Telecommunications Industry Anticipates and is Prepping to Adapt to Increasing Changes

Hello, everyone, and welcome to another episode of Wavelengths, an Amphenol Broadband Solutions podcast. I'm your host, Daniel Litwin, the voice of b two b. It's good to be back in the ABS hot seat with some great conversations, some thought leadership, and more generally, some analysis on the state of the larger telco broadband industries and the major trends that are shaping their development. That's exactly what we're gonna hone in on with today's conversation. It's sort of the theme of the larger show, but we're really getting a future focused lens for our two guest chat today. But before we introduce the topic and our guests, I wanna make sure you're all caught up on previous episodes of the show. So make sure that you're heading to our website, amphenol broadband dot com. Again, that's amphenol broadband dot com. For, again, previous episodes of Wavelengths, we have plenty of great long form conversations with top thought leaders across the industry where we cover everything from bead funding to specific technologies that are reshaping, the larger industry to, trends and pulse checks on market movers. So check that out there or on your favorite podcast streaming app. We can, access all and future episodes on Apple Podcasts and Spotify. So make sure you subscribe so you don't miss out on future episodes of Wavelengths. Alright, team. Let's jump into today's episode. So with today's conversation on Wavelengths, we're going to be looking at what's in store for the larger telecom industry and how ABS fits into that future. So we're both looking externally and internally with today's conversation. Namely, we're gonna be looking at the big three defining trends that are shaping the industry today, its services, its infrastructure, and its market development. And that would be major evolutions in demand forecasting, some of the industry overhauling that we're seeing as a consequence of government programs and their investments, and some of the promises and challenges of cutting edge tech in managing those trends like artificial intelligence. So we're gonna connect all those dots here with today's conversation. In this era that's being defined by rapid technological shifts and unexpected market dynamics, The backbone of global connectivity is under some pressure, but also has a lot of fresh opportunities to take advantage of. Companies stand at this crossroads, right, of innovation as well as necessity as they navigate the complexities of demand surges as well as massive funding and the subsequent operational and execution challenges of making good on that funding from governmental initiatives like BEED, the Broadband Equity Access Access and Deployment Program to revitalize broadband across the entire United States. So this intersection of technology and policy demands a new caliber of foresight and strategic planning as the industry prepares for a bulk of new customers, a bulk of new collaborators, and a bulk of new projects to execute on. So today, we are diving deep into those challenges of aligning supply chain management with ever shifting consumer governmental demands, and how fostering strong partnerships throughout the supply chain as well as looking inward and making sure that if you're a player in the industry, your operations and strategies are aligned with those goals. How all of that can, help lead to greater resilience and efficiency, again, in solving some of these challenges. So we'll pose some questions and answer them with our, conversation today. How should the telco industry remain agile in this dynamic environment, and what lessons can the broader industry draw from Amphenol Broadband Solutions' larger approach and strategies to things like predictive planning and customer collaboration? And where does AI intersect with all of this? Well, let's get to the meat of the episode. I'm pleased to welcome our two guests on today's episode of Wavelength. We're joined by Bill O'Donnell. He's senior director of technical operations and customer service support at ABS. Bill, welcome to the show. How are you doing today? Hi, Daniel. Thank you for having me on the show today. Absolutely love listening to your podcast. You're you're so smooth at what you do, so, hopefully, you'll make us look good today. Hey. I don't have to work that hard, and I appreciate you tuning in. But, hey, it's just as much your podcast as it is mine, so I'm excited to collaborate on some great thought leadership today. So thanks for joining us. And we're also joined today by mister Barry Holt. He's VP of global cable operations at ABS. Barry, welcome as well. How are you today? Good. Thank you, Daniel. I appreciate it. Nice being here. Me and Bill work, together for many years. So it's, yeah, like getting together again. Yeah. Exactly. Right? It's just, you know, an another sit down at the local dive and, having a chat. Right? So it's, it's gonna be great to feed off y'all's energy there and, obviously, your insights and expertise here on these major trends shaping the industry. So thanks again to Bill and Barry for joining us on the episode. Let's get right into it. There's a lot to unpack, and we've got two voices to hear from on these questions. So to kick things off, I think we need to level set and get a a pulse check like we typically do on the show on the context, right, that's surrounding why we're even having this conversation in the first place. So could you both provide an overview of some of the current trends in the larger telco industry, especially in terms of demand forecasting and, the impact of global supply chain challenges and how they're kinda shaping conversations, pressures, etcetera in the larger industry. Just give us that, high level pulse check. Yeah. I can, start off, Daniel. You know, I mean, this is an exciting time for us in the industry because, you know, governments around the world are are seeing the advancements of the, you know, the networks of connecting people together and and getting that that broadband access to everyone in the world. I mean, you're you're seeing it with, you know, broadband, seeing it with satellite connectivity. So it's it's definitely putting some some demand, on the market, but it it's good demand. You know, the the big thing that we see overall is that, you know, with all this government spend that's going on, it it takes a lot of infrastructure, a lot of capital to to get things, you know, moving so that you can have a smooth supply chain. You know, we we first saw it with the Artoff. You know, Artoff invested, you know, twenty billion dollars into infrastructure just in the US alone. And in order to, you know, provide those products, you know, people like Barry had to, to ramp up and and do some, you know, extraordinary work to try to get products out to people. So, I mean, Barry can kinda tell you some of the the struggles he had on that initial overview of what's going on with supply chains. Yeah. It's I I think coming out of, COVID, you know, everybody kinda panicked. There was a interruption in the supply chain. In that period, I I know for sure the whole globe realized how close we were up to that point. Like, even internal, we ran out of stuff. We didn't realize how tight the chain was to China, how contingent it is on where the containers are. You know? And everybody got that from ordering, like, a canoe or a bike or whatever. You you know, everything went to, like, eight, ten months. And I think that's that was a realization for everybody how closely we're linked. And it's a like think that affected the whole world. And then I think that affected the whole world. And then coming out of it with this huge spend, you know, trying to ramp up, and the supply chain kind of broken at that point really, you know, changed the way we do everything. So it's, yeah, it was difficult times. I think we're actually kind of getting through it right now, but it it changed the way we do business. We don't we don't count on those, supply chains as much as we used to. We've we had to find alternates. We had to find different paths. But, but it it was an eye opener for everybody, and it's, it's gonna be it's gonna change forever. You know, what we ended up seeing, Daniel, is that customers, they wanted everything quick, you know, but they still wanted it at the same price that they had before. And when the supply chains became broken, you know, you had to look for sources that were domestic or or closer to your manufacturing facilities. So I always go back to that old saying, you know, better, faster, cheaper. You know, you can have two of the three, you know, because if you want it fast, it's not gonna be cheap. If you want it better, it's not gonna be, you know, it's not gonna be fast or cheap. You know? So it's it's definitely a challenge, you know, from the customer side, you know, especially when demand spikes like it does. You know, I have, I saw one the other day. So a couple years ago, it's like, we tried to buy a canoe. So if I don't know if you guys tried to buy a canoe just after COVID. It was, like, seventeen months or something. It was crazy. So there's a store not too far from me, and I go there now. They've got, like, six hundred canoes. Everything's on sale. You know? And that's that's actually exactly what we saw in our business. People ordered like crazy. It took a year, and then it didn't take a year. It took six months, and this thing got caught up. Everybody had double ordered. And, you know, we were the same. And it's it's for everything, but there's lots of lots of visual reminders just in in the stores around you now. Bikes too. So bicycles were crazy, and now it's like everywhere you turn, there's a hundred bikes for sale on the street. Yeah. And like y'all were saying, so much of this is consumer driven. Right? I mean, obviously, when we're talking about supply chain challenges, those aren't always consumer driven. Oftentimes, they are, you know, it's in the name. They're supply side. Right? And those are somewhat out of the hands of any individual consumer and their trends or preferences or, out of the hands of any one company or industry and their operations. But at the same time, what is consumer driven is where we see pressures on the supply chain and where we see major surges in demand. And as people, you know, get back into the swing of things, we're now sort of you know, COVID is behind us, the pandemic, and these major supply chain challenges that put a halt on things are more or less behind us. We've absorbed and learned, you know, from a lot of those slowdowns and disruptions and now can, you know, better pivot when we do see, for example, the Baltimore port closure, and how that's now sort of rippling out into the domestic and the international supply chain. You know, all of these ecosystems are being impacted by and shaped by a consumer base that, you know, even with inflation and even with some pressures on the pocket, are still eager to spend and still, you know, increasingly have a desire for their services and their solutions to be efficient, quick, and always on. Right? No downtime. So with that comes pressures on, demand surges and, obviously, demand forecasting as well on the industry. So I'm curious if y'all could give us a pulse check on those trends. Right? When we talk about, you know, this challenge of demand surges and, you know, the intricacies of realigning demand forecast strategies in this industry. What does that actually mean in practice? Give our audience some context. Well, I mean, I can I can start off with this? I mean, if you look at what we had back in, you know, twenty twenty two with the rural development fund, you know, RDOF. I mean, that was a twenty billion dollar spend. Now all of a sudden you get into this bead, this broadband equity, access deployment. That's gonna be double that at forty two million or a billion dollars. So, you know, right there, you see that if this demand comes all at once, kind of like RDOF does, you're gonna have to to plan accordingly, and you're gonna have to scale up and scale down. So, you know, I mean, there's with all this large scale funding, you know, there's a lot of competition out there. You know, there's a lot of people that are gonna be able to to enter into the broadband space and start doing development and construction. So, I mean, it's it's definitely gonna allow economic growth for a lot of different sectors. I mean, you're gonna be able to, you know, have rural development you know, rural people that'll now have access to this Internet that can now work from home. You know? So it's gonna be a game changer, I think. And I think we are poised to be, like, you know, at the center of this, you know, this program to to really help bring broadband to the nation. So it it feels good knowing that the products you're making are someday gonna, you know, power all of the homes with Internet, you know, throughout the US. So it's it's exciting. It's gonna definitely take some some and that's where Barry and I work close together to to try to figure out what's the happy medium here. Yeah. And it's what it's really created there honestly, our industry has never been great at forecasting, but there was never never huge swings. So almost everybody just stocks a little bit more. You you add a little bit of padding in it to get you over the humps, and that's always worked. And then, you know, over the last couple years, there's been drastic swings, you know, from double the production to half the production in a short period of time, and it really stung everybody with a high inventory. So now it's like we're pushing and bills on the front end of it. Like, we're pushing hard that the forecasts have to be more accurate. You know, we can handle normal flow, but like Bill said, you're gonna add all this money to it. What is the effect? It's gonna double or triple it? You know, what's the lead time on that? And so far, you know, they're still in kind of the stages of planning what's gonna do and, you know, implementing it. So everybody's talking like monster numbers, but they don't know if it's, you know, is that six months? Is it a year? When am I gonna need it? There nobody's willing to commit to anything. So we're in a we're in a really tough period where we're pressing hard harder than we ever have that we gotta have some kind of forecast. And I think people have now been burned, you know, with long link times and stuff. So they know, like, we're not pushing for no reason. We're saying, look. You you can't you can't double double your your need in a short period of time. You're gonna have to give it some time, because, yeah, as Bill knows, you know, a lot of these funds have a limited deployment period. You know? If they take the government money, they have to install it and have it finished by a certain amount of time. But there's not you know, they're gonna have to give us some kind of forecast to work in that order. Some of those dates are gonna be impossible. So, yeah, it's it's a change for us. You get you gotta you gotta work at those spikes. We need we need more input. We need to be closer to the customer, you know, to get that information or it's or it's gonna be trouble for sure. Our teams, I mean, they they're trying to work at the corporate level at all of these operators. To understand, like, you know, what is your involvement in Indeed? What is it going to be like? But what we've learned by doing the art off piece of it is that you really have to be at the field level too to understand, like, you know, what projects are taking off? When are they gonna start? Do you have the manpower to actually do the installations? What we saw was that, you know, the operators at a corporate level were ordering like crazy. And by the time the supply chain caught up, they were bloated with inventory and not enough people to do the installation of the work. So you weren't consuming as fast as you were ordering. So, you know, what does that result in? Well, it results in they're overstocked. They've got too much capital. We've got too much raw materials. We've ramped up production. Now we gotta ramp back down. Our raw material vendors ramped up, and now they've got too much material. So it's a butterfly effect throughout the industry that, you know, when they shut off the spigot, you know, it might take six months to work all the way through. So same with the reverse. If we're not forecasting properly, it's it's gonna take another six months to ramp back up. You know, everybody in the chain didn't act, you know, perfectly, I'd say. So there's a there's a lot out there of crying wolf. So now it's, you know, when you come to me and everything's gonna be doubled or tripled in a short period of time, like, we're we're kinda evaluating, well, you know, that's what you already told us. But I'm I have the same from our vendors. You know? We doubled production. Now they're coming back, and we're saying, hey. We're gonna need this. And they're kinda like, yeah. Okay. You know? You let you let us know when it comes. So there's, like, that creates a little more lag. You know? And it's it's just, again, needs need to be closer to the whole chain and make sure that we're partners in this, not just, not just bloating it with false facts. And, you know, from the insights that I got from one of the last episodes that we did on the show, which was our bead funding panel. It was a great panel. If you haven't heard it, audience, I recommend you go give it a listen because it was rather candid about some of the challenges that the industry is going to face as it makes use of and actually starts to, well, begin execution on these rural broadband project deployments, with bead funding, one of the big takeaways that stood out to me was the challenge that the supply chain in general and also sort of the relationships between the, service providers, the contractors, the cities, how, you know, missing chain links essentially in those various relationships are gonna make it so that executing on this funding and developing these projects in any kind of reasonable time is gonna take way more work and planning than maybe, you know, know, industry players are even considering today, including things like getting the needed skilled labor to execute on these projects, aligning supply chains for the parts and pieces that are going to be essential for building out all this new infrastructure at scale and in a a a quick, you know, turnaround. So with that as context, I'm curious if y'all could give us a little more insight into the role that Bede is playing here. Right? How are some of these government funded programs like Bede, influencing some of the market dynamics and the demand surges for telecommunication services, products, projects? Give us your analysis. I mean, I can start off on the customer side of it. I mean, we've been actively, you know, soliciting information. We've been looking at the websites. We're seeing who is, you know, receiving funding for BEED. You know? And when we talk to these individuals, you know, like you said, they're still in the planning phase. I mean, this is a huge, huge undertaking. You know, when you had art off, it was like, you know, here's a billion dollars, go build some stuff. But with bead, it's a little different where you've gotta submit your applications. You've gotta submit all of your your deadlines and when you're gonna be building it. You have to pay for it upfront, and then they're gonna, you know, reimburse you or give out payments. You know, that's it's pretty capital intensive, especially in a market that's got high interest rates right now for funding. So, you know, while we haven't really seen the tsunami hit yet, you know, we're definitely looking for markers out there to say, like, are we are we seeing some of the waves roll in? Because, you know, with Artoff, we didn't have much of a a chance. We just were looking up at this huge tsunami coming at us, and there wasn't way out of it except for, you know, paddling as hard as we could. But now we're we're looking at those rolling waves and we're like, okay. Let's let's see. Is this getting closer to shore? And as of right now, I mean, on our side, we're not seeing the huge spike just yet. But, you know, I'm hoping that it'll be coming because, I mean, it's a great program. And it's, I think, at the base of it on both sides, it's, labor. You know, it's hard to find skilled labor right now. It's, it's to fill any jobs is is such a long period of time. You know? And a a lot of times, the people in the market or, you know, some people that have bounced around a bit. So I think that's it's gonna be a huge driver in this. When the wave comes, I it's it's very tough for everybody to find skilled labor on both sides, both on the production side, but on the front side to do the work. And it's like, I think that's some of the concerns. It's where is this labor gonna come from. You know, we all see in our neighborhoods and our fun places closing down because they can't find labor. I've never in my lifetime seen places close saying I can't keep employees or, you know, I can't get anybody to do the work. And then, you know, just flooding it with the money, I I think they're they're gonna have to put a lot of lot of time and effort into the training on the background, and it's I I think looking how you're gonna how you're gonna move into this and provide that, it's a it's a major issue if it comes in a in a huge way for sure. You know, it's it's like data center work. Right? You know, you can find anybody that can do data center work because it's a relatively easy put a connector on, crimp it down, test it. But when you come to cable, I mean, you have to have a really wide skill set of, you know, hard line connectorization, fiber. You know, like you said, it's a very small scope of people that really know it all. And then second of all, I mean, I'm out in Arizona where it's a hundred and fifteen degrees. You you can't get someone to go out in the summer and, install something for less than forty dollars an hour. You know? And in Canada, you guys are like ice cubes up there most of the year, so I I I don't know how you do it up there. We deal with it. You guys hide. Yeah. Exactly. Well, like we promised and thank you for all that industry context. Like we promised on this episode, we're gonna be looking inward as well and trying to learn a bit from how Amphenol Broadband Solutions is reacting to some of these trends and what the larger industry can learn from, you know, your approaches to things like demand forecasting, aligning your supply chains and partners to execute, you know, preparing for some of these inevitabilities, whether they're disruptions or slowdowns, and some of the unexpected ones as well as most of the supply chain challenges we've seen in the last several years have been rather unexpected. And regardless, you know, industry has to respond accordingly. So let's start to learn from some of ABS's approach. When we look at these changes in market demand, right, particularly from government initiatives like Bede, how has ABS adapted its operational strategies to try to stay ahead? Right? Where did you assess some potential gaps or challenges? What did that process look like, and how did you begin to formulate your strategies for resiliency? When we were at the the epicenter of what was going on, you know, back in twenty twenty two, you know, we realized that forecasting and planning and just overall understanding of all the data that that we were getting at the time that we really didn't understand all the numbers. You know, back in the day, it was you took sales history and you divided it by twelve and you you built three months worth of inventory. But, you know, what happens when that number is now three, four times what it used to be? So, you know, we started looking into other systems. Barry can kinda tell you about some of the VMI systems that they put in place, which is vendor managed inventory, where we were able to start kind of planning their usages. But we also started dabbling in AI. And, you know, you hear that buzzword artificial intelligence. And it is like this last year, everybody's like, AI, AI, AI. But what what really is it? You know, like, how is it going to impact our business? How can we utilize it? And, you know, where do you start? You know? And when you think AI, I mean, you instantly go in your head like, oh, there's some computer that's just automatically, like, you know, running autonomously, and it's just gonna, you know, be the magic eight ball, and it's gonna fix everything. But, you know, you'll see. I mean, it's a Swiss army knife. You know? When it first came out, people, like, what am I supposed to do with this? It's got it's got this, you know, thumbnail pick in it. It's got a cutter. You know, there's all these things, but you're like, how am I gonna utilize it in my everyday life? And that's where we are right now with AI. So AI is an amazing tool. I mean, it can literally take our data. It can, you know, run different modeling scenarios, and it can output, you know, like, hey, if I wanna run at twenty percent capacity, you know, what does it look like? Well, you know what? Change that up, and I wanna do x y z. What used to take an analyst, you know, maybe a week to, like, formulate and get all the data together and then run different models took forever. And now we can do it in a matter of seconds. But, you know, there are some major challenges that, you know, we can discuss too with with how AI, you know, reviews the information, receives the information. But I don't wanna steal all the thunder, so I'll I'll switch it over to Barry to kinda talk about some of the VMI programs that we put in space just to, you know, really manage our our inventory levels. And I think Bill had a good point. The problem is we went through, like, a really rough couple of years. So you you can't I what it did is it give it didn't give us a true history. Although a lot of months have these spike you can't you can't just say, okay. Last August, we did this or the last three months, we did this because it's it's rapidly changing. So the old methods of, you know, Excel spreadsheets and take an average over a couple of months of usage and then build into that is has changed. And with it, we've had to change, you know, what we do, how we calculate the data, and we need something more live as it changes. So we we have, we have about seventy five, VMI sites across the states that we basically handle on a daily basis. So we we got a program that basically uses a bit of AI in the background, but it it kind of watches that day to day change and predicts where it's going, you know, instead of just basing it on history. And I I think that's it's like Bill said, AI is really helping us get the data quicker. It's quickly seen, though, for one, when you work hard to get that data, there's an understanding of the numbers, and a little bit of that, I think, is gonna be lost. Not lost, but you're generations of people that moved up on their job because they're good at crunching numbers and coming up with it. But part of that understanding is having to go get the numbers. So now now you're gonna have to have a different, well, it's a different generation already. But, you know, what you're gonna do is have instant numbers. What do you do with them? So it it changes kind of the focus. And plus, can you trust it? You know? Bill's been working on, AI for a little while with this and everything, and it's like you have to be able to sound check that. You know? My my worry is we you know, we're gonna go into this. You're gonna get instant data and everything. You're gonna have twenty people that looking at the data. Nobody has any idea how to do it anymore. It's just like, well, I don't know where that came from. How do you sound check it? So it's I know a lot of people are just like, yeah, it's gonna change manufacturing. It's gonna change the world and everything. And I I definitely think it will, but it it's what it's doing is it's giving you the numbers and stuff that you've always had just quicker. You know? And what you do with that, I it's a it's a lot of the older generation's not comfortable with just reams of numbers, and, you know, I worry about that a little bit. There's a lot of factories that try and run just on stats and and numbers and everything, but it takes more than that. But, yeah, it's what we're dealing with now is really three or four years of, not consistent history and maybe four or five years in the future of not consistent future. And, you know, we're we're just trying to adapt our systems to give us a heads up quick. We can't wait for three or four months to say, oh, jeez. That was a spike and it's not true because that's how everybody ended up with the inventory. Yeah. I look forward to, like, what AI will become. You know, as of right now, though, it's, you know, quality data in, somewhat quality data out. You know, like Barry said, you have to know some history of what you're looking for to say, like, that sounds right or or that's not right. You know? And with AI, which which is like an amazing tool is that they have this, you know, large language model, you know, where I can now kind of somewhat type into a prompt and say, here's what I'm looking for. I would like to see this. And it can program it and figure out how it looks, but but, you know, it's it's a computer program. So it's, you know, really looking at black and white, and sometimes it it can spit out some random things. So, I I think the the role of an analyst is definitely gonna change for sure, with AI. But, you know, it's some exciting things that are coming up. And like y'all mentioned, right, any AI tool, especially integrated into key day to day operations, for something like logistics, right, and supply chain, the effectiveness of that AI tool is heavily dependent on the quality of the underlying data and then also the quality of the interpreted data and how that is then turned into something actionable for the end users, in this case, the decision makers day to day who have to make informed, forecasting decisions, you know, buyer relationship decisions, inventory management decisions based on that day, data. Right? Making sure that all of that is accurate and legible and functional and actionable. Right? So can you get a little more specific on some of the, maybe even potential challenges that ABS has faced in not only capturing, but then interpreting and presenting and making good use out of that data. And how are you addressing some of those? Right? What has been y'all's approach to making sure that an AI tool is not only capturing clean data, but outputting clean data that people can actually work with? So, I mean, at this point in time, how we're we're utilizing this is it's almost like a, you know, I'll run the numbers in a traditional fashion, and then I'll run the numbers through AI. And if I've got, you know, similar results, then I can trust the data that I'm looking at, and I can build my models to be more advanced within the AI. But you have to have that base level foundation of understanding for these apps to be able to, like, fully understand what you're after. Because I can say, you know, oh, I would like to know this. And then all of a sudden, it spits out, you know, a picture of my dog jumping through, you know, a fence or something. You know, it's it can get very off the rails very quick with AI. So, you know, some of the things that we've been looking at are, you know, of course, sales history. You know, you're looking at that, but that's one metric. You're looking at, you know, deliverable times. Like, how quickly did the customers need it? Or how quickly have they needed it? Where are they located throughout the country? You know, what warehouses should we be putting inventory in to make that transit time, you know, quicker? And then, you know, adding another complicated layer on when do projects start, when are they going to be, you know, building, and how long will those commence for? How you know, so you can keep adding layer after layer after layer. You know, I met with a client yesterday, and I said, you know, with AI, we definitely need forecasting and planning information. And I said, I'd I'd happily share what AI tells me about your company. You know, I can put it through our system, and I can spit you out what it thinks your forecast is gonna be. And he said, well, you know, we traditionally don't like to forecast. And I said, well, why is that? And he goes, well, we don't wanna feel committed to something. And I said, well, you know, as a manufacturer, you know, we understand that you don't wanna, you know, be committed to purchasing it, but you have to give a manufacturer some level of quantity volume. Because I may build ten, but you know you need a hundred. You just don't wanna tell me because you're not sure the project is gonna come around. So where we're building in variables is, you know, maybe we tell AI only build seventy percent of, you know, what the number shows us. And then let's trend that out for three months and model it. And then, you know, in three months, I'll run the program again, and it'll say, hey, you you went above and beyond what you said you were going to. You know, maybe we can move it to eighty percent. So it's really about quality data in with lots of data points that is very clean. You have to have clean data. You know, any ambiguity in the data really can just throw these numbers on a whack. And I, for one, you know, I'm always scared to death to provide AI numbers without backing it up because, you know, like Barry said, you're gonna have people down the road, you know, two generations from now that are going to be like the movie Idiocracy, if you've seen that. You know, like, the number's a hundred. Well, why is it a hundred? Because the number says it's a hundred. You know? So that's what I'm worried about with our our future generations. But, you know, I I think I think it's gonna help companies in the long run, though. I think from the people side, you know, we're having a bit of a battle of, you know, you have somebody okay. They they work every week and twenty hours a week, they dish out those reports. So now it's just like, hey. I wanna do those reports instantaneous for you, and I'm gonna I'm gonna kick it out. And there's a little bit of that like, where does that leave me? You know? So if fifty percent of my job is generating these numbers and telling them what about you know? Then if you take that away from me, where is my job gotta go? And and I think that's the problem is, I always say it's it's the culture and the reward system in a company. People work their way up to supervisors and managers because they're good at things. They're good at analyzing the data. They're doing that stuff. So now you have these people that's moved into those positions because they did it successfully. And now you wanna bring something in that's gonna do their job for them. And, you know, it's the same as what Bill said. The industry is like, you know, it's gonna be autonomous. You're just like, you're not gonna have to do anything. You know? Somebody in another room is gonna type it in, and all these analysts are just gonna be laid off. And it and I think until really people see what their value is or how do you handle that, I I think you're gonna have a switch in people. Some people are have got to the job because they're good at something that may be going away. You know? And then how do you promote people in that know how how to do that data? So there's gonna be that transition time where people kinda either have to adapt or change or figure out, you know, how where is my role in this? But I I know that's like, a lot of people are worried, it's like, you know, I know the data. I put it in. Now you're you're gonna do that automatically. So what do I do Tuesday and Wednesday every week? So it's, it it's a challenge for sure. See, I'm in a a tough spot, Daniel, because I still have twenty years left in my career, whereas Barry, he's on the tail end. So I have changed from my old school hammer and nails type of, mentality to to learning how to program the machine. So as if I can make the machine my buddy and I can learn how to talk to him, then then we're good. So it's gonna take a lot of adapting for sure. You know? But it's for the better. You know what? I don't like to sit here and crunch numbers all day. I I've got way better things I'd like to do. But you gotta learn how to to massage the data and talk to the data and and know what the right questions are to ask to get it out. You know? You gotta work on your machine social skills. And it's only fifty percent of the people will adapt to that. You know? You're you're on the side, Bill, where you're just like, how do I use this to make my job better? And like any change, there'll be another side that it's just like, I'm not adapt or so Yeah. The the funny thing about it is, so one of the neural networks that we're using, I won't say their name on the air, but, once that we're using, I won't say their name on the air, but, once in a while, it will get lazy. And it will start trying to cut corners on your data, And you have to, like, pretty much yell at it and say, no. Quit cutting corners and actually give me the full amount of data. So I was talking to the people at the neural network, and they were like, you know, we've actually heard that before. You know, like, it's funny that these neural networks, they they are almost entities. And they start trying to find shortcuts just like we do. And, so it'll be interesting. But sometimes I forget I'm even, you know, not talking to somebody on the other end. You know? It's weird. So to hone in a little bit more on the data capture itself. Right? Earlier, you mentioned that AI is really just there to make better use of the data that you were already capturing to help manage your logistics and your inventory. Right? It's just simplifying that process, making that a little more robust, and focused. And, therefore, you know, you just have sort of better insights into your existing assets and the data that you were capturing previously in a more manual fashion. But I'm curious if with this shift from traditional methods to more AI driven approaches for managing your supply chain, logistics, inventory, etcetera, Are there any new metrics or new data points that are now critical for your forecasting models that maybe weren't there before or that are maybe even a consequence of the way that the supply chain has, retooled itself and adapted to some of its previous disruptions. Anything new in the mix here in terms of data capture forecast modeling? I mean, I can tell you, like, right off the hand. I mean, we're seeing, you know, data that we hadn't seen before because we weren't looking for it. I mean, with all of these, the data was always there. You just you weren't looking for it. I mean, there's, you know, simple things like, shipping locations and time to ship. And, you know, when did, you know, the delivery guys make their deliveries? When did they pick up? You know, there's a lot of analytics there that you didn't really look for in the past. But what I'm really excited about at some point, you know, as this grows, hopefully, by next year, you'll start seeing more API driven, you know, AI where, you know, like, in programs like Power BI, you know, and some of the SAP programs out there, you know, they've got, you know, a bit of AI that helps you to program or to build content or to analyze it. But I'm really looking forward to releasing it into the system and having it go through and say, hey. I've noticed some irregularities here. You know, you've been shipping blah blah blah and, you know, we found that maybe you could do something easier. So we're not there yet, but I I'm looking forward to that information at some point in the future. I think we're on the cusp. I mean, we are literally at the very beginning of, you know, consumer type AI. You know, the government's had it forever, but, you know, we're just now seeing it. So I I'm pretty excited about what's next. We've seen the stamen manufacturing. So I was in a show in Germany couple of weeks ago, and there's quite a few people advertising like extrusion, that's automated. So we went over. It's not really automated, but what they've done is they're bringing in a whole new set of data points. Like, they're you know, you can always put a sensor on stuff, and usually, you know, we do, like, speed and size and stuff, and we analyze that. But part is you can end up with a monster amount of data. So they're going the opposite way, and they're just like, yeah. But AI can crunch this. So what we should do is put something here and take that every ten seconds or, you know, put a sensor on these twelve pieces of machinery that we never even monitored. So, you know, it was really interesting the way it's, developing pretty quickly. You know, one of them was, basically, you put a huge amount of sensors in, which would give you a monster amount of data that we've never had, but we couldn't have done anything with it anyways. And now it's taking that, say, a run of cable that ran over two or three shifts last time. It take and analyzes it. When you go to run that two or three weeks for now, it'll say, hey. You know, last time you did this, you took twenty minutes to set up. This wasn't done too quickly. You struggled with this. Halfway through the run, you know, you ran into some errors and stuff like that. Like, really really got a bunch of us thinking like, never even thought of that, you know, because it wasn't possible. You know? It's, like, it's only possible when you can crunch this data or have somebody looking at it beside an analyst. It would have been almost useless. But we came we came away with a different thought process of just like, yeah. You know, we should be you know, you don't need to buy a new exterior like that. We can just add sensors to what we have. And, you know, now that we have a quick way of analyzing the data you know, for many years, the problem is just you can you can get so many numbers, and they just become, you know, numb. You know? Like, I think all of us are guilty sometimes. You know? I get reports from the factories every day, and a lot of those, you know, I have to you know if I get to look at them once or twice a week, great. You know? But there's no way to look at all that data every day and make anything of it, especially when it's repetitive. So we were really missing out on the analyst of some of that. Like, there's probably something we could do with it, and this is kind of opening doors for that for sure. Dashboards have been, you know, pretty helpful for us because you can get key pieces of information right away versus, you know, like Barry said. I mean, I I don't wanna sit and analyze fifteen spreadsheets all day long every day. You know? So it's it's coming along. I feel like the industry is finally starting to see we've got a lot of planning and forecasting and and data to start analyzing to make this better. So any good supply chain naturally is gonna have partners. Duh. It's an ecosystem. Right? So I know ABS, really values its collaborators, its partners, you know, the other various chain links that help connect ABS to the telco industry. And it seems like in this new landscape, collaboration is obviously going to be key, because this data, while it's necessary for internal operations, oftentimes, it's data about external ecosystems that are impacting your own internal supply chains and, inventory management. Therefore, collaborating with those external ecosystems and the partners who have, you know, roots in those, you know, sort of areas in the periphery are gonna be key. And so I'm curious what ABS's approach to this collaboration has been in the past. How is ABS fostering collaboration? You know, how are you leaning on some of the relationships you've already built to just sort of expand the scope of the kind of information sharing that you now have to do to get that data visibility? And how is all of this improving accuracy and reliability in your forecasting? Yeah. Great question. I mean, it's, you know, a hundred years ago, I mean, they started to come out with EDI, you know, the electronic data interchange. And, you know, that really changed the landscaping of everything because companies could now, like, transmit their data from one point to another. And, I mean, that is, like, the fundamental level of, you know, let's just, you know, be able to exchange data. You send it to me, I send you a response. But now it's getting to the point where you've got a lot of programs that, you know, have shared access. You know, we're using some programs between, you know, our own internal companies. I mean, you know, as, you know, doing the podcast, I mean, Amphenol is comprised of, you know, a hundred plus companies underneath one umbrella. And, you know, to get those people to communicate with each other, you know, you can't just easily afford to set up an EDI link between all of those companies. So we're constantly looking for data that can be used or, not data, but programs that can be used to share and collaborate quicker. So, I mean, even something as simple as a program called Smartsheet, you know, it's if anybody's ever used Smartsheet, I mean, you can tell you it's it's it's an amazing program. It's Excel on steroids. Right? You know, it's, I can use Excel just like kind of like a Google Docs that I'm sharing, but I can attach files. I can set up alerts. I can send email reports. I can set up tasks and projects. And, you know, we're we're getting at that level. And, you know what, COVID was probably a good thing for, you know, a lot of us. Right? We became better parents. We became, you know, better spouses, but we also became better at working alone, working remote, you know, being able to not have somebody hold your hand twenty four seven. And, you know, I personally I mean, until COVID, we weren't even really using video conferencing that much. You know? And and now, I mean, I can sit here all day in the office and collaborate with my peers through all of these other software programs. So, I mean, it's, you know, like anything, I mean, we're evolving. And it's only, you know, getting closer and closer that we're we're virtually in the same room through the programs that we're working with. For the supply side, I think something that's happened through all this is, you know, we got burnt a little bit, same suppliers for years. Also, and everybody's over maxed. It really put us in a tough circumstance. And as we look at the money and stuff that's coming and everything's gonna expand, we've had to come to the realization that, you know, you you're gonna need a wider network. And, you know, the communication we have now is is is okay, but we've had to up our quality side, our supplier audits, you know, and we're trying to double the amount of suppliers in the last couple of years. With that comes a huge amount of data. You know? And, you know, how do you know what's good supplier? How do you make sure it's similar quality over a similar so it's it's really it's really changed the way we look at, like, the communication and and the the demands we put on our suppliers. So we, you know, we opt it now. We we demand everything like, we were traveling in Turkey a couple of weeks ago, but we did a couple of audits. You know, we'd like to see everything. Like, where's your records? You know, you don't have underage workers. How do you know this? Can we see the training records for the employees? In the past, we never looked at stuff like that. But now it's we have a good idea what makes you a good supplier. You know, and instead of just dealing with the comfort level of the same suppliers you had for years, you're having to open the doors to some other people. And through that, you know, we know the demands we need to put on them. But along with that, like, pulling that data together, keeping track of it around the world, you know, what what happens, who's a good supplier, and that is it's really been a challenge. But I think, you know, we we're changing our thought process. You know? And it's like I I constantly push our supply team and stuff. It's just like, I didn't know it. Like, we're their customers. I think sometimes we forget that. And the demand you know, we just don't ask for those demands, enough. And, you know, when we're even talking about supply chain challenges, you know, I think, you know, I I'm in agreement with your silver linings take on COVID. Right? And, you know, I'll throw in my two cents here that I think there were a lot of supply chain silver linings as well. Right? The last decade, but even more recently, let's say the last five years of supply chain disruptions, whether they're geopolitical, whether they are infrastructure related, whether they were, you know, COVID related. They led to the supply chain realizing where it had major gaps, areas where it was weak. And now through new tools, new partnerships, new strategies, is much more capable of, say, you know, with the Baltimore Bridge collapse and the closure of the Port Baltimore, realigning itself to maintain movement of goods and production and international strength as well. And so with that, you know, supply chain challenges, they they can compound into not only, you know, obviously, major crises, but the learning lessons can also compound. And so I'm curious if you had to reflect and look back, right, when we think of this importance of not repeating past mistakes in managing inventory, managing demand, and, executing on forecasting. Do you have any instances or examples or perspectives at all on on some of the historical approaches to forecasting in the past and, you know, some of the potential risk of repeating those mistakes even with new tools and new partnerships and a new outlook on the supply chain and a new outlook on life. Right? And how have y'all approached shifting your strategies to avoid repeating any of those past industry mistakes, with all these new tools and assets and perspectives in your tool belt? I'll start off with my piece of it on the kind of front of house, and then, Barry can kinda comment on his back of house. But, you know, on the front of house, I think we we really realized, from a customer level and from our level that, you know, pricing for items, you know, whenever you're looking for your items to build projects, it can't hundred percent always be based just on cost alone. I mean, we were so resilient on overseas products. And, you know, hey. We'll we'll take the ninety day lead time or a hundred and twenty day lead time, and, you know, we'll plan accordingly with our forecast. But then, you know, when the supply chain broke and all of a sudden customers are like, well, do you have anything domestic? Do you have anything domestic? And this was, you know, lots and lots of industries that, you know, we realized real quick we weren't really building a whole lot domestically. So having that kind of knee jerk reaction of what do we do now, it's been great because you're starting to see a lot more, you know, manufacturing jobs coming back to, you know, you know, North America, you know, be it Mexico, be it Canada, be it the US, you know, getting that material closer to home. But then on the customer side, it was also good because they started to realize, like, let's use, you know, better reliable vendors that may cost a little bit more, but can get us the product. You know? So it's yes. Yes. I can build it domestically, but it's gonna cost a dollar, whereas you're used to getting it for thirty cents. But with that dollar, you're always gonna have availability. It's gonna be available a lot sooner. We can ramp up and ramp down quickly without having to put things into a container ship. You know? Luckily, we didn't have much of our items going through Baltimore. But for a lot of industries, mainly like the chemical industries and I believe car manufacturing was going through there, You know, all of a sudden, they got to change. They got to instantly change. They got to start bringing it to other ports. They got to, you know their whole logistical supply chain of how to get it off that ship to their location changed for them. So, you know, bringing it domestic and, you know, having customers agree that paying a little bit more to have it closer to home, has been, you know, pretty awesome for us. You know? Kind of torn between that. You know? It's like I I think a a good portion of what we use every day. And I I think the difference of our lives being affordable or not is always gonna depend on overseas. I but I think we realized, you know, having specific like, I I think the majority coming into the US, most of it was coming from China and through the LA port. And, you know, something you quickly learned is, you know, now sixty, seventy ships out you can't do anything with. You know, we wouldn't put ourselves in that circumstance again. We we've gotta balance it. It can't be from one country. You're gonna have to have different ones. You're gonna have to use different ports. You're gonna have to always be aware that there could be a disruption and that can't shut you down. You know? Because it effectively, in a couple of ways, it shut everybody down for a period of time, and there's nothing you could do. You're just too all. You're all in on one on one way, you know, just because the cheapest, fastest, you know, that's like, we get caught in that. So it's exactly like Bill said. Some of it's more expensive, but the it's you can't go back to having three or four months inventory. It doesn't get you out of out of these troubles and everything. So, yeah, for us, we've changed the way we look at it. You know, we don't put all of our eggs in one basket. We don't we don't, put everything through knowing problems. You know, they're gonna come around. So I I think it's a it's a big shift, you know, in in some of the infrastructure and stuff that's gonna have to change. But I I I think people are reluctant to to put it all in eggs or give one customer all of the ability these suppliers and stuff. So, yeah, it's it's been a learning experience for sure. Alright, team. I think we're approaching the end of the podcast. So let's go ahead and wrap things up with a final look ahead. As we think about the future of the larger telco industries, you know, consumer demand pressures, technological advancements, If we, you know, reintersect your bead funding and some of the major projects, that are gonna come as a result of that, What key areas should industry players focus on in your view to ensure that they're not only, you know, staying on top of some of the potential challenges that might come from these major market movers, but also contributing and playing their role in a more efficient and responsive telco ecosystem, right, to where their internal improvements have positive impacts on the whole ecosystem and its operations. Yeah. I would say, you know, some of the key points to come away from all of this is that, you know, we know now you have to have that major customer engagement on projects and forecasting and planning. I mean, we've been saying it forever. But, you know, now with AI, you know, it's as a an organization, you need to find a neural network that you can trust, you rely on, and you can integrate into your systems. And then, you know, really, we have to look internally at all of our companies and say, let's identify some people that, a, wanna learn this, or b, have the knowledge to, to work these programs. Because not everybody is gonna be able to fully understand, you know, how to utilize this data or how to get the data in and get proper data out. You know, people that, you know, spent their whole career, you know, writing Excel functions may struggle with, you know, having a very, like, vanilla, you know, I can type in anything and try to get it out. And then, you know, above and beyond is, you know, making sure that your quality of the data going in and, you know, matches the quality of the data going out and then constantly checking it. So, you know, from a technical standpoint, you know, those key things are gonna help you to, you know, move to that next generation of planning and forecasting. And, you know, Barry can kinda comment on on his side how he thinks he'll change his world. But I think the relationships, I think everybody's gonna have to realize that it's constantly changing. And even though the last couple years are pretty hard, I don't think the next couple years are gonna be any easier. I I think you have to it can't be the status quo. What worked yesterday, you know, you can't go forward like that. You're gonna have to adapt. I I think for customers and everybody is gonna have to realize that sometimes exactly what Bill said, you're gonna have to pay a little more for a little more security, a little let less lead time, a little less risk. And I I think that's like, I we're getting there. You know? It's, people are realizing that there's a cost for some of these things. You know? The, cheapest, fastest, quickest, you know, I don't want anything but to buy the cheapest can get you in trouble. So I think everybody's been stung with it. So I think going forward, you can't say, okay. COVID changed the world and, you know, those were the tough years and we're past it. I I think we're in a every year is gonna change rapidly, you know, both with the data and the communication and everything. But I think it's gonna make the stronger relationships. You know, you need to be you need to be close, you know, with your customers. You need to be close with the supply chain. You guys are like, everybody's together. So, yeah, I believe that's one thing it exposed that people didn't realize is really how interdependent these systems are. And you can't you can't just say, like, the cheapest cheapest product wins all the time. You're gonna have to you're gonna have to add some diversity if you want, you know, to take the risk out of it. So I think just just being adapting and making sure those relationships are solid is gonna be more important in the future than the past. And I think with those actionable strategies, we'll go ahead and wrap things up. Thank you to the two of you for your analysis today on Wavelengths. It was a real pleasure getting to hear your high level insights and your in the weeds experience and strategies for aligning telco operations with some of the external pressures that are, you know, shaping the supply chain, shaping inventory management, logistics, collaboration, demand forecasting, etcetera. So I think our audience can learn a lot from what ABS has been putting into practice, and I'm grateful that the two of you joined us on the podcast here to shed some light on those strategies. So thank you again to our two guests on the episode today. We were joined again by mister Bill O'Donnell, senior director of technical operations and customer service support at ABS. We were also joined by mister Barry Holt, VP of global cable operations at ABS. Bill, Barry, thank you to the two of you, and I'm looking forward to future conversations. This was really great. Thanks again, Daniel. Thank you, Dan. And thank you everyone for tuning in to another episode of Wavelengths. If you like what you heard and saw today and you wanna tap into previous episodes or you wanna make sure you're all caught up on the entire ecosystem of Wavelength content, make sure you're heading to our website, amphenol broadband dot com. Again, amphenol broadband dot com, and make sure that you're subscribing to Wavelengths on Apple Podcasts and Spotify or wherever you listen to your podcast content. I'm your host, Daniel Litwin, the voice of b two b. We'll catch you on the next episode of Wavelengths.