Fashion Manufacturing Trends – Digital CxO Podcast EP120

Hello, and welcome to the digital CXO podcast. I'm Amanda Razani, and with me today I have Lenny Murano. He is President of the Americas at Electra.

How are you doing today? Good, Amanda. Thanks for having me on.

Happy to have you on the show. Can you share a little bit about Lectra? What services do you provide?

Sure. So lectra is a integrated solutions technology company that provides a suite of equipment, software services, and industrial intelligence to the fashion appar, uh, fashion, automotive, furniture, and then other industrial value streams, uh, including aerospace, defense, marine recreation. Wonderful.

So we're here today to discuss, uh, fashion manufacturing trends. There are five specifically that you were gonna share. So, uh, can you share what are, what are these trends?

How and how are they impacting the industry? Sure. Um, you know, the, the main five, you know, to start with, I would say the first one is the need for better reading of brand performance.

Um, you know, right now in a, a very highly competitive environment, uh, with product, you know, with product being sourced all over the world, costs and pricing, being adjusted, having, you know, a good sense of how your brand is performing in the marketplace compared to the, the competition is gonna be key. And that, you know, that allows you to make sure that you have the right product on the right, uh, in the right place at the right price, at the right time. And, you know, there's AI driven web-based tools that facilitate this, like a, you know, there's a product called rep views that, that we have, there's a lot of competitive benchmarking.

Uh, so you can see, you know, compare assortments versus competitors and things like that and get a good gauge of how your, your brand is, uh, positioned in the marketplace. So that's, that's really the, the first one. You know, the, the second one is, you know, price increases versus perceived value, right?

And, you know, this is a trend that we talked about in the beginning of the year, not knowing what the macroeconomic context was gonna gonna be like. But, um, you know, as consumer demand goes up and down, as they look at the value of different segments of the fashion market differently, whether it's luxury or sportswear, uh, and as prices fluctuate, how do they perceive the value of your brand compared to others in the market? And are they gonna be willing to pay for whatever your, your primary value proposition is?

Um, the third, and you know, this is one that we see in all different parts of the world, is increases in regulatory trends. And, you know, in the US it may, you know, fluctuate up and down how, how rigid they are, and whether we face, you know, increased regulation or, or, or deregulation. The reality is, is that most fashion companies have some global aspect that require traceability and visibility throughout their value streams around the world.

So having tools like, um, you know, we have a platform called Textile Genesis that provides visibility from literally the, the cotton field all the way through production and to the consumer. Uh, having the visibility throughout that whole supply chain is gonna be key. So you could make sure that, you know, when you're importing products that you can validate that it comes from a, you know, a sustainable and responsibly sourced, um, you know, mill or farm or, or, uh, uh, cut.

And so factory, the fourth one that everybody's talking about, uh, this is one that I'm particularly passionate about, passionate about because it's something that lecture's been on the leading edge of for a long time, is having AI drive innovation. And, you know, there's so many uses for artificial intelligence throughout every area that lecture participates in, whether it's, you know, planning the product lifecycle through, uh, you know, pattern design for the garment that's gonna be produced, whether it's, um, making the, the production and material usage more sustainable throughout the process. On the marketing side, whether it's predicting brand performance, as I mentioned earlier, whether it's benchmarking, competitive trends, there's a lot of things that, that we could use to, uh, that we could leverage AI for.

And that we have been really, uh, you know, leaning into AI since 2007, since the internet of things kind of came to be. And we connected the, the cyber physical worlds, you know, when our equipment first became connected to the internet. So that's one that we see really being a, a game changer for us and for the fashion marketplace.

And then the other one, and this is more relevant than than ever, uh, particularly with the, the current trade environment is the emergence of new geographies. And that's, uh, you know, primarily on the production side. You know, when you look at the business, you know, the, the fashion manufacturing business really starting in about 2017, 2018, we saw this shift away from China.

A lot of it went to other parts of Asia, whether it was Vietnam or Cambodia. Um, the Nearshoring trend for those in the Americas was very real. I wouldn't say it was reshoring, but it was definitely, uh, a nearshoring where we saw, you know, business grow in, you know, Dominican Republic and other islands of the Caribbean, um, uh, central America, Mexico.

Uh, so, you know, where's the, where, you know, what other g geographies are gonna grow in this, you know, as a result of this trade war and whatever trade agreements, you know, get negotiated, you know, there there's gonna be winners and losers. Right? And, you know, at Electra, what our responsibility is, is to make sure that both the brands and the manufacturers have the infrastructure and the tools to give them the agility and the flexibility to navigate this.

Yeah. From, uh, let's talk about that because we are in the middle of, you know, all these new tariffs and how are these gonna play out? So as, um, companies are moving these manufacturing facilities, what advice do you have for them?

I mean, that's a big undertaking to move, to move, um, your manufacturing location. It's A, it's a, it's a big undertaking, but the key is to have the data infrastructure that allows you to do it in a nimble way. So, um, you know, I had mentioned before that there's a lot of areas of the value stream that, that we participate in.

When you look at manufacturing, um, you know, there's, there's certain elements, right? You have the inception of an order, right? So you have an order.

It could be coming from a brand, it could be coming directly from a, a retail outlet, if it's a, you know, if it's a customized order, you have that order being translated into, you know, uh, a production ready set of data, and that's, you know, the, um, the patterns that are gonna be actually produced and then, then sewn together. That's taking those patterns and putting them on a marker. Uh, what a marker is, is a series of patterns that are put together on the material in a way that maximizes your material usage.

Uh, then it goes into planning your production. Okay, what set of, you know, production ready files I wanna send to which location and when, uh, and then it's monitoring that, you know, that production, and if you have that data thread set up, wherever that production is, becomes a means to an end, right? So you could have somebody in New York City taking a look and saying, all right, I have some contractors in Vietnam, Mexico, and you know, Dominican Republic.

Where do I, where do I need to send these data based off of the, the ability of that contractor and the lead time? Or if I'm a vertically integrated manufacturer, I can have factories all over the world and say, you know what, you know, Vietnam is gonna have a 34% tariff. I know that we're still, you know, in the middle of, uh, the U-S-M-C-A exception with Mexico, I'm gonna shift that production to Mexico because you have that cloud-based data structure set up, and we have an enterprise solution called Val that enables that you can make that, you know, you can maneuver those orders.

Now, obviously you have to have the material and the, the labor to support it, but at least from a, a data infrastructure standpoint, you have the agility and flexibility to be able to shift. And then you mentioned ai, and of course, every company is looking at how they can harness AI and integrate ai. What, from your experience, what roadblocks do business leaders come up against when it comes to integrating AI tools?

I think, you know, the, the biggest roadblock that leaders that we engage with is not knowing what's out there and not knowing where to start, right? I think that, you know, as you know, new generations of leadership that kind of grew up, you know, hearing about AI come into leadership roles in the, in the companies that we deal with, there's much more of an openness, but they don't know what's out there. And the reality is, is that a lot of the customers that we deal with don't realize that they've been leveraging the know AI capabilities, which is what they've had for a long time.

So, for instance, you heard me mention early on that, you know, we've been leaning into AI since we connected the first pieces of equipment on the cut room floor to the, you know, to the internet. You know, since 2007, we've been accumulating all of that data using machine learning. We're able to predict when we think our equipment that's on the factory floor is gonna fail.

So what will very often happen is, you know, we'll have a, you know, a, a machine learning algorithm that says, okay, if this motor is running hot for three days, we know that if it runs hot like that for five days, it's gonna fail. We'll proactively ship a motor out and a customer will say, Hey, I just got this motor and what's it for? Oh, well, we think it's gonna fail based off of our machine learning algorithms.

So we've been doing that for the, you know, the last 18 years. So, you know, that's machine learning ai, you know, with generative ai, you know, we use it in our cloud-based path platforms on creating markers, on our production planning algorithms. Those are all AI based.

So there's a lot of things out there now that allows our customers to really ease into it in a way that is natural to their own workflow and processes. Thanks for sharing. Those are some great use cases.

What do you envision as AI is advancing very rapidly? What do you envision for the future of manufacturing with ai? I think it's gonna be, um, it's gonna enable further automation down the value stream, right?

So when you look at, you know, a typical factory that's cutting patterns and sewing garments together, you know, they're automated up to a point. And, you know, that point is typically at the end of our line, our line of cutters, at that point, it gets manually taken off the machine manually kitted, and then brought off to sewing, right? So, you know, could you leverage AI to, you know, combined with, you know, future automation technologies to bridge the gap between the end of the cutting line that's already automated and leverages AI to the finished garment for the consumer.

I think that's where, that's where the, the puck is headed. All right. So with that being said, and I know we've been through, um, industrial Revolution before, but I know a lot of people are concerned about job losses.

Um, what advice do you have there? You know, there's, there's two ways that, that I look at it. One is, you know, artificial intelligence is creating a new type of job, right?

And this is something that we've seen as we've gone through our own digital revolution as a organization internally, but also we see it with our customers. Where, you know, the, the labor pool that's being brought into it is less, you know, mechanical or less viewed as, you know, hard labor than they are technology positions. So there's a shift there.

The other piece of it is, is that, you know, when you look at the workforce, workforce in the markets that we serve in fashion, in automotive, in furniture, there's a workforce shortage. So our customers cannot replace the folks that, that are retiring. And it's just the, the, again, the, the, the nature of the work.

So, you know, one is creating a new type of job, and two, it's gonna help offset the shortfall of workforce that we have as the, the workplace moves on in the markets that we serve. Mm-hmm. Absolutely.

Well, if there was one key takeaway you could leave our audience with today, what would that be? Get started, right? Understand what's out there, because there's a lot of tools out there now that are light to, you know, light to implement that you could be taking advantage of now that are, are technology enabled to connect the dots throughout your process in manufacturing.

So get started now. The tools are out there, um, take a look and, and see what's available that that fits your, you know, your, your company and your process. Alright.

Thank you so much for coming on the show and sharing your insights. Thanks a lot, Amanda. All right.

And thanks to our audience, stay tuned. There's more.