From the get-go, we dived deep into the crucial role that data accuracy plays in today's supply chain processes. Michael made it clear that having the right data is like the oxygen that keeps the supply chain system alive and running smoothly.
We also talked about the increasing importance of AI in supply chain management and how it's changing the game in predicting and meeting supply chain needs. Michael has some fascinating insights on this,
Next, we ventured into the future – quantum computing. Michael enlightened us on the potentials of this groundbreaking technology, predicting it to be the next big leap in handling massive amounts of data for more efficient decision-making.
Next we explored the idea of geographic diversity in supply chains. As industries worldwide are realizing the risks of relying on a single region, the concept of supply chain resilience has become more important than ever. Michael shared his thoughts on this trend and its implications for future supply chains.
In closing, we touched on the increasing trend of diversified manufacturing, especially highlighted by recent developments such as Foxconn's plant in India. It's a change that promises to foster resiliency and improve living standards in underdeveloped economies.
Whether you're a supply chain veteran or just curious about the field, there's something in this episode for you. So why wait? Dive right in and join us for this exploration of the digital supply chain universe.
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Companies now are facing the reality that they can try to understand what's gonna change in the future to the best of their ability. That's risk management. But what they really need to do is adapt for any and all inevitabilities. And to do that, you have to be more diverse and more resilient and be able to change more quicklyTom Raftery:
Good morning, good afternoon, or good evening, wherever you are in the world. This is the Digital Supply Chain podcast, the number one podcast focusing on the digitization of supply chain, and I'm your host, Tom Raftery. Hi everyone, and welcome to episode 319 of the Digital Supply Chain Podcast. My name is Tom Raftery and I'm excited to be here with you today sharing the latest insights and trends in supply chain. Before we kick off today's show, I want to take a quick moment to express my gratitude to all of this podcast's, amazing supporters. Your support has been instrumental in keeping the podcast going, and I'm truly grateful for each and every one of you. If you're not already a supporter, I'd like to encourage you to consider joining our community of like-minded individuals who are passionate about supply chain. Supporting the podcast is easy and affordable. With options starting as low as just three euros or dollars a month, that's less than the cost of a cup of coffee, and your support will make a huge difference in keeping this show going strong. To become a supporter, simply click on the support link in the show notes of this or any episode. Or visit tiny url.com/dsc pod. Now, without further ado, I'd like to introduce today's special guest, Michael. Michael, welcome to the podcast. Would you like to introduce yourself?Michael Farlekas:
Thanks Tom. Really appreciate the opportunity to talk to, uh, you and your uh, members today. My name is, Michael Farlekas. I'm the CEO of e2open. We're a, uh, digital supply chain software company. We focus on, uh, the biggest companies and the mo most complex supply chains in the world.Tom Raftery:
Okay. And when you focus on those big companies with complex supply chains, what are you doing for them?Michael Farlekas:
We're helping them with their end-to-end supply chain management needs, and that means starting with the manufacturing side. Their suppliers and their supplier suppliers, and connecting them to one digital platform. And then we take that concept and all the way through to the sell-through to how they interact with their channel partners and their retailer partners, and everything in between. So in terms of transportation, logistics, planning, we're an end platform and we have a network of about 420,000 connected parties that our clients utilize to have an active and active supply chain.Tom Raftery:
Okay. And. Let me just get into a little bit of the origin story of e2open. How long has e2open been around and who set it up and when and why?Michael Farlekas:
It's a great story. The business was founded in, uh, 2001 or 2002, and interestingly, it was a, a cloud-based software company when there was no cloud, 2000 or 2002, right? There was no subscription. And there was no, uh, no, I, no concept of cloud software. And, uh, the reason it performed that way is because it, it was, uh, created by a consortium of high tech manufacturers and those manufacturers came together to solve one particular problem, which was to help them, manage the supply chain across multiple tier manufacturers, which meant they needed to connect live from, you know, their manufacturing sites to all of their supplier sites. And, uh, the, the system and product they created was essentially a way of connecting all of their suppliers and hundreds of them into one system so everybody could see what was happening live in their supply chain as it changed. So if I was a manufacturer, got an order, I could literally automatically send the information to my suppliers and their suppliers and my co-manufacturers and my contract manufacturer's systems automatically. So everybody could operate as one, even though they were different companies on distributed systems. That's how the company was founded. And, and you know, obviously you could not do that with on-premise software cause it's essentially a connection oriented approach. And it grew and it grew from there and to all the size we are now. And, uh, you know, we're one of the largest, supply chain software companies in the cloud and we've taken that concept and we've expanded it all the way across the entire supply chain because that problem that the company solved originally is really the entire problem of supply chain because brand owners, the largest companies in the world, actually don't make products as much as you think. They don't sell products that goes through the channel. Their retailers, they don't ship products themselves. They, they hire, you know, trucking companies to do that. They have store it themselves, they hire 3PLs for that. So their job is really as brand owners to orchestrate the complex supply chain, across, you know, thousands of suppliers. And what we do that's distinct and different is we connect them live to that supply base. And that makes them more effective in terms of how they manage their data and utilize data live and make better decisions going forward. So that's how the company was formed. It's a remarkable application. I, I joined, uh, the company eight years ago and I've been in the supply chain software world my entire life. And the first demo I saw, my eyes opened wide up and. I said, well, that's really the problem everybody has, not just on manufacturing side. So that's how we built the business.Tom Raftery:
Nice, nice, nice. And in terms of networks that, I mean, you mentioned that you've got a network with 420,000, I think nodes on the network. Yeah. How do you, how do you start and, and build that out? Because networks always have this problem. The, the, the network effect If you've one person on a network and no one else, you know, you're not gonna achieve very much. If you have two people that can just talk to each other and no one else, you know, it's only when you start to get to big numbers that a network becomes useful.Michael Farlekas:
Yeah, I mean it's uh, it's a very, that's very clear. Uh, and that's how it works. So networks take a very long time to form, you know, in order of magnitude of decades, 10, 15 years. And it opens, the original network was on the supply side, and that network took 15 years to form. And when we, uh, came into the business, it was about 45,000, you know, companies strong. And when we thought about what this business could be, We, uh, kind of identified that there are other networks out there that we could, combine to make a more cohesive and larger network. And we looked for networked, oriented companies that had formed the same way and built themselves over time. And we acquired about, 14 companies in seven years. Many each had their own networks, many of which formed in the same way that, you know, open formed, you know, way back, you know. 10, 15 years ago, and they start small with one customer. They grow and they grow and add somebody. And then pretty soon they have a large network and we've, you know, combined them into one. And our, our key enabler is an application that allows us to harmonize and synchronize data on a massive scale. So we can combine these networks to operate as one and then allow us to use data across any number of application sets. So, basically to answer your question is, is they all form the same way either through an application company, a consortium, kind of requiring everybody to join and then we assembled them and put them into one platform. That's how we've got into that size of 420,000 or so network providers, the largest, lux and world by lot.Tom Raftery:
Wow. Impressive. Impressive. And the supply chains now are becoming increasingly complex, with more and more, you know, second, third, fourth tier suppliers in lots of different countries. Yep. That's adding issues in terms of data visibility, in terms of resilience, what are you seeing on that front?Michael Farlekas:
It's the, that is the problem in my opinion, is, How do you, you know, get more complete, more accurate, and, and most importantly, more timely data into applications that can make automated decisions. If you don't have the data, the applications or the algorithms or the AI or whatever mechanism, you know, the, compute power is gonna be used to make a decision, can't make the most effective decision unless it has all the data. So that really becomes the issue, is how do you connect as timely as possible? And, uh, since the data sources are by definition very disparate you know, hundreds of different connection points, you have to have some way of making that data useful for uh, you know, some type of algorithm to access and use and use the data points to make a decision. That that is to me the essential problem of making supply chains more you know, more, more effective and to have less disruptions and to avoid problems in the future? I think a lot, our best customers really are the best at avoiding problems in the future because they have the most data they can see out further. So many of the things that they companies had to deal with in the covid period, many of our clients kind of avoided in the first place cuz they could see what's happening more clearly because of the access to data.Tom Raftery:
Wow, that's impressive. And are there any particular industries that you guys work with or are you across the board on that front?Michael Farlekas:
Across the board we're, we're probably skew a little bit towards manufacturing but increasingly towards the retail side. But in manufacturing it's really across the board. So, you know, you can break industries down into process manufacturing industries and discreet manufacturing industries and, and apparel, that three generalized categories. And we have, you know, very large customers in each of those. Each have the same problem, but the, the variant or flavor is slightly different. In terms of what their most critical burning, you know, platform is. And you know, one of the reasons we've built a broad platform is that we can handle the need set of many, you know, types of customers within, one, you know, application framework. So we're across industry and we're equally not little more skewed towards, uh, north America, I, especially North America and, uh, and client base.Tom Raftery:
Okay. Supply chain resilience and supply chain risk are two themes that have really been emerging in the last few years as, you know, some of, some of the things that supply chain professionals have been most concerned about. Is that something that you're seeing reflected as well in your conversations?Michael Farlekas:
It's, uh, it's really the, what companies now are trying to solve for. And it, it kind of, goes back to how supply chain concepts have now evolved, and I'll kind of put it in the post covid era and, but it's, I I don't really mean it to be just covid in the last, say three to four years, you've had more globally scaled disruptions and changes you know, in our economic environment and we may have had in the last 50 years. I mean, you just think of. Even before Covid, I mean, you know, the, the US government decides to change their entire tariff regime in basically three months. Now, companies have built their entire supply chains based on a tariff regime that was pretty stable for the previous, you know, 10 years. And all of a sudden the, the tariffs changed and that changes the economics. That changes the gross margin of a product. We had to scramble. Then behind that, you have covid, like right behind that yet. Which was remarkable because you've never, in the history of humankind, have decided to shut down economies and literally say, we're gonna shut 'em down and on purpose, and then a year and two years later we're gonna started back up. And then in between you have, you know, war and all the other things. So my point is companies now are, facing the reality that they can try to understand what's gonna change in the future to the best of their ability. That's risk management. But what they really need to do is adapt for any and all inevitabilities. And to do that, you have to be more diverse and more resilient and be able to change more quickly. And you have to leave this idea of building a very static, uh, maybe very lean but very static supply chain where it's very, programmatic. I make it here, I ship it here, and it runs the same way. And the companies are, are now kind of understanding that supply chains affect the top line and the bottom line, where in the past it was mostly a bottom line issue in terms of margins. And now I think boards are waking, you know, said, saw that it affects the top line, because if I don't have the product where it needs to be, I can't sell it. So I need to just build in an ability to get product where it needs to be all the time, regardless of the disruption. That, that is what I'm hearing from all of our clients. That's kind of their main focus. Is to, how do I do that without increasing my costs or increasing my costs too much? But the prerogative is I need to be more resilient. I need to be able to adjust more quickly. And for that, I need a different kind of, infrastructure digitally to allow me to operate in many ways all at the same time.Tom Raftery:
Okay. What about things like changing regulations? Because we're seeing a lot of regulations changing, particularly here in Europe now, in terms of things like, child labor and slavery and supply chains and the movement towards both in the US and the EU towards reporting around sustainability as well.Michael Farlekas:
More of the same? More of the same. Cause if you kind of think about what that implies. If, if countries change their regulations or change their laws or their tariffs, somebody has to understand what that means and those changes across, you know, 200 or so major countries in the world. And those changes have to be adjusted in the software itself because just, you know, you can't just assume that everybody knows that in this country you have to watch out for these issues where I, I can no longer ship some product, from this country because the regulation changed somewhere. You, you have to be able to, in a systematic way, collect that information and codify that into, an application. So the application, you know, is what issue, and then you automatically get, you know, the information coming from the countries in a, so, in effect, that's part of our, in our case, it's part of our network is collecting that data as it changes every single day. So our clients can, reap the benefits of knowing that doesn't matter what the changes are, the system is going to be able to understand them and protect them. And then, adjust kind of in a semi-automatic way. And the same thing in terms of emissions and in terms of, you know, carbon is that, you know, you're gonna have to understand not only what your carbon footprint is, but those of your suppliers and your suppliers. Mm-hmm. So, That's simple to say, harder to do because it implies I have to understand exactly what was shipped in, in what order of magnitude by each of my suppliers, which changes over time. So I had to have a somewhat automated way to capture that. Yeah, you can't just do it in a spreadsheet, like it, it'd be too hard. So all of that leads to kind of the same things, which is the only way really to solve the problem is to kind of think about it from a system or network perspective. Because the brand owners are not doing all this work themselves. They're essentially outsourcing all the activity, which means they have a responsibility to understand that their partners are following great list regulations, that they understand what the carbon footprint is. So all of these things lead back to the same place, which is supply chains need to be more connected. It's the most obvious thing in the world. It's in the name. Supply chains are connected, but yet if you really kind of peek under the covers, most of the technical and, and, uh, digital infrastructure for most companies is still widely not connected, and it's not very manually. That's the, that's what will change over the next five or 10 years.Tom Raftery:
Yeah. Do you think, this is a kind of a facetious question really, so I, I apologize in advance, but do you think it, that, that the term supply chain is a misnomer? It should be supply web, maybe.Michael Farlekas:
Yeah. Or network, you know, or network. The, the reason it network, right? It's just, it's, it's easier because every, it's a very visual connotation, right? So if you say chain, everybody kind of can visually understand what a chain is, right? If you say somebody, a network, it's a bit hard to create an image in your brain of what a network is, right? And it's very specific to the individual. So I, I, I don't think it's particularly useful actually, but it's particularly useful practically because it's very visual and the names are usually visual things because people are mostly visual. So I, I don't think it's gonna change, but the people that are practitioners of it you know, understand that it's actually a network. And it's a mesh network, right? Because, me as a manufacturer, have suppliers and I have all sorts of issue relationships across the board. So, networks I mean, supply chains are increasingly being networked. That will remain, that will become, you know, more ubiquitous. But I think we'll still call 'em supply chains for a long time.Tom Raftery:
That's fair enough. Fair enough. There's an another question If we are starting to see more of a move towards sustainability, do you think that people will start to look down through their suppliers and choose suppliers based, not just on their pricing, but also on their carbon footprint?Michael Farlekas:
I, I think so. I mean, you know, like, like in all management, the first thing you have to know, you everything have to do is understand. And that's the first step at any, you know, effective management structure. I need to understand. And right now companies can't understand. Like as it was impossible to understand. And once I understand, then I can measure. Yeah. And once I can measure, then I can put a goal against it. And then the goal becomes, okay, how do I make that goal? And then that's what you suggested happens because I now have a goal that I can measure against. And if I want to improve, find a way to improve. How do I do that? One of the ways would be, well, to ship less, the other way would be ship with people that have a lower carbon footprint, or most likely they'll do both of those things right to, to get the maximum effect. So I think, uh, it will but I think the predicate is I have to understand, and if you can't understand, you can't measure. If you can't measure, you can't really set an effective goal. Therefore you can't make that part of your decision making, you know, uh, process.Tom Raftery:
Sure. Sure, sure, sure. Another topic that's in the news quite a lot lately is AI. Is that something that you guys are working with as well?Michael Farlekas:
Uh, have been for a long time. Uh, and AI is a, you know, a very generalized term. Mm-hmm. And, you know, it can be hyped easily. It means different things to different people. Sure. And you see a lot of capital rush into something called AI. But reality is, is, you know, AI and machine learning have been, you know, is, is functioning and has been in many of our applications for, you know, 7, 8, 9 or 10 years. You know, the idea that we can take more and more data points and the system itself can learn from itself is something that, for instance, we've been doing for, you know, almost 10 years now. I mean, we have applications that literally forecast future demand by understanding the predictive value of data elements that might be different. Might have 25 data elements for a product, and the system can figure out what's more predictive by going back and back testing on its own, what would've been better and then it retools itself. So these concepts are, are in place. We use them kind of every day. What makes our applications, you know, super valuable? There'll be next generation ai. There'll be, you know, the thing after ai. You know, my, my opinion remains the same, which is you'll always find better uses of compute power to make better decisions provided you have data. Yeah. Like, without the data, you, AI can't make a decision. Just doesn't really work. So, you know, for us, it's not just the AI that matters, it's providing our clients with really excellent, you know, decision making using AI and lots of different techniques that are appropriate for the case, but more importantly, providing them the most complete, the most timely and the most accurate data. So that, the decision making tools to make the best decision. So to me, you need both. You need data and you need, you know, advanced algorithm and, uh, you know, technology's a wonderful thing. And what I've learned about technology for my entire career of 20 years is, you can never predict what the next thing is gonna be, but you can always predict there's gonna be a next thing. And the question is, is how do you adapt and, and, and use that for the benefit of, you know, your company, your constituents, and all this leads to the same place Tom which is, you know, if you can use technology more effectively, you can reduce the cost of the goods you make sure. And that's a worthy journey, right? Like it's, it's helpful cause it, it means you can over time improve the standard of things because you reduce the amount of effort cost to make 'em bring a product to market. So, that's kind of how I see it.Tom Raftery:
Okay, fair enough. I know you said you can't predict the, the next thing, but my next question is what's, what's the next thing, but not specifically the next thing, but you know, Where to from here, what do you see, maybe not in technol in technology terms, but what do you see in supply chains as being the next big things coming down the line that people can expect?Michael Farlekas:
Yeah. You know, if you think about I, I think a lot about enabling technologies and enabling technologies open up doors for additional innovation as an example. Digital mobile phone. It was an enabling technology. Being able to not just speak to somebody with a mobile phone but be able to transmit data, you know, in massive quantities. Digital or mob mobilely over the air enabled so many other use cases that nobody could have ever even predicted. You know, I think AI will be enabling technology cloud, obviously enabling technology, the ability to virtualize servers. And kind spread compute power across multiples an enabling technology. Without those things you like, without virtualization, you can never have the cloud, right? Yeah. Because it, it, it really wouldn't make economic sense, right? So because you have that, you have, that, you have um, you know, the cloud. Because you have the cloud right now I can think about wanting AI across bigger data sets cuz my data's accumulated. Very valuable. My, my, you know, what I think about is really more that type of technology changes, which to me the next big one will be quantum computing, which is a, you know, fundamentally a different way of thinking about how, you know, machines can make a decision using arrays and vastly different points of data rather than sequential data. And yeah, it is a fundamental shift and, uh, to me that'll be the next enabling technology. But you know, we're some ways away from that, but that to me is kind of, would be the big thing. It all goes back to how quickly you can process massive amounts of data and the more quickly you can do that means you can put more data in the system, which means you're gonna always have better decision making with more.Tom Raftery:
Cool. Cool, cool. We're coming towards the end of the podcast now, Michael, is there any question that I haven't asked that you wish I had? Or is there any aspect of this that we haven't touched on that you think it's important for people to think about?Michael Farlekas:
I think the one thing that I've noticed, and you kind of see this was an article about Foxconn building a big plant in India. I think the, continued diversification of manufacturing points globally also is a pretty, pretty important development. And that goes back to this idea of resiliency and diversity, and really kind of de-indexing off of one geography and companies, fundamentally rethinking, their entire global footprint. And I think that's gonna have pretty important implications over the next 10 years. You know, when you, think about, the underdeveloped economies now getting infrastructure and capital inserted into it that'll change things. That, that means it'll change things for people that are living there. They'll over time improve the standard of livings. And it'll tend to have better and more resilient you know, ability to manufacture and ship and bring product to market. So I think that's a pretty big deal. And the evidence there is pretty clear where lots of us are being made in lots of regions around the world. And that's a change from most of the investments being made in basically China for the past 20 years. I think that is, is real. It's de burns de-indexing, and I don't really think of this as a China issue specifically. I think it goes back, companies can't be reliant on one thing anymore. They have to think about, you know, their business in the 20 year context. And they have to say, how do I position myself to be able to operate no matter what happens and be effective no matter what happens. And I think that's probably a, a, a good development for everybody.Tom Raftery:
Okay. Something about eggs and baskets, I think. Is itMichael Farlekas:
eggs and baskets? Yes, that's true. Exactly.Tom Raftery:
Cool, cool. Okay. Michael, if people would like to know more about yourself or any of the things we discussed in the podcast today, where would you have me direct them?Michael Farlekas:
Well, obviously I'm on LinkedIn, so you can just send me a note there. And e2open dot com. E the number two, open, dot com is where you can see all the information. And love to hear from everybody and, uh, your comments and questions and I generally respond. So, uh, let me have it be great.Tom Raftery:
Fantastic. Fantastic. Michael, that's been great. Thanks a million for coming in for coming on the podcast today.Michael Farlekas:
Thank you, Tom. Have a great one.Tom Raftery:
Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about digital supply chains, simply drop me an email to TomRaftery@outlook.com If you like the show, please don't forget to click Follow on it in your podcast application of choice to be sure to get new episodes as soon as they're published Also, please don't forget to rate and review the podcast. It really does help new people to find a show. Thanks, catch you all next time.