Episode Transcript
[00:00:03] Speaker A: But let's bring Pawan in here.
From where? From E2open's perspective. From your perspective, Pawan, running one of the largest supply chain networks in the world, connected over 500,000 enterprises and roughly 18 billion transactions processed annually. I read.
How far has AI actually taken us so far in terms of real prediction, real forecasting or real resilience? Or is all of this promises at the moment? What does your AI strategy look like if I simplify it in that way?
[00:00:35] Speaker B: Yeah. So I would talk about it more in terms of the practice rather than what we are building right now.
I think there's been a lot of use of AI in systems. The challenge is that's not the right way to unlock a lot of things in AI. And I'll build upon what Nada said. Right. Our systems, our processes, our organizations are designed on the technology constraints from 50, 60, 70 years ago.
Right. When we did not have the connectivity that we have right now. Right. There was no Internet back then. We could barely talk over phones back then. And those phones are landlines, hardwired. We did not have compute the way we have it right now. Right. Forget cell phones, where you can actually check stuff. Barely. Desktops were barely there. And even if they were there, there were green screens, no graphical interfaces. So you actually had to tab through and do that. Right. And the largest memory, the largest processors that we had on those desktops were very, very limited. And if you had to do something, you had to actually go borrow time on a mainframe to run systems and processes. Now in that technology constrained environment, guess what happens? Processes get broken down into bite sized chunks that can be solved with the compute and the power that we have. Right. And when you do that, all of a sudden now you're designing your people around that. So all of a sudden your org structure looks like not a planning department, it looks like a demand planning department, a supply planning department, an inventory planning department, a transportation planning department.
Right. Fast forward 70 years from then. We still have organized our systems, our processes and our people are still organized the same way for the most part. Right. Very little change now. Technology has moved so far ahead, at the click of a button. Now we're having this conversation pretty much live, right? There's very little lag in our communication process. We have systems now that are hyperconnected where you can on the cloud, run such a large compute payload in milliseconds and bring that data back into desktops. We have more power in our cell phones than we had when we launched Apollo to the moon. Right. That's the technology. Now if you take a step back and think about what are we doing now, in many ways we are doing what we were doing 50, 60, 70 years ago. I run my forecasting process, I shoot it over my supply plan runs, I shoot it over a, you know, procurement process happens. I send a PO out that that process has not changed for the most part now what has really changed? And when I say AI, there's a lot of AI being used. I would say I, I would use AI as a technology, right? An evolution of the technology.
It's there. And we've been doing concepts around demand sensing, which takes not just last year's forecast and last month's forecast. We're looking at open orders, we're looking at weather patterns, we're looking at inventory availability on the retail shelves and coming up with a forecast that can be executed in lights out mode. But guess what? That's just one piece, one use of AI in one place, just around forecasting. The true power of AI is to take a step back and really rethink and reimagine what the processes should be. Now that you have hyperconnectivity, real time visibility and compute at the tip of our fingers and not just at the tip of our fingers, at the edges, like the edges of capturing a data to be able to make decisions around what happens. Like a good example, I'll use an ocean container example. I mean we move a lot of freight on reefers, refrigerated containers, right? If we can monitor the temperature on a real time basis on that and make that available to the distribution center. Anytime you break that cold chain, you're not only recognizing that container has gone bad or the cold chain is broken, you can actually say, regardless of whether the container arrives on time or not, I will have a shortage at my distribution center because all that material that I'm bringing in is probably going to get quarantined or thrown away, right. So, and it may be a six week long journey or a four week long journey and I get that signal way ahead of time that I can now process not as, not in terms of agent, but just as a raw input into my supply planning process. And say, you know, a container worth of stuff is now offline, I got to figure it out. I have three weeks to figure out what I do. And, and that is really unlocking the power of technology. I would say not even AI of technology is to really be able to connect the dots and close the loop. Right. One of the first classes that I did when I came to the US in grad school was control systems. And you realize an open loop control system where you tell somebody do this and don't find out whether that person did that or not, is an open loop system and it's designed for failure.
And a closed loop system is what you want. But if closing that loop takes you four weeks, it's too long. In this container example, if it takes you 4 milliseconds, that over the last 7 days I have constantly seen temperature going out of band. That is what I want to bring in. And that gives me an opportunity to actually open up the aperture and come up with multiple decisions. That philosophy and that concept is really what we have built our technology on at E2 open and that heritage as well as cargowise on the forwarding side. Right. So that is really what it drives us is to be able to unlock the power of technology, bring in all sorts of technologies that's available, including AI, to solve the problem based on the technology, based on the right technology at hand. AI. Nada touched upon. This is not always the right way to do things. In fact, it in many ways is a cost prohibitive way of doing things because there are better ways to actually connect and provide visibility. I still remember, Andre, you presented to us when Intro was formed. You know the communication hub that sits on a ship, it's still sitting in our office. It still inspires us to say, look, it worked. It works on a ship. It doesn't work when you're connecting multiple enterprises across the globe, right? So if we take that tool set and apply it to the current complexity of our supply chains, it'll not work. And then we'll create all these band aids and throw people at it. And that is really the power that we think is to start thinking and reimagining. It's not an easy process. It's like changing engine of an aircraft while it is still flying. You can't bring your supply chains to a stop and say come back in five years when we redesigned it and then we'll sell you the product. You got to continuously do it. And that's really where the challenge comes in is how do you change? In my mind, the order of operation should be how do you reimagine your business process? How do you reimagine the people that are going to support the business process? And then technology comes in to say here's the best way to solve that problem and it's going to be an incremental evolution.
But recognizing that need is I think the first and foremost Thing.
[00:07:00] Speaker A: Thank you, Pawan. I just. I think we had an unexpected guest there and I wouldn't want any of our listeners to feel a bit left out. So have we got a name for the dog, please? Just in case they can hear the barking and I wouldn't want to welcome them properly.
[00:07:14] Speaker B: I apologize for that. But that is Lambo. We named him Lambo. Lambo? Yeah.
[00:07:19] Speaker A: What's the breed?
[00:07:20] Speaker B: He's an Aussie doodle.
Global citizen. Here's what I'd say.
[00:07:25] Speaker A: A global citizen. Well, welcome, Lambo, to the Freight Buyers Club.
You're here for the highlight, Pawan. ETA Open just became part of Wisetech Global last year. A deal I mentioned earlier worth $2 million brought Ether Open's network planning, trade and supply chain capabilities in to the same group as CargoWise's global logistics execution platform. Sorry, stumbling over that, that most freight forwarders used, does that kind of scale and that amount of data, does that change what's possible in future? Or is more data we've sort of been referencing is data pointless? It doesn't matter how much you've got until something else changes. How does that play out? Do you see it?
[00:08:11] Speaker B: No. For us, there are two pieces of inspiration, right? One is going back to reimagining the business process, right? If you think about the. Of bringing products and services to market to how you and I consume it, it's kind of. I would largely break it up into three broad categories, right? People who are making stuff. Right. All the compute that we're using today to have this webcast is there's one group of people. Second group of people is who actually helps sell that stuff, right? We all bought our stuff from different kinds of Amazon or whatever the other stores are we bought them from. And then the third group is people who help move the product from where they're made to where they're sold. And oftentimes it's components, raw materials, but in oftentimes it's actually finished goods that get into it. So if we look at those three broad audiences, Wisetech and e2open recognized a similar design pattern of the problem. 30 years, 20, 30 years ago, it came from different directions. CargoWise looked at the world in terms of the movers of product and said a lot of that stuff is disconnected, especially around international shipments, right? And that's why cargoise was born and it incrementally built over a period of 30 years or so to get to a point where now you have everything unified. But if you do an international shipment, whether you do air, ocean or Regional shipments are you actually going through just to pure customs clearance, border crossing, all those capabilities are unified as a process flow on that platform and the underlying participants are wired into that system through an underlying network. What that really means is if I'm connected to a ocean carrier, a port or to a particular government agency for customs clearance, I can use that connection for all my customers, all my forwarders that are operating on that platform. Right. That was Cargoise's vision. E2Open came from solving a similar design problem from the perspective of people who are making products and selling products, right? So very large brand owners that had actually outsourced their manufacturing process, outsourced their distribution process, outsourced their selling process and transportation process needed a platform for orchestrating that entire end to end process. And that's where E2 Open was born. Right. So if you think about the aspirational way of designing a system that connects these processes together and connects these entities together, that is really what we're trying to do. We're bringing one of the largest quote unquote BCO manufacturer, brand owner platform, with the largest transportation platform into one quote unquote group structure that allows us to reimagine the business process and not stop at the boundaries of what a brand owner does, but continue that boundary beyond the brand owner to somebody who's moving their products within and taking the boundary where the forwarders processes start and stop and blending that into the brand owner's boundary. So if I need stuff to be moved internationally, well, I do all my planning, forecasting, planning, transportation, all that stuff and collaborate with my suppliers and then hand it over to the forwarder and say, okay, move this 10,000 widgets from point A to point B, guess what happens? There is a process drop. We want to actually continue that process into, through, through cargowise. And when Cargowise drops and says oh, it's been delivered, then you start the E2 open process and say okay, it's available at the distribution center. Now how do I get into the hands of the end consumer? How do I orchestrate the distribution process? How do I actually better plan my supply now that it's available within region? How do I transport it or how do I actually get it to that? That is really the ultimate vision. So the underlying process definition is in the platform.
The underlying network that comes with the platform is what really brings the data in. So if you want to think about data quality, oftentimes people will give you the data that they have. It's not, it's bad data, it's just that they don't understand the context in which you want to use the data, whether it's meaningful to you or not. They don't provide the context along with it. And this is what Andre's DCSA is trying to do, is not just talk about data standards, but also talk about process standards that go along with it in the high tech space. We did that with RosettaNet20, 30 years ago when Edo Open started, we were on the board of that where we are basically saying, look, everybody has data, but how do you actually transport the context of that data so that somebody actually understands it and can use it? It is bad data when you don't even know what it really means. Right? It's bad data. When I give you here's my inventory position and you look at it and say, hey, is this actually netted inventory based on your forecast or is it actually total on hand inventory where I have to do the netting? Right. If you don't have that context, you don't know if the shipment is arriving late. Well, it is late as of what date.
Right. If you give me that information, those are all very important things. So coming back to what we really want to do is to be able to think about the end to end process and let our customers drive us towards what level of end to end nest do you need? Because it's their readiness that allows us to put that in. As a technology provider, we have signed up for the technology challenge and the people process technology part. But we still need the other two dimensions of the stool, which is how do you reorganize your processes and how do you reorganize your people to leverage the technology.
Coming back to what I earlier said, technology has moved so far ahead in the last 70 years or so, we need to move our processes and our technology in it. It's a question of reimagination. So what we are really doing is we are saying how can we as technology providers be ready for that challenge as soon as our customers sign up for the challenge?
[00:13:21] Speaker A: On the other side, is there any part of that chain power and that is adapting to what you're offering or to the technology that's becoming available faster than another part of that chain? So your footprint runs from manufacturing planning all the way through to the last mile delivery.
Are they moving at different speeds? If I can put it like that,
[00:13:42] Speaker B: across that value chain, a hundred percent. I think, like I said, Mike, at the end of the day, everybody that buys software has a business to run, right? They're not going to pause that business and say, let me reimagine my process, let me rewire my systems and then I'll come back to do it. So it always is a function of where the burning problem is and it changes industry by industry and in some cases customer by customer. Like during COVID the biggest problem was where's my container? Am I going to get that container or not? And how is it going to get from where it is to where it needs to be? And am I going to be able to fill it up because I don't have the people to run my physical operations at the right facilities? That was problem du jour. And a lot of people actually solve that problem either through brute force or through deployment of technology.
Right now it's all about what happens when the tariffs change, because it's not if they will change. We've been conditioned to talk about it when it will change. So how do I actually make my transportation such that I'm bringing as much as I can within a region so I don't have to get exposed to the tariffs that may or may not change? That's, you know, topic du jour right now with, you know, the whole USMCA and US Canada and just between in the US region, but even globally it continues to have a play there. Right. So really where I'm going with this is our clients oftentimes gravitate towards the problem at hand, but the clients that are actually further ahead in terms of their maturity of thinking realize that the business environment has changed. 70 years of very stable, global structured way of dealing has been upended in the last 15 years. 10, 15 years, right. Which means that all that wiring that we built and all the interconnectedness that we built is actually exposing us to a lot more risk that needs a lot more resilience. And the clock speed of change is very, very dramatic. So some of our more mature customers are actually taking a step back and saying, look, the way of doing this with our systems and people and technology has to change. And that's where a lot of the transformation activity is happening. And a lot of activity that's happening around being able to run the business, but being able to make these incremental decisions with the long term vision in sight that these things have to change right now, but things around it also have to evolve.
[00:15:49] Speaker A: I want to bring Andre in a sec on container shipping and data and standards. But just before we finish, Pawan, on your network, where's the biggest pushback across that network? Obviously one of your orders might go through the entire value Chain, manufacturer, supplier, logistics provider, retailer.
Where's the pushback or where's the bottleneck? Is it standards? Is it trust?
[00:16:10] Speaker B: So it definitely is trust. I would say trust is number one. I think standards is super important.
But I think going back to the point Andre was making earlier, we have over the last 25, 30 years used technology to quote, unquote, work around the standards. Because one of the things that oftentimes is true is unless the standards are well thought out and adopted, people will say, I adopt a standard, but they'll always be workaround. It's standard as long as you can do these five things around it.
And that is a true definition of a standard that is either based on just information exchange that has not thought through the business context of that. And that's why I think DCSA is extremely unique in that mode. So our resistance really is number one, I don't trust you with my information.
Right. I don't know what you're going to use it for. And this is getting even worse in the day of AI because I don't trust you. I don't trust the AI that you're going to use because any information that I give you might show up tomorrow someplace else because I don't know what governance you have. Right. So trust is an absolute important issue. The second is the standards. But we can work around some of those standards. I think the third is helping people understand what is in it for me. If I give you my data, how do I benefit my business? And that's where the collaborative nature of a network becomes really important. If I'm a supplier and I actually tell you what's happening in my factory, you get better information on whether the certainty on you as a supplier being able to deliver to the PO commit or the promise that I had. That's great, but what do I get in return? Well, if the customer says what you get in return is anytime things change on my side, right. Forecast is a forecast. If my plans change, I'm going to immediately tell you what it is so you can adjust your manufacturing process. Well, if there's a give and take in terms of business outcomes, then data sharing becomes a part of. Okay, I understand now what we are trying to solve for mutually. So I'll give you my data in the context of that mutual solution of the problem and you provide me that data. And now I'm not talking about data and moving, I'm actually talking about solving a problem with information that is being exchanged to help me solve that problem. And all of a sudden you move away from noisy, bad data to a contextualized way of sharing information to solve a specific problem. And that is really, I think, an evolution that needs to happen. We play a role from a technology standpoint, but at the end of the day, it comes back to process evolution. How am I going to work with my suppliers? Not sending throwing a PO over the firewall and telling them what tell me every single step, but when I throw a PO over the wall, this is what I expect you anytime I make a change, I'm going to be cognizant about the fact that this change may be too late in the manufacturing process. So I will buy that inventory from you, but I'll give you advanced visibility.
