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Enhancing Supply Chain Visibility through AI Insights

• Evan Kirstel

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Join us for an enlightening conversation with Sriram Nagaswamy, the Executive Vice President of Technology at FourKites, as we explore how artificial intelligence is reshaping the supply chain landscape. Ever wondered how businesses can pinpoint their shipments’ locations and predict arrival times amidst today's constant disruptions? Sriram shares his remarkable journey from being one of the first engineers at FourKites to leading technological innovations that address these critical questions, offering an insider's perspective on evolving supply chain challenges and the strategic role of data.

Discover how AI is not just enhancing visibility but transforming what were once "black holes" of data into integral, manageable parts of supply chain management. Sriram highlights how AI-driven insights empower businesses to optimize their networks and swiftly adapt to unforeseen events. Through real-world examples, learn how FourKites is pushing the boundaries of what's possible, ensuring companies are better equipped to navigate the unpredictable waters of today's global supply chains. This episode promises a deeper understanding of AI's groundbreaking impact on supply chain efficiency and visibility.

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Speaker 1:

Hey everybody, Should be a fascinating chat today as we dive into using AI to improve supply chain visibility and efficiency with 4Kites. Sriram, how are you? I'm good.

Speaker 2:

How are you Evan?

Speaker 1:

I'm well Thanks for joining, Really excited for this chat. You're doing some really innovative work. Before that, maybe introduce yourself the team and mission at Forkite.

Speaker 2:

Sure, hey, I'm Sriram Nagaswamy. I'm the Executive Vice President of Technology at Forkite. Have been with Forkite for a little over seven and a half years now and joined probably as the ninth person in engineering and maybe the 25th or what have you worldwide, and, having seen exponential growth over the last seven and a half years, has been an amazing ride and I'm very, very happy to be on this podcast.

Speaker 1:

Well, thanks for being here, and let's dive in. Give us an overview of what 4Kites does and the key problems it solves when it comes to supply chain, something that's on top of mind for many of us these days.

Speaker 2:

Awesome. Yeah, so 4Kites was basically born as a company to answer two questions, evan. Born as a company to answer two questions, evan. The questions were where is my shipment and when will it get to its destination?

Speaker 2:

Pretty fundamental and it's kind of even more mind-blowing to think that it didn't exist before Foka. It's actually defined that as the primary problem point, that as the primary problem point. So, as you can imagine, it was Gartner magic quadrant defining problem that we embarked on solving and the testament to that was, I think, 2019 or 2020,. Eventually, gartner did come out with a magic quadrant for real-time visibility, and so that was the primary journey that Focke-Eitz started on almost 10 years ago now and obviously, you know, as we started evolving, you know we've started answering more questions like when should a product be at what destination, and not just you know where is my shipment and when will it get to its destination. So I think we're getting more and more into order-based visibility and then trying to see how we can kind of stitch the entire picture for our customers to be able to see the challenges and then obviously optimize their networks based on the challenges that are specific to them.

Speaker 1:

Fascinating. So let's talk operational challenges. What are some of the biggest challenges in the real world of supply chain today and what are people facing that they have to deal with, and how do you specifically address them?

Speaker 2:

Sure. So I mean beyond just the problems of dwell detention and so on and so forth, right, I think the last few years, black swan events have almost become the norm. So these disruptions that almost seem to happen periodically, right on a very, very consistent basis, we know now that there will be an event that will cause a disruption to the entire network. But how do we overcome that disruption? How do we get as much information as possible beforehand? And then the decision-making data points that are required to be able to say okay, this has happened, what do I pivot to? And having those data points ready. I think those are becoming the primary challenges for most of the companies that are heavily invested in their supply chains, like how do they ensure that they have all the data points necessary ready to be able to make a decision and pivot as soon as an event occurs?

Speaker 1:

Got it Super interesting. Let's talk AI in action here. Obviously, it wouldn't be a tech chat if we weren't talking AI Use cases or examples. How do you use AI to improve visibility, efficiency or what other benefits do you find today? Efficiency?

Speaker 2:

or what other benefits do you find today? Sure, so AI obviously, as you can imagine, has been as revolutionizing as can be expected. I think the number one use case that we are very, very clearly seeing is specifically in the supply chain domain is unearthing data from sources that previously we thought was almost impossible, and so this has become in fact. Personally, for me, this has been the biggest revelation. Previously, you know, there were these black holes, if you will, and just extracting data from those sources which are very, very crucial but almost impossible previously to get the data that we wanted. I think AI is slowly and steadily making those data sources just part of the regular conversation, where it's slowly starting to become, oh, it's just that data source, yeah, I can absolutely pick that. And that unearthing of these new data sources, I think is making supply chains more and more accurate and more and more real time, which is probably the most important factor for supply chain networks.

Speaker 2:

So I think number one for me would be that unearthing of that data. And the second aspect I would say where I'm seeing the biggest benefit is customizing any product or feature according to that specific customer's requests. Like, if you know the SaaS world right, always customizations have been the most heavily frowned upon or, from a pure engineering perspective, it's the toughest to maintain. Like, if you have a hundred different customizations, you're bound to break one of them with one of the releases, and I think with AI, more and more, that mentality is going away and it is more about how can we ensure that we are addressing the exact problem of the customer instead of saying I've addressed this problem. Please see if this size fits you.

Speaker 1:

Fantastic. So, speaking of customers and customer success, maybe you could talk about some of your key customers, how they're leveraging your technology and some of the outcomes that they're seeing with Forkites and an auto visibility standpoint.

Speaker 2:

Quite a few of our customers are using our products like the Smithfields of the world, the Pepsi, walmart, sam's Club and so on and their primary, the biggest area where they've seen benefit is the inventory management on their side, because we provide ETAs on when a particular truck will arrive with a particular shipment and what that shipment contains, and having that visibility has definitely helped plan their inventory, accept orders even when inventory is in motion.

Speaker 2:

Previously, if you look at it, unless there is inventory at a particular warehouse, customers would never accept new orders. But now we are clearly seeing that there is a change in behavior. If they can start operationalizing the data and ensuring that, even when the inventory is in motion, customers are now willing to start incorporating that into their order lifecycle and, along with AI, like I already said, you know the accuracy and then addressing specific problems. These are getting way more magnified now, where any customer can come up with a specific problem, whether it is a procurement issue, whether it is a logistics issue, whether it is a track and trace issue or what have you Customers can very pointedly address those problems with AI. With AI and those benefits in terms of you know carrier performance on-time, in full, and so on and so forth. They're seeing multitude of benefits with these approaches.

Speaker 1:

Fantastic. Let's talk about the real-time data impact. I mean, everything in the supply chain is moving, changing second to second. You know how do you think about harnessing that real-time data? You know what are the challenges with real-time that other systems might not have, right?

Speaker 2:

So, basically, the real-time data so far has been limited to, I would say, the GPS fitted on trucks or the AIS data from vessels, or, you know, rail GPS pings and so on. But, like I said, with AI, I think, even disruption events, specific events at ports, like the berthing rates you know what is the berth occupancy rate at a given port? Similarly, what is the gate occupancy rate at a given port? Similarly, what is the gate occupancy rate at an airport Terminals, rail terminals, at any given point of time, how many rail cars are present, and so on which are becoming more and more democratized, I will say, and accessing this data and making sure that we are using it in real time. That adds a completely different dimension to the real-time nature of supply chain and that is, again, like I said, one of the biggest benefits of AI that we've unearthed.

Speaker 1:

Wow, fascinating. So you obviously track trends short-term, long-term trends as you view technology. What are some of the trends you're tracking in IT and supply chain 2025? As we kind of look into the new year, what are you excited about?

Speaker 2:

lot of the previously discussed concepts in supply chain, like whether it is the digital twin concept, whether it's the control tower concept. All of these have been given a new lease of life with AI. That's the way I'm kind of looking at it, and specifically with respect to supply chain companies and IT companies within supply chain, to supply chain companies and IT companies within supply chain, it is very, very obvious that whichever customers I visit, they have a very clear mandate to start incorporating AI into their day-to-day operations, which absolutely is the right direction, I think in 2024 or 2025. And I think more and more companies are getting to a point where they are very clear that AI is going to give them that next frontier or next plane of efficiency that has been missing. I mean, as you know, right, supply chain is a bit of a tribal domain where there are pockets which are not as modernized, and I think companies are looking at this as an opportunity to completely skip even the SaaS revolution where people were just going in with those spreadsheets and pen and papers and then marking, yeah, this truck has arrived and it's at this gate or this dock. I think, from there to how AI can manage an entire yard, or looking at incoming shipments as well as outgoing shipments, marrying the two and breaking down the silos Like we have.

Speaker 2:

Supply chain specifically, is definitely very, very siloed. To make it more simple, right, you have a procurement department, you have a logistics department, you have a transportation, you have a track and trace department, with not much communication happening between them other than just the need to know information. That actually gives rise to more inefficiency. The more and more these silos are broken down, the synergies that happen in a natural network, they can be taken advantage of. I think companies are very clearly realizing that AI is a tool that can help them break down these silos Because, like I said, previously, a lot of this data existed in papers and somebody was writing them down with pens and papers and stuff like that, whereas with AI now, if they just take a photo of that paper, ai can probably understand exactly what's going on, what is written over there.

Speaker 2:

Similarly, with cameras all over the yard, even at ports, ai knows exactly which truck is coming into a facility, which truck is going out, which dock it was in, what was packed, and so on and so forth. So, marrying information from these different sources and just managing the end-to-end, and I think that is what is attracting more companies, and very, very clearly what we're seeing is our customers have a very clear mandate to adopt AI in 2025.

Speaker 1:

That's an exciting time. It'll be an exciting year to watch. You have so much experience in this domain. How do you suggest business leaders, technology leaders, get started to drive this kind of change in their organizations? A lot of companies have very old infrastructure best practices, maybe workflows. You know infrastructure best practices, maybe workflows. What's your best advice for getting started in your experience on a journey with Forkites?

Speaker 2:

I mean, I would suggest some of the most successful approaches that I've seen are starting small, because it's a new technology, right, and people need to get used to it. There need to be new workflows built around it. There needs to be new data that's coming in to support these workflows, so it cannot be business as usual. So this is a revolution we're talking about. This is not just a small change, and so the most successful approaches, what I seen are when companies take a particular workflow or a particular task and then use AI to automate that workflow or task. Look at the learnings that they have you know the supply chain side of the domain to be able to incorporate AI to take care of one workflow or one particular task that is very, very manual in nature. Once they have one or two of these under their belt, then you can truly think about how do we adopt this company-wide. As you know, like the revolution it potentially is going to be, Well, great advice.

Speaker 1:

Thanks so much for the insights and the conversation, really eye-opening stuff, and keep up the great work. Thanks, thank you, thank you and thanks everyone for watching, listening and, as always, sharing, and see you next time, thanks, thanks, bye-bye.