Tom Raftery: 34:02

Cool. Great, great. Super Diego, that's been fascinating. Thanks a million for coming on the podcast today.

Diego Pantoja Navajas: 34:08

Oh Tom thank you very much for having me and as always a pleasure.

Tom Raftery: 34:12

Okay, thank you all for tuning in to this episode of the Digital Supply Chain Podcast with me, Tom Raftery. Each week, over 3, 000 supply chain professionals listen to this show. If you or your organization want to connect with this dedicated audience, consider becoming a sponsor. You can opt for exclusive episode branding where you choose our guests or a personalized 30 second mid roll ad. It's a unique opportunity to reach industry experts and influencers. For more details, hit me up on Twitter or LinkedIn or drop me an email to tomraftery at outlook. com. Together, let's shape the future of the digital supply chain. Thanks. Catch you all next time.