Snowflake Data Cloud Summit 2024 | Tyler Prince | Snowflake & Duncan Angove | Blue Yonder

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Tyler Prince

SVP, Worldwide Alliances & Channels

Snowflake

Ransomware attack on Panasonic’s Blue Yonder disrupts supply chains in UK and US

A ransomware attack on Panasonic Corp.-owned supply chain management company Blue Yonder Group Inc. resulted in supply chain delays and issues in the U.K. and U.S. over the weekend and into today.The ransomware attack, which was detected on Nov. 21, caused disruptions to Blue Yonder’s managed services hosted environment. In contrast to many other companies, Blue Yonder has disclosed that the attack involved ransomware and provided updates on its website, though without a lot of detail.As of Nov. 23, the company said it was working around the clock, together with external cybersecurity firms, to restore systems safely

Blue Yonder and Snowflake tackling supply chain challenges with AI and data cloud

Since supply chains are accustomed to a siloed data environment, running them in a coordinated way is an uphill task, and this is why a data cloud for supply chain is needed. Through a unified platform and data cloud, Blue Yonder Inc. offers interoperable and resilient supply chain solutions through end-to-end connectivity with the help of Snowflake Inc. because the presence of data silos in supply chain triggers inefficiency based on increased latency and batch, according to Duncan Angove (pictured, right), chief executive officer of Blue Yonder. Snowflake’s Tyler Prince and Blue Yonder’s Duncan Angove talk to theCUBE about the importance of data cloud for supply chain

play_circle_outline Introduction to the Snowflake Data Cloud Summit and the hosts

play_circle_outline Introduction to Blue Yonder and their role as the largest supply chain software company

play_circle_outline Unveiling the Vitality and Trials of Supply Chain Data: Exploring its Immense Scale and Complexity

play_circle_outline The potential of supply chain as a massive opportunity for Snowflake

play_circle_outline The recognition of Blue Yonder as Snowflake's retail and consumer goods data cloud product partner of the year

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Tyler Prince | Snowflake & Duncan Angove | Blue Yonder

Tyler Prince

SVP, Worldwide Alliances & Channels Snowflake

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Rebecca Knight

>> Good morning everyone, and welcome back to theCUBE's live coverage of the Snowflake Data Cloud Summit here at the Moscone Center. I'm Rebecca Knight, your host, alongside my co-host and analyst, Dave Vellante. Day four of the conference. Let's talk about supply chain.

>> Yeah. Well, so two years ago, Frank Slootman on theCUBE's off-camera said to me, "Dave, you should look into supply chain. It's a really hard data problem, and it's a really interesting one that I think you'd be into researching." And so yeah -

Rebecca Knight

>> And there are companies that are also working on the problem and trying to solve it.

>> Doing some work there. And I'm excited to have these guys on.

Rebecca Knight

>> Indeed, indeed. Well, let me introduce our next guest to theCUBE, Duncan Angove. He is the CEO of Blue Yonder. Welcome back to theCUBE, Duncan.

>> Hi, good morning.

Rebecca Knight

>> And Tyler Prince, SVP, Worldwide Alliances and Channels at Snowflake. Thanks so much, Tyler. Great to have you.

Tyler Prince

>> Good to be here.

Rebecca Knight

>> So I want to start with you, Duncan, why don't you tell our viewers ... I know you've been on theCUBE, you've told your story, but tell us a little bit about Blue Yonder.

>> So we're the largest supply chain software company in the world. We run just the largest brands you can imagine across a multitude different industries, from retailing to semiconductor, to automotive, to CPG, and we do all the warehouse management, all the transportation, all the e-commerce, and then more importantly, all of the AI-based forecasting, replenishment, inventory management, all of that. So that's basically what we do.

Rebecca Knight

>> So we know that, as Dave said, these are hard problems to solve, in terms of bringing data to the supply chain. Why do organizations struggle with this so mightily?

>> So the volumes in supply chains surpass pretty much any other category of enterprise software. These are billions and billions of permutations. When you think about a retailer, the number of SKUs, the number of stores they have, and you do the mathematics on that, it's huge. And it's an AI problem at massive scale. So for example, every day on Snowflake, Blue Yonder runs 10 billion machine learning workloads. It's applied AI at scale and it's authentic. And those are basically predictions. Predicting demands, so you know what to buy and where to put it. But because of those kind of volumes and the mission criticality of supply chain, it's always been a very siloed data environment and a very diverse application topology. And it just makes it very, very difficult to run supply chains in a coordinated way. When you have all of these data silos and you're moving data around, it adds a lot of batch and latency and it's very, very inefficient. But there hasn't been the technology available to basically solve that problem. So the industry over 30 years has just broken it up into discrete problems to solve it.

>> So Tyler, when Sridhar was here earlier, I asked him, "Are you a data cloud company, an AI company, or an application platform for intelligent data apps?" And he said, "Yeah, basically. Yes, that's right." So that new vector of growth, obviously ISVs like Blue Yonder are very critical to that future vision. So I wonder if you could talk about the progress that you guys are making, the alliances that you have and the traction that you're getting in that regard.

Tyler Prince

>> I'd be happy to, and certainly Sridhar would've articulated this idea of being a platform and a generational platform in the technology industry. And every platform, if you think back in the history of our industry has had a robust ecosystem to support it. An ecosystem of people building apps and bringing data and other technology integrations, including services providers. Certainly some of the largest GSIs in the world like Accenture, Deloitte, EY, but literally thousands of system implementation firms that can help customers get value out of it. But every platform requires that robust ecosystem to really bring the platform to life for customers across every industry. And so we're thrilled to be working so closely with Blue Yonder. Think about how iconic that is to really come together and deliver the value Duncan just talked about, which is to really bring the data to life and be able to share that up and down the supply chain for so many customers.

>> Duncan, we don't talk about COVID anymore, but I remember you and I were talking during COVID about the future of bringing the digital and physical worlds together, and that is happening now, forced by COVID. We all know that. But you've always had a fascination with that concept. Where are we today and how do you see that playing out generally and specifically in supply chain?

>> It's been a massive catalyst for people to step back and actually reimagine how supply chain software should support a new blueprint for how supply chains run. If you look at the last 30 or 40 years, what's powered the world in a way is two concepts around supply chain. One is China as a factory for the world, globalization, all of that. And the second thing has been just in time, those two things together. And the pandemic exposed the emperor has no clothes. That's actually a flawed model in today's world, particularly when it's exacerbated by siloed applications that support it. So companies are looking for resiliency, and the way they responded to it is by building up inventory. So JP Morgan did a study of the S&P 1500 and they said in the last two years, working capital has increased 40%. That's $500 billion of extra inventory sitting on someone's balance sheet that's not being invested back in the consumer or growth. And our premise is the answer to resiliency is not inventory, it's software, but not the software we traditionally had where it's these different silos that don't allow you to operate in a coordinated way across departments and across enterprises. And that's where the data cloud is so powerful. All your data in one place, one version of the truth across the enterprise. You're moving applications to the data and it allows you to operate in a speed and in a way you can coordinate that was unprecedented before this technology came along.

>> So I'll tell a little story and get your perspective and you can explain how you're going to solve this problem. So I was traveling, my wife was away, and she said, "Hey, we're getting this furniture delivery at the house. It's two pieces. Can you get home in time to be there when they deliver it?" "Yeah, I can figure that out." So I get there, one piece shows up, they drop it off and they're leaving, I'm like, "Where's the other one?" They're just like, "We only have one. The other one's coming tomorrow." I'm like, "Well, I'm not going to be here tomorrow." I was like, why does that happen? Now, speaking to you, I know why that ... but you can explain it better than I can, but I'm more interested in how you're going to solve that.

>> So that happens because even though we call it a supply chain, people don't really operate ... A chain implies that the links are all connected. And the dirty secret is they're not, because again, everyone has their different incentives. This person runs the warehouse. They care about these metrics. This person runs transportation. This person runs order management and e-commerce. So not only are they not really coordinating within an enterprise, they're certainly not doing it with their carriers or their suppliers or things like that. So what happens is someone builds the perfect plan, they're going to deliver those two things to your house on that day, but the plan never survives the light of day because of disruptions and uncertainty. Maybe you get to the warehouse and the robot went along it and that item was damaged, the second item, or Bob and Bill went on a bender last night and didn't show up for work, but there's no coordination. When something happens, how can you react in a coordinated way in real-time to actually resolve that? And that's why if you bring all of the data together into one data cloud and you run all the applications on it and you design these applications to actually talk to each other, you actually enable cross-functional excellence and orchestration. You solve that exact problem.

Rebecca Knight

>> And that is a ginormous shift. Just in terms of the way organizations, how the supply chain used to work and how organizations used to run and how there were these many fiefdoms within organizations. "I run the warehouse. I run transportation." So describe for me, Tyler, how you also help organizations deal with this massive change management issue.

Tyler Prince

>> Yeah, that's exactly the secret sauce of Snowflake is the ability to share data among business partners. And that's why the supply chain story is so incredible because it's all about the data and sharing that as quickly and securely in a very compliant way with your business partners, not just me to you, and not just in the examples, but up and down that supply chain real-time. So that's the real value of empowering that. Now driving that solution is critical to help these customers get that right, because what we just described between the two of us is game-changing for that supply chain and every player within that supply chain. So helping them understand how to get the value out of the data and how to change their business process to operate in this real-time world is a critical step in this.

>> So because it goes from an asynchronous batch job into something that's near real-time, as close to real time as you can possibly get. I guess I would define real-time before the truck leaves without the other piece of furniture. It sends a signal. You've got all those coordinated efforts. What does it require, however, to do that? What are the assumptions that you need ... You've got to have the data inside of Snowflake. You've been clear on that. What else do you have to have?

>> So it's a good point. One of the things that has plagued supply chain software is it's batch oriented. And it's batch oriented because there's a ton of data. There's a lot of compute where you're running billions of permutations, like the 10 billion a day we do. So it's always been done in batch because you haven't had an architecture like you get with a data cloud where you have access to elastic compute and technicalities around zero copy cloning and separating storage from compute. So it allows us to do things we've never been able to do before, and it's in essence, eliminate batch, which is the latency that you have in supply chain. It's sort of like you remember the old military thing, the OODA, the observe, orient, decide, act thing, and it was all about getting inside your competitor's OODA loop? So that's really what we're trying to do. And if you think about supply chains, all our metrics are founded in speed and time, on time in full, just in time. How fast are your turns, flow, all of these things. So what Snowflake allows us to do is inject speed in that OODA loop, get rid of batch, get rid of the hourglass, deploy infinite compute. So that's a big part of it. The second part is it needs to be event-driven. So if stuff happens, like someone went down the aisle and saw that the second item of your furniture was damaged, that event is a prompt into a generative AI. The event itself is, "What should I do? This second item is not available." And then it calls different APIs, different solvers, different AI algorithms to figure out how to solve it on behalf of the human. So that's really what it is. It's snowflake with an event-driven architecture wrapped around it.

>> And you can update that in near real-time.

>> Yep.

>> Two questions. How are you using knowledge graphs and where do agents fit into this?

>> So as you know, we use relational AI as our semantic layer, the knowledge graph that sits on ... And by the way, it's perfectly oriented supply chains because supply chains are all about relationships. This product, this supplier, this brand, it's this store. It's very well-tuned to that. So that gives us really, really strong AI capabilities, because for language models and agents, it brings context and semantic meaning to the underlying data, which is critical for it. And on top of that, we deploy agents. So for every end user we have in the supply chain for Blue Yonder, whether it's an allocator, a planner, a warehouse operator, we deploy an agent that augments what they do, and it's attached to our intelligence, our ML, our solvers, all of that. Think of it as a calculator for the supply chain. Everyone knows, generative AI isn't terribly good at math today. So this is a calculator for the supply chain. And it's connected to our execution APIs. So it can't just figure out what to do, it can actually affect the physical world. It's a bridge from digital to physical. So that's basically what we're doing from an agent perspective.

>> How much AI do you have to develop and what AI do you want to get from Snowflake? Where do you leave off and Snowflake picks up or vice versa?

>> So we leverage Snowflake as part of the ... think of it as almost like the middleware for AI and all of that. And we obviously develop our own intellectual property around machine learning algorithms, generative AI. We filed 70 AI patents alone last year. We did 17 in Q1 just around generative AI applied to supply chain. So that's a core component of what we do. Supply chains were always the birthplace of ops research. And back in the day, that was the beer run and all of that. And so we've been doing AI for over a decade now, authentically. We're not just adding .ai to our domain name. So it was natural to extend that into the generative AI field, and that's where all the investments that Snowflake's made and what we're doing there, a lot of stuff was announced earlier this week. We're taking advantage of all of that to basically accelerate the delivery of what I've talked about.

Tyler Prince

>> And if I could just add, I think that's why we're seeing quite a bit of excitement even here in this room around third parties, these innovative companies that can focus on what their core business is and the domains that they're serving around supply chain or banking or whatever the industry or business process might be. But it allows them to focus on those core competencies and leverage the innovation that we're driving in the world of data and AI. Because it's complicated, and so the things that we're solving allow them to focus on other things.

Rebecca Knight

>> So Tyler, how big an opportunity does supply chain represent to Snowflake? As we've said, we've painted this picture of it is a massive problem for organizations large and small.

Tyler Prince

>> It's a massive problem and a massive opportunity, but it's also dependent on a tremendous amount of data. It's almost mind-boggling to think about the amount of data. I think probably, and you would know the numbers, it probably trumps the idea of customer data as an example, the supply chain data that's up and down that supply chain, because it touches every part of the company. It includes customer data, but it includes manufacturing data, inventory data, financial data and so on. So I think it's a massive opportunity. And I think that's probably what attracted Duncan and his team to Snowflake is our ability to process and manage and govern that much data.

>> What was the inventory stat you gave earlier?

>> Well, just in ML predictions, it's 10 billion a day, and it's probably growing by a billion every month. So the scale of this is incomprehensible, and it's not running in a batch-based architecture. So in essence, we talk about our shared vision of building the supply chain operating system for the world where anywhere trade and commerce and the supply chains take place, it runs on our software rails. It's like part of national infrastructure. I made a video for a press conference in Tokyo a couple of years ago, and the whole premise of the thing was, "Can you get through the day without touching something that Blue Yonder put there?" And you wake up in the morning, you've got Lululemon on, you open the fridge, there's a Danone yogurt, there's a Dasani water bottle. You get in your Mercedes-Benz, you stop at Starbucks, you order -

Rebecca Knight

>> I want that person's life. That's a nice life.

>> So literally, it's everything that we interact with. It's there. You see a postal truck, it's there because we put it there, and the parcels on it are on there because we put it there. So we touch so much in the world, and you just think about the volumes and the complexity of all of that. And every day there's disruption, and companies are operating in an age of uncertainty. In a way, that's a further catalyst to actually stepped back and re-imagine traditional approaches.

Rebecca Knight

>> So earlier this week, Blue Yonder was recognized as Snowflake's retail and consumer goods data cloud product partner of the year. As you said, your company is enormous and touches so much of our daily life. But what does this recognition mean to you as an organization?

>> We have a very, very deep partnership with Snowflake. We have a shared vision around where we think the world should go as it relates to supply chains. Dave, you said it. Supply chain is fundamentally a data problem, and it always has been. And Snowflake are uniquely positioned to solve that. And when you take our intellectual property and you combine it with that, it's a very, very compelling proposition. So we do a ton of work in R&D with Snowflake. Our teams are locked together. Because if Snowflake can solve the challenges of supply chain and the volumes and the complexity and the compute and the scale, they can solve it in any industry. And we have a very, very strong go-to-market partnership as well.

>> We had Jeremy Burton on the other day. He's the CEO of Observe. And that's an example where a new software company can come in. Observe can come in, run on top of Snowflake, they can disrupt New Relic. What I like about what you're doing with Blue Yonder, you could easily just milk it and do the EBITDA thing, but instead you're transforming the company. You're rewriting your stack on top of Snowflake. You've got things like relational AI, which is highly advanced. So obviously you're paranoid. But it's very difficult to not only disrupt supply chain, but actually reinvent it. So that's really what I like about what you're doing. What's in the future for you guys?

>> So the company's built on innovation is what we believe, and that's why I told you we've constantly file new patents and we're constantly trying to reimagine the world. Supply chain software is being too incremental across the landscape, and no one's actually stepped back and say, "How do we drive a step change on top of new technology that reflects the reality of what's happening in supply chain today?" We spent a billion dollars in M&A in the last six months. We're spending a billion dollars in R&D over the next 18 months. So there's a massive commitment here at a scale that people have not seen in investment. Well, it's the perfect storm. You've got all this uncertainty happening and wake up every day, and we have AI, robotics in the data cloud. A beautiful new canvas on which to reimagine all of this.

>> Yeah, very bold vision, Duncan. Really appreciate you guys coming on.

Tyler Prince

>> Yep.

>> Thank you.

Rebecca Knight

>> Indeed, indeed. And I just want to ask one last question for Duncan. And I know you had said earlier that the supply chain is all about relationships. And you were talking about the relationships between team organizations and departments, but it's also about human relationships. And I was reading your leadership bio where you talked about striving to have a diverse organization centered around camaraderie and passion and purpose. And I'm just curious as a leader of an organization, how you think about the kinds of traits you're looking for in employees, particularly as we are at this real inflection point with what the future of work looks like?

>> So purpose is very important. So we call ours sustainable abundance. And if you unpack that a little bit, the two prongs to ours first of all is sustainability. Supply chains are guilty of creating a lot of food waste, apparel waste, carbon emissions, 60% of all the carbon emissions. So how do we make supply chains more sustainable? Ironically, having them behave in a more joined-up way actually does help. There's a lot of, I'll call it green leakage between silos. And the second thing is around abundance. Supply chains have delivered so much benefit to mankind. If you go back to the Silk Road, it lifted billions of people out of poverty. But invention and technology has always been the amplifier of those benefits. The invention of money, the steam engine, the internet, the shipping container, all of those things. And so our goal is how do we use ... And by the way, they've created abundance. Technology turns scarcity into abundance. Food, clothing, electronics, medicine, all of those things. So our goal is how do we leverage all this technology in the data cloud to usher in this next wave of abundance, but do it in a more sustainable way? So that's a big part of our purpose. And we want people here at Blue Yonder that are driven by re-imagining what's possible and innovating and challenging conventional thinking. It's a big, big part of what drives the company.

Rebecca Knight

>> Excellent. Well, again, thank you both for coming on theCUBE.

Tyler Prince

>> Great to be here.

>> Thank you.

Tyler Prince

>> Good to see you.

>> Thank you. Good to see you again.

Tyler Prince

>> Thanks.

>> Thank you.

Rebecca Knight

>> I'm Rebecca Knight for Dave Vellante. Stay tuned for more of theCUBE's live coverage of the Snowflake Data Cloud Summit. You're watching theCUBE, the leader in enterprise tech news and analysis.

Tyler Prince | Snowflake & Duncan Angove | Blue Yonder

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Rebecca Knight

>> Good morning everyone, and welcome back to theCUBE's live coverage of the Snowflake Data Cloud Summit here at the Moscone Center. I'm Rebecca Knight, your host, alongside my co-host and analyst, Dave Vellante. Day four of the conference. Let's talk about supply chain.

>> Yeah. Well, so two years ago, Frank Slootman on theCUBE's off-camera said to me, "Dave, you should look into supply chain. It's a really hard data problem, and it's a really interesting one that I think you'd be into researching." And so yeah -

Rebecca Knight

>> And there are companies that are also working on the problem and trying to solve it.

>> Doing some work there. And I'm excited to have these guys on.

Rebecca Knight

>> Indeed, indeed. Well, let me introduce our next guest to theCUBE, Duncan Angove. He is the CEO of Blue Yonder. Welcome back to theCUBE, Duncan.

>> Hi, good morning.

Rebecca Knight

>> And Tyler Prince, SVP, Worldwide Alliances and Channels at Snowflake. Thanks so much, Tyler. Great to have you.

Tyler Prince

>> Good to be here.

Rebecca Knight

>> So I want to start with you, Duncan, why don't you tell our viewers ... I know you've been on theCUBE, you've told your story, but tell us a little bit about Blue Yonder.

>> So we're the largest supply chain software company in the world. We run just the largest brands you can imagine across a multitude different industries, from retailing to semiconductor, to automotive, to CPG, and we do all the warehouse management, all the transportation, all the e-commerce, and then more importantly, all of the AI-based forecasting, replenishment, inventory management, all of that. So that's basically what we do.

Rebecca Knight

>> So we know that, as Dave said, these are hard problems to solve, in terms of bringing data to the supply chain. Why do organizations struggle with this so mightily?

>> So the volumes in supply chains surpass pretty much any other category of enterprise software. These are billions and billions of permutations. When you think about a retailer, the number of SKUs, the number of stores they have, and you do the mathematics on that, it's huge. And it's an AI problem at massive scale. So for example, every day on Snowflake, Blue Yonder runs 10 billion machine learning workloads. It's applied AI at scale and it's authentic. And those are basically predictions. Predicting demands, so you know what to buy and where to put it. But because of those kind of volumes and the mission criticality of supply chain, it's always been a very siloed data environment and a very diverse application topology. And it just makes it very, very difficult to run supply chains in a coordinated way. When you have all of these data silos and you're moving data around, it adds a lot of batch and latency and it's very, very inefficient. But there hasn't been the technology available to basically solve that problem. So the industry over 30 years has just broken it up into discrete problems to solve it.

>> So Tyler, when Sridhar was here earlier, I asked him, "Are you a data cloud company, an AI company, or an application platform for intelligent data apps?" And he said, "Yeah, basically. Yes, that's right." So that new vector of growth, obviously ISVs like Blue Yonder are very critical to that future vision. So I wonder if you could talk about the progress that you guys are making, the alliances that you have and the traction that you're getting in that regard.

Tyler Prince

>> I'd be happy to, and certainly Sridhar would've articulated this idea of being a platform and a generational platform in the technology industry. And every platform, if you think back in the history of our industry has had a robust ecosystem to support it. An ecosystem of people building apps and bringing data and other technology integrations, including services providers. Certainly some of the largest GSIs in the world like Accenture, Deloitte, EY, but literally thousands of system implementation firms that can help customers get value out of it. But every platform requires that robust ecosystem to really bring the platform to life for customers across every industry. And so we're thrilled to be working so closely with Blue Yonder. Think about how iconic that is to really come together and deliver the value Duncan just talked about, which is to really bring the data to life and be able to share that up and down the supply chain for so many customers.

>> Duncan, we don't talk about COVID anymore, but I remember you and I were talking during COVID about the future of bringing the digital and physical worlds together, and that is happening now, forced by COVID. We all know that. But you've always had a fascination with that concept. Where are we today and how do you see that playing out generally and specifically in supply chain?

>> It's been a massive catalyst for people to step back and actually reimagine how supply chain software should support a new blueprint for how supply chains run. If you look at the last 30 or 40 years, what's powered the world in a way is two concepts around supply chain. One is China as a factory for the world, globalization, all of that. And the second thing has been just in time, those two things together. And the pandemic exposed the emperor has no clothes. That's actually a flawed model in today's world, particularly when it's exacerbated by siloed applications that support it. So companies are looking for resiliency, and the way they responded to it is by building up inventory. So JP Morgan did a study of the S&P 1500 and they said in the last two years, working capital has increased 40%. That's $500 billion of extra inventory sitting on someone's balance sheet that's not being invested back in the consumer or growth. And our premise is the answer to resiliency is not inventory, it's software, but not the software we traditionally had where it's these different silos that don't allow you to operate in a coordinated way across departments and across enterprises. And that's where the data cloud is so powerful. All your data in one place, one version of the truth across the enterprise. You're moving applications to the data and it allows you to operate in a speed and in a way you can coordinate that was unprecedented before this technology came along.

>> So I'll tell a little story and get your perspective and you can explain how you're going to solve this problem. So I was traveling, my wife was away, and she said, "Hey, we're getting this furniture delivery at the house. It's two pieces. Can you get home in time to be there when they deliver it?" "Yeah, I can figure that out." So I get there, one piece shows up, they drop it off and they're leaving, I'm like, "Where's the other one?" They're just like, "We only have one. The other one's coming tomorrow." I'm like, "Well, I'm not going to be here tomorrow." I was like, why does that happen? Now, speaking to you, I know why that ... but you can explain it better than I can, but I'm more interested in how you're going to solve that.

>> So that happens because even though we call it a supply chain, people don't really operate ... A chain implies that the links are all connected. And the dirty secret is they're not, because again, everyone has their different incentives. This person runs the warehouse. They care about these metrics. This person runs transportation. This person runs order management and e-commerce. So not only are they not really coordinating within an enterprise, they're certainly not doing it with their carriers or their suppliers or things like that. So what happens is someone builds the perfect plan, they're going to deliver those two things to your house on that day, but the plan never survives the light of day because of disruptions and uncertainty. Maybe you get to the warehouse and the robot went along it and that item was damaged, the second item, or Bob and Bill went on a bender last night and didn't show up for work, but there's no coordination. When something happens, how can you react in a coordinated way in real-time to actually resolve that? And that's why if you bring all of the data together into one data cloud and you run all the applications on it and you design these applications to actually talk to each other, you actually enable cross-functional excellence and orchestration. You solve that exact problem.

Rebecca Knight

>> And that is a ginormous shift. Just in terms of the way organizations, how the supply chain used to work and how organizations used to run and how there were these many fiefdoms within organizations. "I run the warehouse. I run transportation." So describe for me, Tyler, how you also help organizations deal with this massive change management issue.

Tyler Prince

>> Yeah, that's exactly the secret sauce of Snowflake is the ability to share data among business partners. And that's why the supply chain story is so incredible because it's all about the data and sharing that as quickly and securely in a very compliant way with your business partners, not just me to you, and not just in the examples, but up and down that supply chain real-time. So that's the real value of empowering that. Now driving that solution is critical to help these customers get that right, because what we just described between the two of us is game-changing for that supply chain and every player within that supply chain. So helping them understand how to get the value out of the data and how to change their business process to operate in this real-time world is a critical step in this.

>> So because it goes from an asynchronous batch job into something that's near real-time, as close to real time as you can possibly get. I guess I would define real-time before the truck leaves without the other piece of furniture. It sends a signal. You've got all those coordinated efforts. What does it require, however, to do that? What are the assumptions that you need ... You've got to have the data inside of Snowflake. You've been clear on that. What else do you have to have?

>> So it's a good point. One of the things that has plagued supply chain software is it's batch oriented. And it's batch oriented because there's a ton of data. There's a lot of compute where you're running billions of permutations, like the 10 billion a day we do. So it's always been done in batch because you haven't had an architecture like you get with a data cloud where you have access to elastic compute and technicalities around zero copy cloning and separating storage from compute. So it allows us to do things we've never been able to do before, and it's in essence, eliminate batch, which is the latency that you have in supply chain. It's sort of like you remember the old military thing, the OODA, the observe, orient, decide, act thing, and it was all about getting inside your competitor's OODA loop? So that's really what we're trying to do. And if you think about supply chains, all our metrics are founded in speed and time, on time in full, just in time. How fast are your turns, flow, all of these things. So what Snowflake allows us to do is inject speed in that OODA loop, get rid of batch, get rid of the hourglass, deploy infinite compute. So that's a big part of it. The second part is it needs to be event-driven. So if stuff happens, like someone went down the aisle and saw that the second item of your furniture was damaged, that event is a prompt into a generative AI. The event itself is, "What should I do? This second item is not available." And then it calls different APIs, different solvers, different AI algorithms to figure out how to solve it on behalf of the human. So that's really what it is. It's snowflake with an event-driven architecture wrapped around it.

>> And you can update that in near real-time.

>> Yep.

>> Two questions. How are you using knowledge graphs and where do agents fit into this?

>> So as you know, we use relational AI as our semantic layer, the knowledge graph that sits on ... And by the way, it's perfectly oriented supply chains because supply chains are all about relationships. This product, this supplier, this brand, it's this store. It's very well-tuned to that. So that gives us really, really strong AI capabilities, because for language models and agents, it brings context and semantic meaning to the underlying data, which is critical for it. And on top of that, we deploy agents. So for every end user we have in the supply chain for Blue Yonder, whether it's an allocator, a planner, a warehouse operator, we deploy an agent that augments what they do, and it's attached to our intelligence, our ML, our solvers, all of that. Think of it as a calculator for the supply chain. Everyone knows, generative AI isn't terribly good at math today. So this is a calculator for the supply chain. And it's connected to our execution APIs. So it can't just figure out what to do, it can actually affect the physical world. It's a bridge from digital to physical. So that's basically what we're doing from an agent perspective.

>> How much AI do you have to develop and what AI do you want to get from Snowflake? Where do you leave off and Snowflake picks up or vice versa?

>> So we leverage Snowflake as part of the ... think of it as almost like the middleware for AI and all of that. And we obviously develop our own intellectual property around machine learning algorithms, generative AI. We filed 70 AI patents alone last year. We did 17 in Q1 just around generative AI applied to supply chain. So that's a core component of what we do. Supply chains were always the birthplace of ops research. And back in the day, that was the beer run and all of that. And so we've been doing AI for over a decade now, authentically. We're not just adding .ai to our domain name. So it was natural to extend that into the generative AI field, and that's where all the investments that Snowflake's made and what we're doing there, a lot of stuff was announced earlier this week. We're taking advantage of all of that to basically accelerate the delivery of what I've talked about.

Tyler Prince

>> And if I could just add, I think that's why we're seeing quite a bit of excitement even here in this room around third parties, these innovative companies that can focus on what their core business is and the domains that they're serving around supply chain or banking or whatever the industry or business process might be. But it allows them to focus on those core competencies and leverage the innovation that we're driving in the world of data and AI. Because it's complicated, and so the things that we're solving allow them to focus on other things.

Rebecca Knight

>> So Tyler, how big an opportunity does supply chain represent to Snowflake? As we've said, we've painted this picture of it is a massive problem for organizations large and small.

Tyler Prince

>> It's a massive problem and a massive opportunity, but it's also dependent on a tremendous amount of data. It's almost mind-boggling to think about the amount of data. I think probably, and you would know the numbers, it probably trumps the idea of customer data as an example, the supply chain data that's up and down that supply chain, because it touches every part of the company. It includes customer data, but it includes manufacturing data, inventory data, financial data and so on. So I think it's a massive opportunity. And I think that's probably what attracted Duncan and his team to Snowflake is our ability to process and manage and govern that much data.

>> What was the inventory stat you gave earlier?

>> Well, just in ML predictions, it's 10 billion a day, and it's probably growing by a billion every month. So the scale of this is incomprehensible, and it's not running in a batch-based architecture. So in essence, we talk about our shared vision of building the supply chain operating system for the world where anywhere trade and commerce and the supply chains take place, it runs on our software rails. It's like part of national infrastructure. I made a video for a press conference in Tokyo a couple of years ago, and the whole premise of the thing was, "Can you get through the day without touching something that Blue Yonder put there?" And you wake up in the morning, you've got Lululemon on, you open the fridge, there's a Danone yogurt, there's a Dasani water bottle. You get in your Mercedes-Benz, you stop at Starbucks, you order -

Rebecca Knight

>> I want that person's life. That's a nice life.

>> So literally, it's everything that we interact with. It's there. You see a postal truck, it's there because we put it there, and the parcels on it are on there because we put it there. So we touch so much in the world, and you just think about the volumes and the complexity of all of that. And every day there's disruption, and companies are operating in an age of uncertainty. In a way, that's a further catalyst to actually stepped back and re-imagine traditional approaches.

Rebecca Knight

>> So earlier this week, Blue Yonder was recognized as Snowflake's retail and consumer goods data cloud product partner of the year. As you said, your company is enormous and touches so much of our daily life. But what does this recognition mean to you as an organization?

>> We have a very, very deep partnership with Snowflake. We have a shared vision around where we think the world should go as it relates to supply chains. Dave, you said it. Supply chain is fundamentally a data problem, and it always has been. And Snowflake are uniquely positioned to solve that. And when you take our intellectual property and you combine it with that, it's a very, very compelling proposition. So we do a ton of work in R&D with Snowflake. Our teams are locked together. Because if Snowflake can solve the challenges of supply chain and the volumes and the complexity and the compute and the scale, they can solve it in any industry. And we have a very, very strong go-to-market partnership as well.

>> We had Jeremy Burton on the other day. He's the CEO of Observe. And that's an example where a new software company can come in. Observe can come in, run on top of Snowflake, they can disrupt New Relic. What I like about what you're doing with Blue Yonder, you could easily just milk it and do the EBITDA thing, but instead you're transforming the company. You're rewriting your stack on top of Snowflake. You've got things like relational AI, which is highly advanced. So obviously you're paranoid. But it's very difficult to not only disrupt supply chain, but actually reinvent it. So that's really what I like about what you're doing. What's in the future for you guys?

>> So the company's built on innovation is what we believe, and that's why I told you we've constantly file new patents and we're constantly trying to reimagine the world. Supply chain software is being too incremental across the landscape, and no one's actually stepped back and say, "How do we drive a step change on top of new technology that reflects the reality of what's happening in supply chain today?" We spent a billion dollars in M&A in the last six months. We're spending a billion dollars in R&D over the next 18 months. So there's a massive commitment here at a scale that people have not seen in investment. Well, it's the perfect storm. You've got all this uncertainty happening and wake up every day, and we have AI, robotics in the data cloud. A beautiful new canvas on which to reimagine all of this.

>> Yeah, very bold vision, Duncan. Really appreciate you guys coming on.

Tyler Prince

>> Yep.

>> Thank you.

Rebecca Knight

>> Indeed, indeed. And I just want to ask one last question for Duncan. And I know you had said earlier that the supply chain is all about relationships. And you were talking about the relationships between team organizations and departments, but it's also about human relationships. And I was reading your leadership bio where you talked about striving to have a diverse organization centered around camaraderie and passion and purpose. And I'm just curious as a leader of an organization, how you think about the kinds of traits you're looking for in employees, particularly as we are at this real inflection point with what the future of work looks like?

>> So purpose is very important. So we call ours sustainable abundance. And if you unpack that a little bit, the two prongs to ours first of all is sustainability. Supply chains are guilty of creating a lot of food waste, apparel waste, carbon emissions, 60% of all the carbon emissions. So how do we make supply chains more sustainable? Ironically, having them behave in a more joined-up way actually does help. There's a lot of, I'll call it green leakage between silos. And the second thing is around abundance. Supply chains have delivered so much benefit to mankind. If you go back to the Silk Road, it lifted billions of people out of poverty. But invention and technology has always been the amplifier of those benefits. The invention of money, the steam engine, the internet, the shipping container, all of those things. And so our goal is how do we use ... And by the way, they've created abundance. Technology turns scarcity into abundance. Food, clothing, electronics, medicine, all of those things. So our goal is how do we leverage all this technology in the data cloud to usher in this next wave of abundance, but do it in a more sustainable way? So that's a big part of our purpose. And we want people here at Blue Yonder that are driven by re-imagining what's possible and innovating and challenging conventional thinking. It's a big, big part of what drives the company.

Rebecca Knight

>> Excellent. Well, again, thank you both for coming on theCUBE.

Tyler Prince

>> Great to be here.

>> Thank you.

Tyler Prince

>> Good to see you.

>> Thank you. Good to see you again.

Tyler Prince

>> Thanks.

>> Thank you.

Rebecca Knight

>> I'm Rebecca Knight for Dave Vellante. Stay tuned for more of theCUBE's live coverage of the Snowflake Data Cloud Summit. You're watching theCUBE, the leader in enterprise tech news and analysis.