Snowflake Summit 2025 | Tim Long, Snowflake & Vishwa Ram, Penske Logistics

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More from Snowflake Summit 2025

Tim Long

Global Head of Manufacturing, GTM

Snowflake

Vishwa Ram

Vice President Data Science & Analytics

Penske Logistics

play_circle_outline Convergence of IT and OT data in manufacturing operations for improved efficiency

play_circle_outline Blue Yonder's investment in rebuilding their stack on Snowflake for modernization

play_circle_outline Role of Snowflake in providing scale, flexibility, and innovation for Penske's technology evolution

play_circle_outline Utilization of Snowpark and anticipation of OpenFlow and Cortex Agents for future enhancements.

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Tim Long, Snowflake & Vishwa Ram, Penske Logistics

Tim Long

Global Head of Manufacturing, GTM Snowflake

Vishwa Ram

Vice President Data Science & Analytics Penske Logistics

In this Snowflake Summit 2025 segment, theCUBE’s Dave Vellante and John Furrier speak with Vishwa Ram, VP of data science & analytics at Penske Logistics, and Tim Long, global head of manufacturing at Snowflake, to unpack how AI-ready data strategies are redefining performance for manufacturers and logistics providers. Broadcasting live from the show floor, the conversation explores Snowflake’s vision of the AI Data Cloud as the connective tissue for enterprise innovation – and how Penske is turning integrated IT/OT data into real-time decisions that move fre... Read more

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What are some emerging patterns in the field that are being attacked with a data platform? add

What is the company's tech stack for supply chain management and data infrastructure? add

What has Snowflake provided in terms of scale and flexibility for the company? add

What are some of the key innovations and technologies that your company is currently focusing on for growth and scalability? add

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Tim Long, Snowflake & Vishwa Ram, Penske Logistics

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Rebecca Knight

>> Good afternoon everyone, and welcome back to theCube's Live coverage of the Snowflake Summit here in San Francisco. I'm your host, Rebecca Knight. Alongside my co-host and analyst Dave Vellante. I have two great guests for this next segment. I'd like to welcome back to theCube, Tim Long, global head of manufacturing Go-To-Market at Snowflake. Welcome back, Tim.

Tim Long

>> Thank you. Great to be here.

Rebecca Knight

>> And Vishwa Ram, he is the Vice President, data science and analytics at Penske Logistics. Welcome, Vishwa.

Vishwa Ram

>> Great to be here.

Rebecca Knight

>> So I think that Penske is pretty well-known company. A lot of people know what you're all about, but for the unannointed, tell our viewers a little bit about Penske and the exceedingly complex data problems that it has.

Vishwa Ram

>> Yeah, so Penske Logistics, we are a large third-party logistics provider, which means that we operate logistics on behalf of our customers. We're owned by Penske Truck Leasing, which is the largest leasing company in America. We've got the largest fleet of anybody in this country, over 300,000 trucks in North America. And our data challenges are primarily because of many things, right? But most importantly we have onboard telematics devices inside of our fleet that are generating millions of data points, including things like hard breaking and following too closely and fuel, fuel consumptions and so on. So really getting all of that data in one place and adding it up with other sets of data that we have that are contextual is really a huge challenge for us.

Dave Vellante

>> Not much going on in manufacturing these days is there? And I know that's sort of not the topic, but it is in a way, right? You get stuff that's made to where it goes as we see, we don't know. Every day you read a new headline. Market's up, market's down, but you have to be able to plan around that as best you can. So what's the state of your world today, Tim?

Tim Long

>> Yeah, absolutely. Well, it's a great place to be in the manufacturing industry. So much excitement, so many things are changing. And when it comes to our world supply chains right now, as you just pointed out, there's always a surprise every day. We lived through the last five years of incredible turbulence, whether it was pandemic disruptions or geopolitical issues or military conflicts, and now these trade wars. And so manufacturers and their supply chain partners are really looking for data to be the answer, to have that visibility so they can react in real time.

Dave Vellante

>> Did we get better muscle memory in a way because of the pandemic? And how has that informed... It was kind of pre the AI, heard around the world, even though there was ML back then, but did that in some way prepare us like spring training for what we're going through now or has it just been flipped on its side?

Tim Long

>> Yeah, absolutely. I think that what's happened is we're accustomed now to disruption being normal, and as a result, organizations seen just how important it is to invest in that visibility element so they can see the disruption as it's coming, or at least be able to react in real time when it does happen. And I'd love to hear know, Vishwa, you guys are supply chain experts. What are you seeing?

Vishwa Ram

>> Yeah, so one of the things that we do is, disruptions are part of what makes supply chain complex, and it's one of the reasons why customers come to us to manage their supply chain. So one of the things that we do is try and be predictive on the types of disruptions that are going to occur. So for example, for large automotive company, what we really do is figure out which supplier is going to have trouble shipping parts to them because they manufacture and they are running just in time. So if a part is delayed, that's going to stop their assembly. So getting ahead of the game, utilizing the data in predicting where might we be having challenges so that we can get ahead of the game.

Dave Vellante

>> So I mean there's a lot of opportunity to reduce waste in the supply chain, drop right to the bottom line. How is AI impacting that monetization, if you will? Where are we? What's the upside look like?

Vishwa Ram

>> Yeah, so I'll give you a couple of examples. At Penske, we're really taking a very targeted and a value-driven approach to AI, really focusing on areas where we can make measurable improvements to both our performance and employee experience. One of the things that has been really impactful for us has been in the area of workforce retention. Now Penske, we employ over 11,000 drivers and that's 11,000 drivers on the road every single day, and that's over 50% of our total workforce. So ensuring that they are engaged and supported is really critical to our business. So what we've done is we have developed an AI-based program that essentially looks at various indicators including their hours work, their route histories, and even sort of their engagement signals to proactively identify drivers who might be at risk of voluntarily terminating. And so that gives insights to our frontline managers who can then really act on that particular information, either that's say, check-in conversation or it's a schedule tweak or at some other way that they can show support to the driver. Now since we've launched this particular program, we have really reduced our turnovers quite dramatically. In fact, in some locations up to 30%.

Rebecca Knight

>> Because it's making them feel better, first of all about the company they work for and more loyal to it and also having a better on the job experience too.

Vishwa Ram

>> Yeah, absolutely. If your boss calls you to your office and just asks you how your day is going, that's going to make you feel better. So it is showing a little bit of TLC, but actually following it up with action so that if you tell me your schedule is really bad and if I could do something about it, you're going to feel like I work for a really good company, I got to stay here and an extra dollar somewhere else, is it really going to matter to me that much?

Dave Vellante

>> Exactly.

Dave Vellante

>> So to broadly speaking, what are you seeing in the field? Any patterns that you can share with us that are emerging that you guys are attacking with your data platform?

Tim Long

>> Yes. So really one of the things I'm most excited about is we're now starting to see this convergence of the world of IT and the world of OT, which is the manufacturing operations technology. We've been talking about this for a long time. It's now coming together. In fact, I did a little research last week and we see at least over 300 of Snowflake customers bringing that shop floor data from the basement to Snowflake in the cloud. And that's created incredible opportunities to really improve the manufacturing production and efficiency. And when you integrate also IoT data from telematics like your supply chain vehicles, now you truly have that full end-to-end business. And of course, AI is just bringing that to the next level of interacting with your data, getting the questions answered you want without having to spend a bunch of time digging through spreadsheets or dashboards to get to the point.

Rebecca Knight

>> So I'm fascinated by this. Can you give some examples about this convergence of OT and IT data? What are we talking about here?

Tim Long

>> What we're talking about is bringing information from your enterprise resource planning systems, your sales systems, your supply chain systems, and then integrating that with data from the shop floor itself, the equipment performance metrics, the machines that are building things, information about environmental sensors, energy utilization, et cetera. So you can truly manage the business end-to-end and that's what's exciting. Understanding things that are driving your efficiency or driving your product quality really requires all that data to come together.

Dave Vellante

>> So when I come to Penske Logistics and say, "Help me with my problems." How do you do that? Take us through that. Is that software and services and just data? What do I get? What do I buy? How do I pay you?

Vishwa Ram

>> Yeah, so let me just back up for a second. So we are what we would call a supply chain services company and we offer essentially, three major product lines. The first one is what we call dedicated contract carriage, which is really delivering on the Penske trucks, which is what most people are familiar with, but with also Penske drivers and our logistics sort of processes. We also do everything within what we call within the four walls, which is warehousing, distribution, and so on. And then the last is what we call freight management, which is really essentially, we don't have assets there, but we're sort of the conductor in an orchestra managing the underlying transportation providers. Now, all of these various elements has technologies that are associated with it that are really important for running that piece of business. One of the biggest advantages of working with somebody like Penske is that you get not only the technologies that manage their day-today, but also all of the backend things on reporting and the insights that we gather from you, giving you insights into your own supply chain health. And these are things that we find our customers are really important, find it important, and that's one of the reasons why they come to us.

Dave Vellante

>> And you've got a technology stack. Are you selling that technology stack? You're selling services and then you're producing results from that technology? Is it reporting maybe as an output of that, but what's your tech stack look like? I mean, obviously Snowflake is part of that, and then you've got other supply chain software, ERP. It's a pretty sophisticated, complicated backend, yeah?

Vishwa Ram

>> Right. So our philosophy here is to buy the best and build an ecosystem around the best so that our customers get value not just from the off-the-shelf software, but with our expertise and sort of the associate ecosystem that we have built around it. So we use, for example, in the transportation management sphere, we employ three of the tier one platforms. We employ Oracle Transportation Management System, Blue Yonder's Transportation Management System, and Mercury Gate. In warehouse management area, we employ Blue Yonder's Warehouse Management System primarily across all of our warehouses. Now, these are the execution systems, meaning that they help us execute the day-to-day. On the backend, Snowflake is the backbone of our data infrastructure. We employ Snowflake not just for consolidating our data from all of these various platforms, but we also use Snowflake to essentially create the sort of a unified trusted layer upon which we can build the AI and machine learning applications that both our internal and external teams use.

Vishwa Ram

>> Interesting. So Oracle, Blue Yonder, what was the third?

Dave Vellante

>> Mercury Gate.

Dave Vellante

>> Okay. We know Blue Yonder a little bit. They've come in theCube a number of times. They're doing some pretty remarkable things. It's amazing because sort of all these legacies and companies that they've bought put together, but they're rebuilding their stack on top of Snowflake and building some pretty sophisticated stuff. From a customer standpoint, how have you seen that impact? Is the marketing match the reality?

Vishwa Ram

>> Yeah, so I would give you a straight answer and say yes in the sense that Blue Yonder has been a long-term partner of Penske and we've utilized their services for a very long time. In fact, we were one of their early adopters of the transportation management platform. We had a big stake in making sure that that platform evolved to what it is today to handle our business and the complexity of our business. And if Blue Yonder was here, they would agree with me that the complexity in a third-party logistics company is way beyond what you would find with the shipper. The shipper may have larger scale, but the complexity is something that we have because of the various different types of businesses that we handle on any given day. Now, we haven't utilized all of the new cloud offering, but that is something that we're really super interested in. We're really trying to figure out how they can be leveraged within our environment.

Dave Vellante

>> Because they're investing. That's the reason I ask is because their owner could just squeeze and drop margin, but they've chosen to invest, to reformat their stack with Snowflake. So that's got to be exciting to see because you want to modernize. You're not a PE trying to just squeeze margin out of the assets that you have. You're trying to modernize and for the next 100 years, I mean, Penske's been around for a long time. Okay. So when you think about the evolution of your technology and your business, I'm interested in the role that you see. What do you want out of Snowflake, I guess is what I'm asking? What would you like Tim to do that would solve a problem and make your business better?

Vishwa Ram

>> So what I would say what Snowflake has given us is really, scale and flexibility. So I'll take you back to the day when I stepped into my role about 5 or 6 years ago. And when I stepped into that role, we were operating a very traditional BI tech stack. It was Oracle Business Objects and so on. And it came with a lot of the familiar challenges. I mean, we had performance bottlenecks, we had data silos and it just couldn't scale and keep up with our growth. So what Snowflake really did help us with is really, take us to the sort of modern age where we built this sort of modern ecosystem where we get this platform, we're able to get data, and we're able to really run really complex processes out of Snowflake. The thing that is central to us is still that particular thing, scale and growth. I think the innovations that keep coming is really important. So for example, Snowpark last year around this time was being released. We were one of the early adopters of Snowpark, and we converted some of our pipelines from Databricks into Snowpark, and that's been an incredible achievement. Now, the things that I'm looking for this year are things like OpenFlow, I think that's going to be huge for us. Cortex Agents, I think your sort of push into the AI space is really critical for us because the things that we want our people to do is to be able to engage with data in natural language and Cortex Agents and Analysts are going to help us do that. And we want to take that integrated directly into our platform so that whether you are a business leader or whether you're an analyst or you're an operator, you're able to get that speed to insight. And so that's where we really are pushing Snowflake, and that's where, I mean, they're innovating and really are looking forward to using them there.

Tim Long

>> Nice.

Vishwa Ram

>> Anything you'd add?

Tim Long

>> Well, I mean, I've met with dozens of customers in the last couple of days and everybody's sort of saying the same thing. They're incredibly excited about Snowflake's latest capabilities in AI and getting Cortex Analysts turned on and their data and developing and deploying these agents. So it's an exciting time for us.

Rebecca Knight

>> Well, great note to end on. Thank you both so much. A really interesting conversation.

>> Great story. Thank you.

Tim Long

>> Thank you both.

Rebecca Knight

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