Sponsored by Coats Digital

Title: Fashion intelligence to synchronise brand strategy and supplier execution - Coats Digital, Winter Quilts & WTiN Fireside Chat
Date: Friday 25 September 2026
Duration: 47 minutes

 

 

Summary

In an industry defined by complex siloes, the traditional divide between brand strategy and factory-floor execution has long been a source of friction and waste. When brands and manufacturers rely on disparate systems and siloed data, agility is lost and the opportunity for true collaboration and real gains, remains untapped. This Fireside Chat brings together Anika Amalean, Director at Winterquilts, Shanika Kande Lekamge, Group Industrial Engineering Manager at Winterquilts, and Jamie Symon, Global Brands Director at Coats Digital, to explore how a connected digital ecosystem can transform this relationship. The Fireside Chat will move beyond the technical implementation of GSD Cost to examine how a shared language of data creates a single source of truth, allowing brands and suppliers to function as a unified team.

Speakers:
Anika Amalean
Director at Winterquilts (Pvt) Ltd
Anika Amalean is a Director at Winterquilts (Pvt) Ltd, a Sri Lankan apparel manufacturer with over 35 years of history supplying some of the world's most renowned fashion retailers. In this role, she leads change management and transformation across a team of 3,000 employees, guiding the business through its next chapter as part of a third generation leadership transition.

Shanika Kande Lekamge
Industrial Engineering Manager·Winterquilts
Shanika Kande Lekamge is a skilled industrial systems engineer with strong experience in manufacturing, product development and technical operations. At Winterquilts, a leading Sri Lankan apparel manufacturer with over 35 years of history supplying some of the world's most renowned fashion retailers, she applies this expertise across a network of four factories, supporting the technical and operational standards that underpin the company's manufacturing capabilities.

Before joining Winterquilts, she held leadership roles at MAS Holdings, driving innovations in design for manufacturability and lean processes. Armed with a BSc in Industrial Engineering and a Master's in Manufacturing Systems, Shanika brings expertise in automation, quality control and sustainability. She is currently pursuing a Doctorate in Business Administration at the University of Kelaniya. A certified ISO auditor and GSD practitioner, she combines strategic thinking with hands on technical proficiency to deliver impactful manufacturing solutions.

Jamie Symon
Global Brands Director at Coats Digital
Jamie Symon is a seasoned professional at Coats Digital, with over 15 years of experience in industrial design, digital transformation and manufacturing technologies. Working closely with fashion brands and manufacturers worldwide, he helps organisations accelerate innovation through the adoption of digital and AI-enabled solutions that improve product development, optimise production, and strengthen collaboration across the supply chain.

Combining deep industry expertise with a practical, results-driven approach, Jamie is passionate about helping businesses harness connected data to drive smarter decision-making, greater operational efficiency and more agile ways of working. In this webinar, he will share insights into how connected digital ecosystems can bridge the gap between brand strategy and supplier execution, creating a single source of truth that enables stronger collaboration, faster decisions and more resilient, future-ready supply chains.

Madelaine Thomas
Managing Director at WTiN
As Managing Director of WTiN, Madelaine leads the delivery and strategic operations of critical data-driven intelligence and market insights that empower the global textile & apparel value chain. She is dedicated to driving digital transformation and sustainable innovation across the industry through high-quality intelligence, consultancy and strategic partnership. Working at WTiN for over 10 years, and previously as Head of Content, Madelaine has a wealth of knowledge across the supply chain. She holds an MA in International Relations from the University of Leeds, UK and a First Class Honours degree in International Journalism from Liverpool John Moores, also in the UK.

Transcript
This transcription has been AI generated and therefore may have some inaccuracies.

Fashion intelligence to synchronise brand strategy and supplier execution
This Fireside Chat will move beyond the technical implementation of GSD Cost to examine how a shared language of data creates a single source of truth, allowing brands and suppliers to function as a unified team.

This is a WTIN Fireside Chat hosted in partnership with Courts Digital.

I'm Madeleine Thomas, Managing Director at the World Textile Information Network and I'll be hosting this webinar today.

The textile and apparel industry, as you'll know, is one defined by silos. The divide between brand strategy and factory floor execution has been a source of friction and waste much longer than any of us have worked in it. When brands and manufacturers rely on separate systems and data that doesn't travel, agility is the first casualty and the real gains that come from proper collaboration are never realised. So today we're asking what changes when that data is connected.

With three brilliant panelists, we are taking on a number of viewpoints, including that of the technology partner working across brands and their supply base and the manufacturer who lives in that supply chain and its complexities every day. So I'm really looking forward to this one today.

Before we dive into it, just a brief bit of housekeeping. As this is a webinar, you can't be seen or heard, but we do invite you to submit your questions in the Q&A function on the bottom of your Zoom window. Myself and the team would love to hear your questions, and I will be moderating and posing your questions to our wonderful panellists at the end of this panel session. So do type your questions in whenever it occurs to you, and we'll endeavour to get you an answer at the end of the session. We are recording. If you have to drop off or you'd like to share this with a colleague, the recording will be emailed to everyone who registered. So without further ado, let me introduce our speakers.

So joining us firstly today, we have Shanika Kande-Lakagme. She's the Group Industrial Engineering Manager at Winter Quilts. A Sri Lankan apparel manufacturer with more than 35 years of history, supplying some of the world's best-known fashion retailers. Shanika works across a network of four factories and brings a serious technical background to this. Industrial engineering, a master's in manufacturing systems and leadership roles at Mass Holdings, driving design for manufacturability and lean processes. She's also a certified ISO auditor and a GSD practitioner.

Joining us on the Winter Quilts side, we have Annika Amelien, who is the Director at Winter Quilts. She's originally from a finance background and she leads the change management and transformation across a team of 3,000 employees, guiding the business through its next chapter as part of a third generation leadership transition.

And then last but not least, we have Jamie Simon, who is Global Brands Director at Coats Digital. With over 15 years in industrial design, digital transformation and manufacturing technologies. He works with fashion brands and manufacturers worldwide on adopting digital and AI-enabled solutions that improve product development, optimise production and strengthen collaboration across the supply chain.

So Shanika, Annika and Jamie, thank you all for being here with us today. I will now invite each panelist to begin with a quick introduction about themselves and their respective roles. So, Shanika, we will start with you. Thank you for joining us.

Hi, everyone. It's a great pleasure to join the webinar today. So we've been working with GSD and winter quills has gained a lot of benefits and advantage in onboarding the GSD and we are so excited to share like how it has been impactful in manufacturing and also like bringing the productivity of the business. Thank you Shanika and Annika welcome to you now.

Thank you, Madeline.

Hi, good morning, good afternoon, good evening, everyone. And thank you for having us at this webinar. I too, along with Shanika, am excited to share about our journey on GSD and where Winter Quills is right now. I've recently joined the family business as a part of the third generation and we have been going through a lot of transformation and this transformation has come initially with process, with operations, with people and now we are finding that evolving and transforming digitally is also a very, very critical part. So hence that is how after many, many decades of being in the business that we have finally been able to onboard GSD. And yes, it's a pleasure to be here and share our insights. Thank you.

Thank you, Annika. It's great to have you with us. And Jamie. Yeah, thank you very much, Madeleine. I think it's great to have these conversations and really understand more and more of what our customers need. So part of my role, as Madeleine mentioned, is really to work with those big global brands that are using our software and their suppliers. So how can we help that communication? How are we building tools? to assist their current processes and maybe speed up some of those. So, you know, it's great to have these conversations and, you know, I appreciate you inviting me on. Thank you.

Thank you, Jamie. So we will now get into the session, which is what you've all been waiting for. So, Shanika, we'll start with you. Take us back to before you guys adopted GSD Cost and Quest. What was the hardest bit about costing and planning your production then? And what has seen the most change since? And what are you able to do now that you couldn't do before?

Yeah, so to begin with, before adoption, like before using GSD cost, Uh, it was more like subject to costing method engineering, even the same with standard minute value also estimated and relied heavily on historical estimates and also. Uh, experience personal experience. And, uh, this created a lot of, uh, variance across estimators and also led to either like uncompetitive codes and then margin erosion. And also like when it comes to like pre-production planning kind of like siloed as early stage, the product costing as in like before having Quest, GSD Quest in place, it was quite disconnected from the shop floor realities and like making it difficult to give rapid, accurate, or like feedback during product development. And what has changed the most is it's a single source of truth, I would say, like establishing globally recognized standardized time standards, which eliminates the debate between costing, pre-production, and planning, and also the flow execution. And speed to court as in like generating accurate costings at the development stage happens in minute rather than it used to be in like days. So what we can do now and that we couldn't do before is that this is more data back negotiations and we justify cost breakdowns transparently to brands using it is more like scientifically validated SMB rather than an arbitrary negotiation and also predictive line balancing which is like line layouts and capacity allocation like all this can be modeled accurately before loading styles and cuts into the flow and like it also minimizes the line balancing and all the bottlenecks which was very difficult for us to tackle earlier.

Interesting. Thank you, Shanika. And, you know, from your experience here on the change management side, would you like to add anything?

Yes, what I would like to add there in terms of the people, and that is what supported us on this journey as well, because as Shanika mentioned, initially it was all based on experience or it was person driven and how an individual would perceive a particular costing or an SMB. And now having brought in the right expertise, having brought in the right leadership to drive this project, I think that's one thing that is very critical. You've got to have the right team to be able to then execute.

And how difficult, Anika, is it to find that right leadership when going through a transformation like this?

Interesting question. So in fact, Shanika has, you know, when she joined Winter Quilts, we went through multiple work study, you know, industrial engineering managers and roles. But I think now where we are is, you know, like I said, it after I think four years or four to five years that we've been able to, you know, finally drive this project and drive work study as a very critical, you know, foundation for the product. Thank you. And we'll go to Jamie now, because I wanted to pick up on some of those points, Jamie, from the ladies at Winter Quilts. You know, the technology only creates value when it's intuitive for its users. What is Coats Digital doing specifically to make that process more intuitive?

Yeah, it's a good question because we talk about change management often and how we actually introduce new systems and introduce new processes. But the reality is that change needs to be, you know, the less invasive, the better, really. You know, if a tool makes an engineer's day harder, then it doesn't get used. It doesn't matter how good it is. And for us, intuitive means the software fits with how that industrial engineer already thinks. So things like Quest, our AI tool that runs within GSD cost, it runs in a browser. There's nothing to install. Everyone is always on the same version. Engineers work from a standard, which means they're adapting sort of proven methods and not starting every single style from a blank page. We're also using AI to take out some of the more tedious parts of roles. So things like Spec AI, which is a tool that we have developed to read tech packs and populate the data into systems. Means that an engineer is spending their time on judgment within that process, not on data entry and takes away some of that. So, you know, I think for me, the real test of intuitive is when people stop talking about how the software is used and start talking more about the garment and the role that they're actually pursuing. And something that I've been hearing a lot from manufacturers recently is that You know, the brands and legislation, everybody wants them to harness the data within the factory. But some of them feel that it's quite overwhelming. There's too much data and don't know what to do with it. Is that a problem or could that be where kind of the opportunity is for this type of technology?

Yeah, I mean, along with all the AI tools that we are developing to actually make sense of a lot of that data, I'd say the problem isn't usually that there is too much data, it's that the data isn't consistent. And so potentially three engineers in three factories could measure the same operation in three different ways. You can have lots and lots of data and still not be able to compare anything. And really that's where we are spending our efforts with programs like GSD. This is where this matters. A minute is a minute and is the same thing in any line in any factory. And so suddenly you can compare lines and factories and styles by minute rather than opinion. And I guess the opportunity comes that when the data drives those decisions, you can actually make decisions on that. So when your SMVs are accurate and potentially they feed straight into a planning tool like Fast React Plan or something like that, your capacity plan is realistic because you're working on realistic targets and realistic minutes. So you quote delivery dates that you know you can hit and I guess see which which lines are suiting those specific style. I guess my advice is to any manufacturer who feels overwhelmed by that much data is don't start with all the data. Start with a question. Where are we losing margin? What line is underperforming? And then use the data to answer it. So it's not make sense of all that data. It's pinpoint a specific area, fix that, and use the data to fix it. That's a good point. Thank you, Jamie. And Shanika, we'll come back to you now. Brands today are looking for greater transparency. We've got things like DPPs coming in now. They're looking for speed and greater reliability from their manufacturing partners. How have you been able to demonstrate those capabilities and build stronger confidence with your brand customers? And what difference has it made to those relationships? Are there any kind of examples that you can provide?

Yeah. So in terms of transparency, so having this, I mean, sharing standardized time breakdowns, like it gives brand partners like a complete visibility into like labor costs. And also the GSD has fair wage tool. Like if you, brands are actually using that. So this fair wages and also realistic lead times. And in terms of the commitments, so we can give more reliable commitments because it's calculated through the software because based on the standard method engineering and it removes the guesswork and also allowing us to hit targets like delivery dates with like high precision than before.

Shubha Tole: Alongside and also like it has a major impact on the relationship that we have with the customers because it's like shifting the dynamic from.

Shubha Tole: A traditional vendor by a transaction to a collaborative a strategic partnership and also it reduces the friction during commercial discussions because. Both sides speak the same language. It's a globally accepted standard we are all referring to and it's easy to take our communications better. For an example, I would say some of the brands, they have open costing policy. So we do share the OBDR operation breakdown and like the standard minute value with them. And the... Scenarios would be like, sometimes they want to assess our productivity, like how well have we done a certain program? Certain brands, they actually do that. And through GSD, we can actually provide them the exact precise data. And through that, they are assessing whether how good are we, how capable and competent are we with compared to other vendors in taking forward that particular program. And based on the performance, they would place the orders for us for the next season and likewise. So that could be an example with how the customer, I mean, the customer experience with GSD. I would also like to say not just the customer, but also the supplier. Say, for example, if you want to... Through an ROI for the board on like automations and to effective utilization of automations also GSD comes in handy because we can analyze the motions and define the SMV and define what do we do in the process time or the IRT like what's the operation combination that could give us the optimized benefit out of that automated machine also. So likewise, this has given us multiple benefits in terms of working with the customer as well as with the suppliers. Interesting. Thank you, Shanaka. And Anika, do you have anything to further that point or any other points?

Yeah, I think to add to that, as the landscape is becoming very, very, very competitive. So with the help of bringing in a more accurate planning and costing purposes, This also helps us streamline at the factories and become more efficient and hence be able to mitigate some of the costs that we're experiencing from the other aspects. So, yeah, I just wanted to add that in terms of the cost. And Jamie, how does the, you know, going back to that consistency point before, how does the same readable and reliable data carry from brands to manufacturers. For example, if we look at colour development and what becomes achievable that wasn't beforehand.

Yeah, color is a great example. You know, obviously being owned by Coats and the largest thread manufacturer in the world, this is something that we come up against in the thread side. So, you know, color is, again, color is a great example. When a brand and a supplier work together on a digital color standard, you get fewer rounds of lab dips and faster approvals because everyone's looking at the same reference. And really I kind of view labor in the same way. So labor content works in the same way. When a brand and the factory are both looking at the same GSD method, the conversation changes. It stops being a negotiation over a number or your SMB is too high, taking too long to do that. And it becomes a conversation about the actual method of manufacturing the garment. How is this garment being made? Could it be made any better? And that really opens up a lot. So costings get agreed faster. The price discussion is fairer because it rests on facts. And the one I get most excited about is that kind of design for manufacturing can happen earlier. We're not just negotiating on factory margin because we're actually looking at minutes and these are trusted. The factory can book capacity earlier with more confidence based on minute value.

Thanks, Jamie. Shanka, you've got your hand up there. Did you want to say something as well?

Yes, one more point that I missed, which I want to share is, this also is very helpful in cross-costing as in say we are working with, when the brand is working with multiple vendors, so they compare the costing, like which one has given a better costing or likewise. So when when we have used the GSD database and given the costing, it's very easy to negotiate and also to like communicate because it's a standardized and globally accepted minute value once again. And we can bridge the benchmark or like the expectation in such a way. And then it's an agreement with like all the vendors, like it's GSD, SMV, and it's a, It's more transparent rather than giving based on the videos in the production or like, like I previously mentioned, like, uh, internal databases and so on.

Thank you, Shanika. And Jamie, I just wanted to come back to you on a security point. Now, you know, when you're connecting manufacturers with brands, there is that security element to it. And, you know, a brand running an RFP across 10 suppliers, doesn't want them seeing each other's information, for example. How do you build systems that are open enough to be useful and secure enough to be trusted?

Yeah, this is an interesting one. And this comes up in practically every brand conversation I have. And I understand it. With the advent of more and more AI tools and data running around and pulling in from different systems, there are rightly so questions over this. So firstly, Codes Digital takes its security very, very seriously. And we are constantly looking at how that data is shared. The principle that we work with is that each party owns its own data. So if, as you mentioned, a brand runs an RFP process across 10 suppliers, the brand runs will see each supplier's submission separately and the suppliers never see each other. So there's no kind of crossing over information there. And I think just as important, you know, the supplier decides on how much to share. Depending on how the brand is working, that might be a kind of headline cost as an FOB price, a cost breakdown of what that's made of, or even a complete full operation by operation method, you know, depending on the relationship and that level of trust they have with the brand. Where we use that data for benchmarking, it's kind of aggregated and we anonymize that. So everyone gets the value of the comparing the tool without actually seeing other people's data. I guess the way I would sum it up is that it's kind of closed by default and only open by permission of the supplier that's providing that data. And I think that's, you know, trust is what makes the whole thing work, really. If suppliers don't trust the system, they won't put in that data. And then it's not really any use to the brand either. So it's something we take very seriously.

Thank you, Jamie. Annika, I want to come to you now and think about the factory of the future. And what do you think, I guess, really matters when we think about what the factory of the future is or could look like is that You know, the technology that's the most important thing or, you know, efficiencies, the agility, you know, adapting or could it be something else?

Interesting question, Madeline, because Factory of the Future, when I envision it, you know, in my mind is that there's a lot that comes up. But I think in the apparel manufacturing or any manufacturing, it's about at the end of the day, you're delivering the right product at the right quality with quality. Competitive prices and most importantly, the deliveries on time to the customer. Now, when we look at time and when we look at speed, everything has increased twofold. So even with technology, so technology does help us deliver at the speed in terms of the data that is available, accurate data, and also to help make decisions faster. So technology certainly helps to bring in the visibility. But at the end of the day, as I mentioned before, it's about the adaptability, Madeline, and as you mentioned as well, ensuring that we have the right people in the right positions to be able to execute. And we are seeing it, we're seeing it a lot where in terms of the skill or in terms of the experience, especially when it comes to these really critical, critical roles, they are far and few. So it's important that as leadership and a learning that we have taken is as much as we have the right people, it's about ensuring that we are able to provide them with a platform and the workspaces, you know, and the right training so that then they are able to, you know, able to then execute. So I think the adaptability, it comes down to the people, most importantly. Even on the shop floor, how much are we using technology even at the shop floor? So it's an integration from the head office all the way right down to manufacturing. And I strongly believe that I still keep coming back to having the right people in the right places. So, yeah, and I think at Winter Quilts, as leadership, what we do is that we ensure that we provide the right platforms for this to be able to execute. Do you feel that, you know, what we call the factory of the future. Has that changed at all, do you feel? Because for me, I mean, I've been in this industry, you know, not as long as you guys, but for nearly 11 years now. And I feel like at the beginning, the factory of the future was all about IoT. And then it was industrial, you know, industrial internet things. And now it's AI. But then we're now starting to hear about quantum computing, for example. So it's kind of, I feel like it's shifting all the time, what the guardrails of the factory of the future is.

Yes, absolutely, man. I totally agree with you there because it's as the mileposts change, you know, previously, if we take the industry 40, 50 years ago, it was very different. You could have 50, 60 sewing operator lines and, you know, still be able to manufacture and still be able to deliver and still be able to be competitive. But having said that now, that's not possible. So it is how easily are you as a manufacturer, are you able to adapt to take on digital, but to take on the right amount of digital into your organization to ensure that it's seamless and that whatever digital that we take on, because that does come with a cost. So, you know, as we move into this factory of the future, it does become more and more in terms of the capex when we're looking at investments, digital investments. So it's ensuring also that are we getting returns from that? But yeah, it is changing and So to answer you, Madeleine, from the quantum computers to AI, it's how much of that do we want to take on to be able to, because the baseline is you've got to get the right product, right cost and quality. At the end of the day, it's the quality that matters the most.

Absolutely. Thank you, Annika. We'll go to Shanika now. If she has anything to add from her experience there.

Well, for me, technology itself is nearly an enabler. And also, it's more than having like... Because apparel industry is very human-centric and human-driven, mostly on the dexterity. More than automating an entire sewing line, it's more that you look at how you can have this... Operational digitization, having the agility in like quick line balancing, like data capturing real time. I feel that is what the factory of future should be more emphasizing on rather than trying to have like robotic arms to like just replicate the sewing modules.

Interesting. Thank you, Shanakan. Jamie, I come to you because you were nodding along there And, but you know, course digital is 10 years old, but the products behind it, you know, go back to correct me about 30 years or more. Where does that leave you now? And what are you building next? You know, if we're thinking about that, the factory of the future.

Yeah, it's a good position to be in. GSD as a standard has been built and kind of proven over decades, you know, in real factory floors. And that, the depth of data that we have within there and the trust that we have isn't something that you can just create quickly. So, you know, we have tools that are being used every day providing real benefits and and you know going back to the previous question as well um proving you know a real roi based on you know the money that the suppliers are spending to purchase our software um we are looking forward, starting to look at how do we bring these together? So the things like GSD driving planning in Fast React and how do we connect all that data? So really what we're focusing on is connecting those pieces. The method in GSD drives the cost, the cost drives the plan, and then Fast React can plan what actually happens on that factory floor. So there's one source of truth from product development all the way through to production. And that's really what we're aiming at. The next step is bringing brands and suppliers into that standard so that they can compare cost on a like for like and have a much better informed conversation with AI taking out a lot of the kind of typing and keying of information and the admin that really slows everything down. And that's really where we're seeing the benefits. So when I think about the factory of the future, I don't necessarily, Maybe there will eventually be robots everywhere. That's not what I'm picturing. I'm thinking more about engineers and planners spending their time improving things instead of typing into boxes and trying to figure out how to use a system. A factory that can show its brand customers how it performs using data, but not just claim it. So actually have a system that is covering that whole base.

Thank you, Jamie. And I know you speak to brands and manufacturers on a daily basis. What have you found are kind of their main, I guess, blind spots when it comes to information or their main inefficiencies that you know that the technology that you have can help them with?

The conversations, we're having more and more brand conversations. Typically GSD was used as a tool on the factory floor. And it's not just a create an SMV number. GSD really as a methodology helps factories improve their efficiency, improve their processes, break down their process to go, okay, why are we doing it like this? Why is the method in this way? How can we improve? And what I'm hearing from the conversations I'm having with brand is a couple of things, right? So it's the brand would like to get an idea of cost at an earlier stage so that when they're designing a product, they can really say, okay, if I make this design and make this design change, is it going to affect my price in a way that means that we can't sell this? They also want to work more closely with their suppliers. So, you know, creation of SMV standards is not about beating down on price for suppliers. You know, if anything for the supplier, it gives them a, it gives them advantage to actually justify the price that they're quoting. So there is a real conversation between the two. But the other side of that also is this manufacturing excellence side of things where brands want their manufacturers to be more efficient, to be better at creating their garments, to create better quality garments. And really the conversation I'm having with brands is, you know, how do we understand what's going into the method and how do we improve on that? And That's the area where I think we can really add the most value.

Thank you, Jamie. And thank you to Annika and Chanaka as well. I do want to move on to our audience questions now so they get the opportunity to get their own questions answered. We have some good ones through already, so thank you, everyone. If you haven't asked your questions yet, there is, excuse me, still time so please use the Q&A box at the bottom of your screen. But we'll take the first question which is for Winter Quilts. How long did it take before you started seeing measurable business benefits from the solutions? And Shanaka will come to you first with that one.

Shanaka, is it you? Sorry. Yes, so we actually start, we are still at the initial stage of it, like we started onboarding GSD this year, second quarter, and we completed the phase one and phase two trainings and like Right now, we are training the model or the database. And we are targeting on seeing the results probably next year, focusing on our core products in the business. But during the project proposal stage, it showed us incremental-- I mean, the payback or the ROI was even less than two and a half years that was quite attractive and yeah I would say that's where we are right now.

Thank you Shanika so maybe we'll have to do another webinar with you in a year's time to find out all those results.

So the next question here um shanika and annika will will stick with you um because it's talk about and again you may not know they've been early on but have your brand customers responded differently since you introduced more data-driven costing and planning processes or what feedback have you received from the brands regarding transparency and responsiveness So again, in terms of the brand's responsiveness, Madeline, we're still not at that place at the moment. We've just completed our phase two. But what we have identified is what are the internal benefits that we are going to get. And in terms of streamlining, like I said, I keep going back to the people factor because it is a learning journey for us, even for our steering committee members and for those who are interested even at executive level, it's been an understanding initially internally on what are the benefits and then a slow progress into then rolling this out formally with our brands. Because also we need to shift this mindset of technology is not replacing a person. It's not replacing, it's just helping you, Jenny, as you mentioned, How can we be more efficient? How can we be more competitive? So in terms of the brand's perspective and from the costing part of it, we are still yet to have feedback from them. But internally, definitely we've been able to build our processes now around this. So it's been faster. I think response time has been faster. That's one thing that we are witnessing so far.

Thank you, Annika. And Jamie, a question for you here picks up on one of your AI points, I believe. Where is AI generally useful in technology like this today rather than something that we talk about or are scared of?

Yeah, it's a great question because we just hear the word AI everywhere. What does that mean? What it means is we are taking data and we are making sense of that. So, you know, for example, in GSD, why AI has been so successful there is that we have these you know, proven built in methodologies within GSD. We're not we're not asking AI to create these methodologies. What we're asking AI to do is speed up that process by by matching those methodologies to what that's that style that they're looking at. So so, for example, the reason we can the reason we can take an image of a shirt, put it into GSD Quest and come up with a pretty accurate bill of labor is because we are not creating that bill of labor from scratch. We're matching it to the foundations that GSD is built on. So, um, Sometimes there are questions around, why can't I just go on to one of these big AI models and say, give me an SMV for this? Well, it's not built on standard data that has guardrails. It could be built on anything. So we are using AI to automate processes, to connect different systems so that we're not having to find something from an email, find something from a WhatsApp message or whatever that is. We're speeding up that process using AI. I think we're still at the point where AI is speeding up the process, but it's not something that we should have 100% trust in. What we're doing is we are, in the same way that you might say to another AI system, write me an email to Madeleine thanking her for her time on the W2N webinar, and it would write Another madam.

But I wouldn't just send that email. I would read through that to make sure it's not written anything silly. And I guess that's the same thing that I would caution the users of any AI system.

Yeah, it will speed up that process. But it still requires that human intervention to make sure that everything has been done in the way that you would expect it to be. So, yep, we are using AI to speed up the process and to automate as much as we can. But those industrial engineers that are using it are still becoming really effective by using the system and then what it's capable of after that initial SMV has been created.

Interesting. Thanks, Jamie. Another question for you here, and it's more on the implementation side. How do you help organizations when implementing the new digital solutions?

So implementation is the key part of any technology system. So how it is trained to be used, how it is connected to other systems that customers have, but also how it is developed as it goes. So there's a number of things here. In larger installations, we would never say we're going to come in and we're going to create libraries and templates for all of the styles that you create. What we would do is we would tend to have that sort of staggered as we go. So let's start with these styles. Let's make sure that we're effective there. And then let's move on to maybe something more complex in the future. So we are very careful to make sure that any of the customers that are buying our solutions, feel supported by us, feel that we're not just training them, this is how you use the software and then we move on. We're actually running live projects with them in sort of more of a consultation approach rather than just a train and here's the software. So it's really important because that implementation can be the success or failure of any product that's installed. And then we are there to make sure that happens correctly.

Thank you Jamie. And a final question now for Shanika. How long does it take to embed this across four factories? So you've said before you're starting it within your key product lines. Is this across all four of your factories at the moment? And how did you go about that? Or have you started with one factory and how's that going? So we are trying to implement it all across, like considering all four factories based on the, we are going on the product base actually. So our main product is school uniforms. So we are targeting on that first and then the rest of the products. So it will be implemented like all across the four factories, depending on how the product allocation is for the factories right now. And we are trying to roll it out and get it up and running 100% by end of 2027 is the goalpost for us. Right now, we are on track with the roadmap. And we have 10 licenses with us right now, GSD holders. We are in the process of building the database is what's going to take time for us because we started this from the scratch. Earlier, we didn't have a GST database. So this is completely new to Winter Quills. This is a new onboarding for us. And so building the database and modeling the styles would take about three to six months down the line. And from there onwards, it's about the implementation in the production flow. How do we improve and then also train the team members for the GSD motions is the tricky part for us, is what's difficult more than training the model. So that's the high level plan that we are looking at. And there onwards, it's about like measuring the performance of the system, like having a KPI, having set KPIs to see how many styles did go through the GSD cost and how many did we implement in the production and how many standardized operation do we have in the database per se. So those are the KPIs that would tell us like how effectively that we are using the system and also how productive it is in the implementation and like realizing the benefit out of it.

Yeah, thank you. And we're running out of time. So I just want to go quickly to Anika on what this has taken from kind of the change management side of this to embed the new technology across the four factories. Thank you. So, yeah, it has been, like I said, it's from a leadership standpoint, it's been able to provide the right platform and the right working environments to be able to implement this. Because I know when the team were working on the workshops for their trainings, you know, they had to take a lot of time off their day-to-day roles and sort of very much focus on these workshops. So it was that flexibility and the ability for them to be able to take on and focus on the trainings.

Yeah, so again, I think it is... It hasn't been easy, but definitely with the right leadership and then monitoring it. As Shanika mentioned, we've set up now a monthly catch up as well with the executive committee where we discuss where we are, where do we stand and what challenges, opportunities are. So I think it's just constantly being able to engage with the teams who are on the job, who are actually doing the work and just supporting them with any challenges that come about and see how we can overcome them together. Brilliant thank you Annika unfortunately that is all we've got time for with that we've actually gone over so thank you to Annika, Jamie and Chanaka for being with us today and providing your insights your experience and your learnings we really appreciate it hearing this from the factory floor as well as the technology side is what makes this conversation I believe so impactful and I hope our audience has gained a great deal from it. So thank you to everyone who joined us as well and to those who sent your questions. If we didn't reach yours, then I am very sorry. We'll make sure we get it to our speakers regardless. So the recording will be with you by email in the next few days, along with the details on how to reach Coats Digital if you'd like to carry the conversation on. So thank you all so much for your time. It's been great being with you today. Thank you.

Thanks very much. - Thank you.