The Future of Fit Standards, Trust & Transformation

Hello everyone, and welcome back to another PYE Spotlight. Today we are diving into one of the most consequential challenges in digital product creation, and that is fit. Fit is a make-or-break factor in digital adoption. No matter how advanced the render or seamless the workflow, if a garment does not perform as expected, trust in digital systems starts to erode. And so today we'll examine why achieving reliable fit is still so difficult, what digital tools can reveal that physical fits often will miss, and where fabric behaviors, avatars, and human interpretation continue to undermine confidence. Ultimately, this conversation is about trust and decision-making and what truly changes for design development and the consumer when digital fit becomes credible at scale. So we are joined by a really great group of speakers who are not only deeply experienced in this space but are also active members of the 3DRC, working collectively to bring greater clarity and alignment to digital standards across the industry. We will share a link in the chat at the end for anyone if you'd like to learn more about the 3DRC work and how you can get involved. So look out for that in the chat box. But first, a huge thank you to everyone on our panel and of course for all of you for joining us again today. We are really, really thrilled to have you here with us. Just before we get started, a couple of housekeeping notes. If you have questions, feel free to pop them in the chat box on your screen. These will be sent directly to our panel chair who will do his best to get to all of them. And please don't be shy. These are meant to be interactive. So please send in anything you'd like to ask. And if you miss anything or want to revisit the discussion later on, this session will be available on demand via Seamless and the PAI YouTube channel very, very soon. So with all that said, let's get to it. Philip and the panel, over to you.

Hey everyone, my name is Philip Sidbury. I'll be serving as your panel chair and also a panelist today. A little bit of background on me. I am currently a PhD student at Auburn University studying digital innovation in the industry. I also have an extensive background in technical design and 3D technical design. So I'm excited about our conversation today. I'll allow the rest of our panelists to do a brief introduction before we jump into it. Michelle, would you like to introduce yourself?

Sure.

Hi, I'm Michelle Greenhouse. I am a senior 3D material artist at Target, but I also chair the 3DRC Innovation Committee. Specifically working on digital fabric interoperability and now moving into 3D drape validation. We work together in a collaborative way to solve industry problems, and obviously this is a big problem, so we hope to address it. I'll kick it off to Chris.

Hi, my name is Christine Klerken Zenz, and I have worked now nearly 4 decades across manufacturing, large retail, and now now, lately in a startup environment, all fit adjacent roles. And my focus today is really focusing on how digital shifts decisions earlier, potentially, and turning fit from really an approval moment more to a design process. So I'll turn it over to Becky.

Hi there, I'm Becky Snowden. I have been at Old Navy for the last 13 years. Working in tech design across various categories and divisions, including a couple years on the digital product creation team, which really kind of started up my love of this topic. And I've been working on the 3DRC as well in the digital fit category. And I'm going to turn it over to Erin.

Hi, I'm Erin. I've spent about almost 13 years at Carter's Children's Wear doing multiple categories, mainly in girls' bottoms, tops, dresses. I have been in the 3D space for— since probably 2019, but acted as a traditional TD at first at Carter's.

Well, thank you for everybody, for everyone introducing themselves. Now that you're mildly acquainted with our panelists, we'll jump straight into it. So the first question is kind of the big one. It has the big word in it, trust. Where do teams genuinely trust DigitalFit today and where does trust still break down? I'll start us off because I'm fairly acquainted with the trust issue in DigitalFit. I think it is very subjective. Firstly, it's all about your familiarity with the 3D space. Have you seen it before? Have you— are you able to see in 3D, as they say? But from my observation, what I have found is that placements and proportions are like— those are the easiest things to gain trust with, like art placements, pocket placements, seams placements, things like that. Um, but then when we get into, um, the details, like the fit details, things like shearing ratios and, and, uh, like saddle and rise fits and things like that, I believe the trust begins to break down a little bit, um, when you get closer to the fit-to-body things. Um, and kind of the best way to, to alleviate that is doing the, um you know, the digital twin process, um, talking through the, um, the differences between the physical and the digital. Um, you know, the construction is going to be a little different, um, because 3D doesn't innately have thread tension, it doesn't innately have seam allowance. Um, so yeah, those are the two areas I've seen where trust is, is pretty much solid, and then it begins to break down when you get into those, those, um critical areas in the fit. Becky, do you have any thoughts?

Yeah, definitely. I think in my experience, the digital fit, we trust it when we get to some of the core drivers of fit. So I feel like the teams are really confident when they evaluate things like more overall ease and proportion and balance. And then kind of like Philip mentioned, the things that kind of veer more towards the aesthetic. So where the style lines are hitting and maybe an overall silhouette. I also think the ability to clearly identify these fit issues, it's definitely something that once people's eyes are trained, they really are able to identify those issues. And then the fact that you can make the real-time adjustments and then see if it fixed it also again in real time, I think is what really starts to build up that trust because you can see it changing. Evolving and getting better. Um, I think for what I've seen, the ability to trust really also helps when you have a really good 3D toolkit. So things like 3D fit blocks and, um, a library of known fabrics that you really know how they, they work in the digital space. And then, um, things like digital component libraries. So, you know, um, those pieces and you can put them together and really feel like I know how all these pieces work and that I know that they're good. And then I think, like, utilizing those tools and standards over and over really starts to build up the team's trust, and it kind of removes some of the variables. So if you trust your block and you trust your fabric, then you can really get down to the style details and the fit changes that you're making. Where it kind of still breaks down, I think, is maybe in the product categories that are a little bit more nuanced. You know, so you get into things like denim or sweaters, um, a product like performance where it is maybe really dependent on the body and the soft body avatar not being quite available for things like that. Um, I think that's where the— it starts to break down a little bit because you lose kind of your trust because you don't have those elements, um, that in your 3D toolkit quite the same way.

Yeah, I totally agree. I think foundational information, trusted foundational information is definitely part of it. Erin, do you have any thoughts?

I mean, I'll just mirror basically what you both said. I feel like the early stages when, when you can first really identify not so major issues, more like the obvious issues that could happen in a garment where when it's on the body, you can spot like the tightness or drag lines before you get really into detail with what is actually happening in the digital asset space. Um, I feel like sometimes you can easily see where your pattern validation is too in 3D up front a little bit before you start to get into the weeds of it all. I feel like where it breaks down, of course, is when when tech probably understands more of what is going on, especially because they're the ones executing the digital asset upfront, trying to convey that to cross-functional who may not be able to see in 3D as well. Sometimes there's hesitation, then it's hard to convince your cross-functional team members that this is what is true. The realism versus how fabric behaves. That could be some aspects of where it can break down to trying to decide whether or not it's the physics or if it's actually what's going on in the 3D garment. So that's basically where I see it.

Yeah, that's a good point. I think it's definitely a muscle that cross-functional partners have to also develop, not just TDs and people that are actually using the 3D. Does anybody else on the panel have any thoughts?

Yeah, I'd like to add also, I had the same question early on in my 3D career as well, where I'm like, how do I trust this? So I worked on a project with a technical designer, actually in the pet costume category. And I wanted to convince myself, like, what, what, what can I use this for? Is it really going to help me predict what needs to happen to this pattern to make it fit and solve the problem? And what I discovered very early on is I was just naturally falling into being able to trust what I was seeing in 3D, making a change to the pattern, and seeing that change reflected in real time. So trust is built by actually having a problem and this thing solving that problem. And it did for me. And I think if we can replicate that throughout our workflows, I think that is one of the many ways that we can build trust.

Yeah, I agree. I mean, what I basically heard you say is trust is built through repetition. The more I use this tool to solve my problems, the more I trust it. And I totally, totally agree.

Yeah.

Yeah. I don't have really too much to add, but I was just going to echo what Chris said and what Aaron said. It's like attuning the eye and getting familiarity. Like for fabric, for example, if you sort of look at a jersey and how that jersey drapes hundreds of times, you're going to start to believe the credibility that the jersey is draping like a jersey actually should drape, because I've seen it hundreds of times. And so you can start to see the difference between a woven and a knit and understand if materials maybe have different characteristics, like it might be a bonded material, so that should for sure drape differently than a really stretchy knit material. So just wanted to add that.

Yeah, I think again, it's that familiarity part of it where it's like the more you use it, the more you get used to it. So companies should not abandon it so soon. They need to just work through it. We do have a question in the chat. Jim B says, does your company have a specific 3D team? And also, do you build assets in-house or do your vendors create them for you? I can tell you from my past role, which was just ended in December. We did it both ways. We did actual tech packs and built assets. We actually did not rely on the vendor to build things. So we were building things from scratch in-house and reviewing them that way. But from my understanding, it does vary from company to company. Anybody on the panel want to speak to that?

Yeah, I've actually worked in both methods. My last role was very much vendor-owned building the assets. So, you know, on our side, we were reviewing. And where the role that I'm in now, I'm— it's building, it's building from the start. So, I've seen it from both ends and there's pros and cons to both. But definitely, you know, both can work in that environment.

Yes, I would agree. I think most companies right now, it's a little bit of a combo where you do have the fit teams that are digitally enabled. So, they're working in some ways starting or editing vendor 3Ds. And then I think that a lot of companies do have a 3D team, but you'd have to have a huge 3D team to be able to do all of the 3Ds. So I think the vendors and the actual like fit teams being enabled is what really like drives everything forward.

Yeah, I totally agree. Jambi, I hope that answers your question. Um, yes, audience, if you have other questions, just drop them in the chat and we'll get to them as best as we can as we go through the conversation. So moving on past building trust to the second question, um, the second question is, what does digital fit reveal that physical fittings consistently miss? That's a good one. Um, and where does that insight actually change decisions? So Chris, I'm gonna let you have that one.

Yeah, I've reflected a lot on this question. Physical fit, let's go back to physical fit. Physical fit is really good at telling us what happened. So it gives us a, here's the problem. What digital fit offers is an understanding of why the problem happened. So it becomes, with digital, it stops becoming just an event at the end of a particular stage gate. For example, we have to approve it, so we have a physical, we approve it. And it really becomes how the garment is designed. So the real shift isn't necessarily fewer fittings. It's really fewer surprises. So being able to iterate in 3D to get to a better physical is ultimately the goal that we would like to get to. So it's really about moving those decisions earlier because that really benefits everyone from designers, technical teams, as well as vendors.

Uh, anybody else want to add to that?

I'll jump in on that one. Um, I actually really love this question because I feel like it kind of frames up digital being not something that is replacing but actually adding something to the process. And I kind of think that gets lost sometimes where people do feel like they're— something's being taken away. But I really think of it as like this other thing that's being added to our toolbox. Where you can do things in digital that you just like could never do in physical. Um, first of all, like the time, uh, aspect. Obviously everybody kind of will speak to that probably a million times during this, but, um, you just could never work that fast with the physical, the back and forth with the vendor and then creating the sample. It's like having, you know, a sample room right at your fingertips here. Um, the other thing is that you can do a lot of things with the garment that you would never be able to do with a physical garment, or it would be very time-consuming. So, you know, taking one leg of the pant off to look at the rise, or taking the sleeve off to look at your armhole shape, it's just stuff that you would never do in a physical environment, or you'd be ruining your sample. And you can do that really quick, back and forth, just to refine the style, you know, swap in shearing amounts and really land the style. And it's just something that's completely impossible on the physical side.

I also wanted to add, if you wanted to go toward the literal sense, if you're actually talking about a physical fitting with live models and all that other kind of stuff, I feel like digital helps you remain consistent. You only have— you have— every brand has their set fit, their set consistency, but when you're trying things on models, they tend to range in different sizes. And so seeing the garment on different forms could give you a different perspective when 3D actually gives you the exact perspective of what the exact perfect person would be in that particular garment. So I feel like digital can help in that way to make sure everything is consistent and uniform to your standard.

It's perfect. I also want to echo on a point that Becky made about physical samples. There is an underlying benefit to 3D, and that's the sustainability aspect. You don't— you don't lose the money by tearing up the sample, for lack of better words. And you also don't need to have the physical sample. So I think that's, that's always the big win when doing things, doing things digitally. We do have a question in the chat. Carol McDonald, we do have a question that's specifically related to Avatar. So we will get to your question later. We'll move on to the next question, and it's related to Fabric. Where does Fabric behavior most often undermine digital fit, and why is it still so hard to resolve this in practice? Michelle, as our expert, I will pass this on to you.

Okay. I have heard a lot, a lot of times that knit fabrics have more discrepancy than woven fabrics in terms of digital fit. And I feel like the, the places where I have seen the most discrepancy is materials that are higher stretchy content, such as rayons, modals, and fiber contents that include spandex. So the 3DRC has kind of aligned on 5 key parameters that we use for measuring fabric physics, and that is bend, elongation, thickness, weight, and bias. And so these don't include stretch and recovery. So I think that that might be also something that knit fabrics have a lot more stretch and recovery that isn't taken into account. So the discrepancy I've seen mostly is in knit fabrics, which are a higher weight, which have a high spandex or elastane or stretchy material content. And then how to resolve it. Like I said, with the 3DRC has sort of identified the 5 key parameters for fabric physics, and it doesn't include stretch and recovery. So I feel like maybe including that in the next round of elements to include in fabric physics testing would be a good solution. I have noticed that woven fabrics don't have as much discrepancy, so that's, that's good. And our 3DRC group has started to lean into a 3D fabric physics drape validation partnering with ASTM, which I can talk about that a little bit later. But our goal is to establish a standard for validation where you compare a 2D image physics to a 2D output photograph, your digital to the physical. And once this is established, we feel like this will unlock all kinds of different things, such as building out your own digital tolerance for your brand and how that can translate to the garment. So there's more to talk about there, but that's where I'll start.

Hey, I'll, I'll just try to follow that up. It's going to be hard. Um, So where it undermines fit, I mean, it's— you don't have a garment without the fabric. So if your fabric properties aren't correct, then your garment fit isn't going to be correct. So I mean, that's pretty much the heavy, heavy correlation there. I think it may be hard to resolve in practice also because of this The theme I think is going to be in this conversation is repetition. The more you're familiar with your digital fabric's relationship to your physical fabric, the less of a headache it will be. If you go into it and it's jarring to you at first and you, you don't develop that muscle, it's going to be more, more of an issue to resolve in practice. And the fabric properties are only getting better, to Michelle's point, like The more, the more we analyze, the more we improve, the more people practice, the better it gets. Uh, anybody else want to add to that?

Yeah, I do. Um, the repetition piece, I think you're, you're totally spot on there, Philip. Um, in working with, with a lot of, uh, vendors in the past, I think where, where there's often a struggle is really around, um, not, not necessarily a struggle, but I think what, what We want people to understand is that the knowledge that you have, if you're, if you know your fabrics, for example, that doesn't look like a jersey. I know what a jersey looks like, and that doesn't look like a jersey. So that doesn't go away. You have to be able to visually identify where you see discrepancies, where you know the fabric should look a certain way, and then you can go into that software and understand, is it a fabric issue? Is it the way the properties are presenting themselves? Is it the way the software is interpreting that? But ultimately, it starts with the base knowledge, and that doesn't go away whether you're whether you're talking fabric, whether you're talking fit, whether you're talking any of it, the base knowledge is still there. And that's what helps us kind of push that software, build the tolerances, and understand where the problems are and how to solve them.

Yeah, it's kind of hard not to know that. It's kind of hard to know the problems if you're not familiar with them.

So it does take repetition.

Exactly.

Yeah.

Totally agree. Mercedes, I see your question is related to avatars, so we'll get to that later. Yours as well, Gerald. So Caroline has a very general question. Which 3D package or software system is the most user-friendly? I think there might be a lot of bias. It's kind of where you started. So I'll let you guys take it. But I mean, my opinion on it is it really depends on where you started. From my understanding, like if you started in a particular system, I feel like you're going to be slightly biased towards that system. Any other thoughts from you guys?

I mean, I've dabbled, I've dabbled a bit in the Optitex 3D. It's, you know, there's a complication there, but it's a very robust 2D system. I've only viewed and browsed where I haven't actually built anything. And of course, CLO is very easy to learn, so I'm kind of biased that direction. And there's so many resources out there to help you get to that point. So, but I think any and all can be learned. It really depends on what your product is. What's available to you, and then just learn it.

I would agree. I think it really is kind of the user-based a little bit, because I've dabbled across the three and some a little bit more than others. So it's a little hard to say because some I've definitely dug in a lot deeper on. So I obviously feel like those ones now I know a lot better. Um, but I would agree, I think Optitex probably has the more of a 2D system, um, and then the other two I think are more 3D enabled.

Yeah, but I've been recently impressed with the robustness of CLO's 2D. Um, I, I think that there's definitely a lot of gains being made there.

When it comes to fabric, both of them have pretty robust libraries. I'm comparing CLO and Browzwear. Those are the only two I've used and they're both pretty similar in terms of how material is draping on a specific avatar. I have no bias one or the other.

Caroline, I hope that answered your question. Carol McDonald, she has a question I believe is specific to you, Michelle. She's asking if you can list the fabric properties in the chat for the participants. I guess those fabric properties you mentioned earlier.

Oh, the 5 that we—

the 5 key parameters.

Yeah.

Yeah, I can type those into the chat.

Sure.

Okay. I'll take 2 more questions and then we'll get to some other ones after the next question. Saeed, I hope I'm saying that correctly. How is 3D DPC used in denim apparel and wash prototyping and what are the benefits? What benefits does it bring to the process? I specifically haven't worked in heavy denim product. Being my background is in children's wear. We weren't doing like crazy super duper novel washes and things like that. So I'll pass it on to the rest of the panelists. You guys have any feedback about the denim apparel and how wash prototyping is using digital and what benefits it brings?

I would say denim is definitely a challenge because of wash. I can't really speak to the fabric side as well, but I know it is a challenge, just like I said, to, to trust what you're seeing and the fit, because we do know that the wash impacts the fabric so much in denim that, you know, I think looking at denim as more of an overall fit, that, that works really well developing, you know, like a new silhouette. The fabric side is— that's the part I can't speak to quite as much.

Yeah, I know that in denim, um, because of the wash, the, the pattern dimensions change radically and in a very strange way often. I've seen some of those after-wash patterns and they're just weird looking. Um, so I, I would say that because of the wash concern, you would probably want to fit and evaluate the garment in a pre-wash pattern capacity first. And that, I think it goes back to my earlier comment that in 3D you can, you can section off things a little bit better to say, now we're going to review the pattern just for the pattern. And now the next thing we need to do, which we can currently only do in physical, is work out the dimensions for the wash process. So those can be done separately, um, but it is something that, you know, in a dream world in the future, if the system could actually work out what a true wash process would be digitally— I just don't think we're there today. But just know that, that it's not a one, you know, an all or nothing. You can actually still do it, but you have to really be diligent about saying that this is what we're evaluating around fit in a pre-wash capacity, and this is what we're going to evaluate in the wash, which really currently needs to be done in physical.

Yeah, I totally agree. Especially if you're taking in the hand processes and things like that, that will totally change the stretchability and things like that. So yeah, totally agree. I'll take one more question from the chat and then we'll have to move on to our next panelist question. Thomas has a question in regards to just the process. How has the development process changed with the implementation of 3D in your experience? And do you see drastic shifts in the development timeline as the usage of 3D evolves?

Yeah, I think—

are you trying to fit it? Are you even trying to fit it in your current process?

I think we'll get that in question 5. I think definitely we got something to say about that in question 5. Yeah.

So, uh, a lot of these questions you guys are asking are very good questions. We'll get to them. Um, so question 4, what does an avatar actually need to be good at for fit decisions to hold up in the real world? Chris, I'm a fan of what you're doing.

A lot of questions about the avatar and definitely, I mean, it's the standard, it's where you start. If it doesn't fit on the body, then what's the point? I get it. Now let's start by being just describing what we all know would be the perfect avatar. It would obviously be the body dimensions of our guests, the one that we've decided we want to fit to. It would definitely move, it would sit, it would stand, it would do all the things that a human can do. It would tell us whether they like the fit. So obviously using a little bit of AI in the future to be able to understand that. Of course, then we get into the issue of fit isn't just technical fit. Sometimes it's preferential too. I like things this way. You like things that way. So the future is out there, but we're not there today with the avatars. And I don't think we need to be. And I think that's— I want to reframe the question that the avatar does not need to be perfect. It just needs to be— an accurate— allowed to be a tool to be an accurate predictor of the next step in the process. So if I fit on an avatar and it gives me good directional positioning for what needs to happen next, and I do that thing and it actually does work according to what the prediction told me it would do, then in my opinion, the avatar is doing its job. So I think that, that it's important to kind of understand what's what the usefulness of the avatar is today. And it's in many respects, it's not that different from the physical mannequin. We always know that you put it on the physical mannequin as a standard first point, but then you have to put it on the body for movement and preferential understanding of comfort. Um, so any other thoughts on, on the avatar? I know there's a lot of questions around that, and I, I had a very particular point of view on that. So anybody else want to share?

Yeah, I'll add to that. Um, obviously best case scenario, your avatar, you know, matches exactly to your live model that you're used to seeing. And in that case, it really takes a variable out of the process because your team is used to seeing that body wearing that garment. And it just, you know, again, we're like kind of reiterating this like repetition and training your eye, and that does make it a lot easier. But like Chris said, we're already used to some discrepancies when you have a physical fit form and you also have a live model. They're usually not exactly like for like. So I do think we can't put the same pressure on the digital that you would in the physical world where this mannequin and this avatar have to be exactly perfect. I think we were able to kind of make up that gap in, you know, real life. So we should be able to also make up that gap in digital. For me in particular, I think the biggest win when you get into avatars in the digital world is to review grading. I think Erin mentioned it earlier, digitally, like how you can review a full-size run simultaneously and it's on a consistent avatar. It's kind of impossible to do that physically. And obviously very few brands can actually, you know, have access to that many live models or afford them or be able to get them all in a room at one time. And it just unlocks like a level of grading visibility and equity that doesn't exist in the real world. I think in my case, especially because I'm in kids and baby, that's another layer. You just can't have kids and babies in the office all the time. And it just kind of removes, again, those variables that are kind of unavoidable with a live fit model and the growth changes that happen with kids and baby, that your fit model from last week is no longer your fit model. They've gotten too big and keeping them still. To be able to review things. So I do think, again, there's some things with, um, when you get into digital that are actually a win over the physical. So I think it's good to like reframe it that way too and know that you have that level of consistency and repeatability when you have, uh, Avatar.

Yeah, and there I want to add to what Becky said about especially bringing up the grade size approval, but also the ability to look at multiple different bodies of a single size, which those are projects that you could never do in cycle. You had to wait until the end of the cycle and do a big big production about the grade review or the, you know, how do we fit on various size 10s or various size 8s. And those are things that you can do at your own desk in cycle to test things out. So in my feeling that the digital offers the ability to improve the product and view it in ways that you just couldn't do realistically in the physical world.

Totally agree. Um, Becky, I definitely agree with you about the expectations in digital space are like miles away from what we accept in physical, uh, uh, we would have these high expectations of like the diaper fit on the form and like the diaper is going to vary. Um, there's no way we can standardize like to the eighth of an inch that diaper. So it's just given a little grace. To the digital, like back off a little bit, you know what I mean? We do have another question in regards to the avatar. Gerald asks, how do you get an avatar to be close enough to the live fit model? Anybody want to take that one?

Well, I know with, with our company, we work with like the Avanon to, to have the forms reflect what we do. In, in-house. So you just work with the vendor to, to do that. If you're using the avatars from the 3D software, there are settings in that platform where you can adjust sizing to the avatar to fit your standards. So there's ways to adjust the avatar, or you can get custom ones built for you.

Yeah, going the Alvin Enrod route obviously gives you a lot more precision in how you want to adjust that body. You can get a lot closer to your live model. The avatars that exist within the software gives some adjustability, but you have to accept, for example, a stance or, you know, the overall shape of this part of the body or that part of the body. But you can get relatively close. And really, it's— it goes back to, I think, an earlier comment that was made is, do we really want to fit to one particular fit model body? Or are we really trying to fit across a range of different body shapes within a single size? So I think that's a workflow change and a thought change that we have to make within the industry to really be a little bit more open to, you know, looking at the garments on various bodies of the same size.

Yeah, definitely agree. Circling back to Carol McDonald's question, her— I believe her question is about posture. And just, just imperfections in like the physical body. She says avatars may not reflect the more normal of people, especially the roll of the shoulders or the hip tilt. That could be a limit to trust, which I agree with. Do you review or compare the 3D CAD avatars to the physical fit models? I can start it off. I mean, typically the, the avatars are built off of the measurements of the physical fit model. So the physical informs the digital, if that makes sense. Uh, from my experience, they don't have the depth of, um, measurement entry to get like those inconsistencies from left to right on the form. Like it's going to be completely symmetrical in the digital space. Um, but we do review them. Um, um, digital— the digital twin process, you, you pretty much do do a side-by-side review to try to establish that trust. So So I'll just go ahead and say yes to your question. Anybody else want to tag on?

I think you said it. Yeah, I agree.

A win for me. So moving on to the next question. This one is about workflow. So if anybody in the chat asked about workflow, hopefully this conversation answers your question. The question is, why do some of the digital fit workflows accelerate decision-making while others stall it?

Hmm.

So based on my experience, what accelerates or speeds up the process is basically when uncertainty is removed from the situation. And what ultimately slows it down is when you leave room for interpretation. So for example, like In terms of accelerating, if your digital asset is answering a specific question, then, you know, it is like how a garment is fitting, its tolerances, how loose it is. It doesn't leave anything up to interpretation. You're actually answering the question you set out to solve with the digital asset when Things are shared like fit standards, alignment. Again, that eliminates any subjectivity to what you're looking at. Everybody that is looking at that particular garment is assessing it the same way. So there's no room for it. Again, no, no room for interpretation. But the cycle, just like we keep repeating, consistency, trust is a huge issue with 3D. And everybody basically has to be on the same page. Open and willing to retain the same type of information, to trust what they're seeing is valid instead of waiting on a physical sample in order to do that. Clear ownership roles to me play an influence on how something moves across the platform. Like if TD is responsible for creating it, they know how to build it. Whoever is interpreting it and looking at it, they know how to analyze it. And then whoever finally makes the call for approval. That— so identifying specific roles in your process can help accelerate it. And then ultimately alignment. So whoever is again reviewing it, they're reviewing it through the same lens. Everybody's looking at the same thing. Design's not looking solely on aesthetics. Tech is not looking solely at the fit. Everybody's looking at the same thing. Interpreting it the same way. And so installing it is having maybe too much information or too much data, like overload, where people don't know how to interpret that and realize what they're seeing is what they're actually seeing. I feel like I've also seen stalls in skill gaps, like actually there's a difference between seeing in 3D and then seeing in the physical set. So having to learn those skill sets can, can cause a stall in that. And then workflow ambiguity, when DigitalFit is positioned as a discussion point instead of a decision tool. So again, that goes back to interpreting things versus just making a solid decision on what you're looking at. That's where I feel like I see a lot of acceleration installs with 3D.

3D has to be able to solve a problem. It starts with defining what is the problem you are trying to solve. Too many times I've seen, you know, 3D just layered into an already existing physical process, and then it becomes an either/or. And for those comfortable with a physical process, the either/or is easy. I want to stick with what I know. So you have to have a problem that you're trying to solve. And I think it really— the workflow, I believe, is the key to either success or stall of the entire— especially in fit, I would say, but probably the whole thing. I would be bold as to say that, that you have to look at workflow and simply layering 3D on top of existing workflow can be problematic. Because if you think about it, the physical process is one that is very much stage-gated. So you've got steps in the process, it's calendar-driven, you need to approve. It's really an approve— fit becomes an approval step. When you move into digital, it becomes an engineering journey. It's a, it's part of the design process. And I'll give you a story in my current role right now. Um, I'm working with a designer for the first time and having been a pattern maker before, I know that that relationship between pattern maker and designer is very important.

Important.

So one of the things that I'm using to be able to engage with a designer and help us understand each other is 3D. So working on a garment, I've sent kind of the basic shell of it in 3D, saying, this is, this is how I interpreted your vision. And these are the things that I think we need to change. And we had a conversation about it. And then I went in to build more details. So, so it's really becomes an iteration tool. And it becomes an essential tool. So it's not something that as a pattern maker I would ever want to give up. It is a critical, critical tool because it solves a problem for me. And the problem is I need to communicate with that designer. I need to be able to quickly see whether my pattern is working. Those are real-life problems that are being solved through this technology. So workflow, workflow, workflow— it has to be looked at in order to understand where the stalls are happening.

I totally agree, Chris. I feel like showing people what the wins are for them and how this is going to move the process along in the future, like the long-term roadmap of it, is so essential because it is a steep learning curve sometimes for people to get there, and you're asking them to work differently. And if they don't know why, then, and what's in it for them, it's really going to break down. And I think I think the biggest thing for me and what I've found is that having your cross-functional team and the key decision makers at your organization really being behind it and supporting it is what you really, really need to like move it forward. You just, you can't move it forward all by yourself. And as a TD, I'm super confident in looking at the 3D, but if my designer isn't, we're still not gonna approve the style off of it. So I think it's really like the holding hands part that is the most important.

Yeah, I totally agree. Based on my experience and some of my research, the organizational support is a big, big, big factor in how things are framed. I believe Aaron said that it needs to be like— Aaron and Chris, you both said it kind of has to be framed as a solution, not an option. And if it's framed as an option up front, it's likely going to be an option and not the go-to. So totally, totally agree. Demetrius asked a question earlier about fitting multiple layers. He wants to know, how are you solving and/or addressing digital fitting of garments that have multiple layers or components, as in outerwear feel? My background, we didn't do a lot of layering. We were fitting the individual items to get them to fit properly. Um, when we got to some outerwear, we did fit over like a top and things like that. And I mean, tool-wise, it was some simulation issues. Uh, from conversations I've had with outerwear companies, they still— like, for the aesthetic fit, they'll use 3D, but for the functional fit, um, you have to know if it's actually providing warmth. Um, you have to know that your, your polyfill or whatever fillers you're using is like what you bought So the physical sample becomes a little more important in those spaces. You guys have any other thoughts?

I'll go back to an earlier comment where nothing— this doesn't replace completely the physical, the need for the physical. So especially in these areas where you have to, you know, evaluate it for warmth, you have to evaluate it for, can I fit the sleeve if I have a heavy sweater on, those sorts of things. But again, it's the iteration. It's getting to a point where you're ready to actually see the physical in a better space, where you're more likely to get an approval on the first as opposed to having to iterate. You never want to iterate in physical. I think if we're iterating in physical, that's your opportunity. Yeah.

Yeah. Um, Demetrius actually added on to his question and asked, how are we addressing movement or functionality? Um, some static decisions can't be can't currently be made in a virtual space. I'll start this one off. I think what digital offers is tools like the fit map, strain map. You can move around the avatars and see where those stress points are. And that's something that you really couldn't get in physical. You kind of rely on the model's interpretation. And sometimes, like Chris said earlier, like it's a preferential fit and it's not like a functional fit. So I think 3D can keep it objective with their strain map. But as you said, like, we're just trying to get to a better final garment. Like, we're, we're not necessarily selling physical garments. I mean, not— we're selling physical garments. We're not necessarily selling the digital garment. So we're just trying to get to that physical garment that is, is sellable and can fit well and serve our functional fit needs. Um, anybody else have anything to add?

I'll reiterate that, that digital gives you more information, not less information. So in a jacket where you at the end maybe need to see that physical to test all the things that we talked about earlier, you're not out anything. You have all that additional digital fabric, digital information around, um, you know, everything from, from how it's behaving in the fit mapping, how it is looking in terms of maybe different, different body fits. I mean, when you get to an approval, you want to be able to have as much data as possible. And I— and that's what 3D kind of offers is you have visibility to not only the garment, but you have the pattern right next to it. In a physical workflow, you don't necessarily ever see the pattern. And that's data that you're missing to make an approval. So you're seeing everything and incorporating it as an add-on and an additional point of data only enhances that workflow and that approval step as well.

Yeah, totally agree. Okay, guys in the chat, we're going to move on to the next panelist question and I'll jump back into you guys' questions. So the next question is, where do teams struggle most to interpret digital fit outputs and why does that gap persist?

So I'll take that. I'll kind of go, you know, build on to what we've been saying quite a bit, which is about repetition and training the eye. So I really do think that trusting 3D is like a learned capability and it's about building that muscle memory to evaluate fit in a digital environment with the same confidence that we have in the physical environment. So that repetition, repetition and recalibration is what kind of keeps building it up. I think early on, the fastest path to people being able to interpret the fit output is just doing consistent side-by-side validation. So reviewing your 3D with your physical over and over. And like Michelle said, you know that the jersey is draping how a jersey drapes. I think the comparison really allows teens to start to identify where it's very accurate to the real-world fit and then where it's falling short. And then I think more importantly, it starts to create an opportunity for us to diagnose why the discrepancy is there. So not just saying, that doesn't look like my physical, but saying, why is it? Because my avatar is different to my model? Is it because the fabric behavior? Is it— Is it something in the digital construction that's not quite looking like the physical? Or is it just simply like your simulation settings? Sometimes that makes a world of difference. So I think understanding why the digital is not accurately reflecting the physical is really critical to address the gaps so that you don't just kind of move on. You look at it once, you say, my teacher doesn't look like my physical, I don't want to look at this again. Keeping, you know, that cycle of figuring out why it doesn't, fixing it, and then showing it to the team again is really what starts to build it up. And I think it reinforces with your team that it's a decision support tool, it's not like a blanket replacement, and that the feedback that they have is really actively informing continuous improvement and better product outcomes. We're not simply just trying to push the 3D through and make it happen, that we're really trying to take in where it's matching and where it isn't so that it, in one day, can always match and we don't have the back and forth. And then I think where the gap persists is in places where we haven't done enough of that, where we haven't been able to do that iteration. So I think scaling it up through product categories, starting with something that is very easy to see a like for like, maybe like a t-shirt. And then, you know, as people get comfortable with that, then scaling it to the next product category that you find to be maybe a little bit more challenging. I think it kind of builds trust on top of trust and then it can create kind of the adoption roadmap of your product categories.

I mean, I agree.

The—

I mean, not to sound repetitive, I mean, basically everything you said in terms of how to interpret a digital fit is there, just the consistency of it, how to translate it, and how to, uh, teach people how to interpret that. So I feel like that is kind of what leads into the persistence of the gap, because I feel like a lot of companies adapt the capabilities, adapt the software, they get the software, they get the technology, but they don't put enough time and emphasis behind implementation. So they, they run too quickly into building instead of standardization, finding standards, training, and then even governance over those things. And so I feel like, you know, you get into the weeds and then it's like, you know, you have this 3D garment and it looks nice and, you know, but you don't really know how to interpret it. You, you can't teach you know, who, who is also looking at that garment, how to interpret it, especially when it's not in their wheelhouse to, to look at, to look at it. Um, so I mean, I totally agree with everything you said.

I think it's also important for, for us to not put as much as too much pressure or undue pressure on the 3D workflow that we didn't already put on the physical workflow. How many times have I evaluated a garment where it's in like fabric, it's not the exact production fabric, and I've—

I've—

you can do it. I mean, if it's, you know, a type of fabric type and it's close, you can do it. So why would we judge 3D any differently? So I think it's understanding where those differences matter and where they just don't, where it's just noise. So yeah, that's what I want to say about that is, is just being fair about You know, it's pretty typical, something new, we have to be very critical of it. And I don't think that's necessarily helpful if that criticism in the physical space doesn't matter anyway.

Yeah, I mean, I agree. I mean, sometimes people have a tendency to blame the technology, like the technology is the problem when really it's just how to translate it and then trust that it's not the problem. Yeah. And it goes back to at first, yes, most companies have to do the apples to apples, like to like. I mean, some, some areas may not even see the sample size or the garment in the size that they're used to seeing it in. So to them, it may look too big or, you know, but, but they're willing to trust a picture or a strikeoff or something, you know, that the lighting is distorted, but yet you can't, you know, identify any or identify all the issues in this, you know, digital space.

3D also has a level of precision that physical does not. And I'm remembering years ago when I made the transition when I was a patternmaker from making patterns on the table to going in the system. And I remember fussing with a corner or fussing with a piece, you know, a line on a piece. And I was manipulating a line and I realized I was manipulating it 1/32 of an inch. But it looked this big to me on the screen. And I think now digital is the same way, 3D is the same way, with a problem. Maybe you, you would not see it as much in an actual garment, but it's under a microscope in that 3D. So that's another thing to learn is, am I fussing about this one detail too much because it's really showing up very acutely in the 3D, whereas in physical it would sort of blend back into the fabric or the color of the fabric or the pile of the fabric or whatever, like a dragline, for example. So yeah, it's, it's, it's attuning the eye, but it's also realizing that sometimes what 3D is giving us is the absolute truth, not less of it.

Yeah. Great, great conversation. Guys in the chat, in the essence of time, we're going to have to get through the rest of our panel questions. The next question is, how can the industry align on fit expectations without flattening brand-specific fit DNA. Michelle?

Yeah, thank you. Yeah, so as I alluded to, the 3DRC Innovation Committee has a group of us who are collaborating in the industry with academics, with ASTM, and brands, labs, software providers. We're all coming together to come up with a standard for 3D drape validation. And we feel like this 3D drape validation is going to unlock, uh, once we establish the criteria for the validation, we're going to unlock a digital tolerance that we can recommend. And everybody's already said it, but we have a digital tolerance and we've already come to believe it and rely on it in physical materials. We should have the same in digital materials. So there should be some variances that each brand can identify based on the validation standard that we create, Brand A could say, you know what, my tolerance is 5%, or Brand B could say, you know what, my brand tolerance is 2%, or whatever it is based on the criteria of the validation that we define. So long-winded answer, but I think that could help the brands have their own DNA based on the standard, 2D standard that we put in place. I also believe that this is going to unlock so many different things for other digital standards in the future. So for example, it could be a texture-based standard or it could be something that once this standard is established, then maybe your team could branch out into other technologies such as AI for fabric physics. So yeah, hopefully that answers the question.

Yeah, I think you did a great job. Um, and just from a fit standpoint, um, I totally agree. Like the, the purpose of the, these, uh, aligning our expectations is to push everything forward. It's not necessarily to, uh, give out people's secret sauce or their trade secrets. Um, it's more how can we on a broad level, um, level set the expectations for 3D, um, fit reviews, um, level set the expectations for fabric. And from there it's only up, like we can just build on top of that and make the processes better. It's not to get into the details of who is your fit model, what are your measurements, like what are your blocks? That's not what we want to know. We just want to know how are you working in general? And that way, if we are all working in a standardized manner, that helps the manufacturers and it just helps us get more into a better general process for digital fit. Becky, you have anything to add?

Yeah, I'll kind of reiterate what Philip was saying. I think it's not about like the details, but it is about those general like wins that we're seeing and the pain points. And I'm finding through things like the 3DRC that we all really have common pain points. And I think collectively being able to group those pain points together and elevate them is really important. I think it helps us to tell the 3D softwares what we need and how we actually work, um, so that they are doing the updates in their systems towards what we need. And I think our voices are much stronger if we're all together on that. And then I think from the vendor side, you know, a lot of us work with the same vendors, and being able to tell them exactly how we all want to work, I think, is really helpful so that they can train their teams and allocate their resources appropriately so that it's moving everybody forward. I think, um, it— we again, like, the, the industry only moves forward if we all kind of work together in that way.

Totally agree. Anybody else have anything to add?

I just wanted to add that the goal of the validation standard is obviously to create consistency across all the different brands and retailers and to help digitize the supply chain, but also to increase that confidence and build trust in your 3D fabric physics. And we know that it's a starting point and it can only get better from here, but we have to start somewhere.

Exactly.

Exactly.

Okay, so we're going to wrap up with one more panel question. Uh, this is going to be open to everybody. Um, if digital fit becomes credible at scale, what actually changes and for whom?

I'll jump in. Oh, sorry. I'll just say we kind of touched on it, but we did say sustainability. Obviously, that's like a real-world impact on everybody as Digital Fit scales. I think the more that we can trust to fit digitally, and the less reliant we are on those physical samples and all the waste that comes with that, um, is, is really impactful, especially if it's an industry-wide trust that we have in them.

I was actually going to say the same thing.

Oh no, sorry, Erin.

It's fine, that means we're on the same page.

I would say that, that having made that jump in that journey in my career, that it brings into your space, the ability to do more with the, with the tools that are in front of you. So when I was a pattern maker, I wasn't the sample sewing room, but sitting at my desk, I am the pattern maker. I am the grader. I am the cutter. I am the sample sewer. So it's, you can do more. You can, you have a much more potential to have the end result and the answers you need, and you don't have to wait. So when What you, what you gain is that instant data and you don't have to wait days and days and days to get the result, which may not be the right result.

And just to piggyback off that too, I just feel like not only does it do that, but it also teaches you, like even the person who doesn't know tech can, can, can learn it to a degree. And I feel like that can only aid you in your, your department. Even more. I mean, I've experienced designers that maybe are not totally familiar with construction or patterns. And so I feel like it will help you become a better designer, or as a tech, it could help you understand more aesthetics, just stuff that's not necessarily always in your wheelhouse.

Exactly. And that will lead to better product. I will make a bold prediction that if we truly did this at scale, all the things that we just said, Product would improve, fit would improve, guest satisfaction would improve. All those metrics would go up. All of them.

Yeah, yeah, totally agree. I think it, it does kind of— it has like a decentralization effect where it's like you're not only responsible for this, you give visibility to everything. And that's kind of what digital transformation in general does. So totally agree with you guys. Well, I want to thank everybody for joining us. I know I didn't get to all of the questions, but we do invite you to connect with us. Michelle is one of the chairs on the digital— not the digital innovation subcommittee of the 3ERC. Myself, Becky, Chris, and Aaron are all on the technical fit committee. Please do reach out and join the groups. You can you can actually join the groups at 3drc.pi.tv and just go to the group you're most interested in. And thanks again, guys.

A huge thank you to all of you on the panel for such a great conversation. That was great. And also a huge thank you to everyone in the crowd. The chat was alive with a lot of discussion and questions too. So thank you for bringing that kind of energy to our spotlight today. I think it is often framed as a technical chat channel, challenge, but I think it's safe to say after today's conversation that it's just as much about interpretation, alignment, and decision-making as it is about the tools as well. So thank you all so, so much. As mentioned at the beginning, all of our panelists are on LinkedIn, so please do reach out to them. And as Philip mentioned, they're all involved in the 3DRC. I believe a colleague of mine is putting the link to the 3DRC in the chat as we speak, so please click on that to find out more and also to find out how you can get involved. We'd love to include you in that. We'll be continuing this conversation across our, our Fashion Tech Shows throughout the year in London on the 30th to the 31st of March, New York on the 28th to the 29th of July, and LA in September, dates pending. So please come along to those events too if themes like this and other related to DPC and 3D and AI and so on are interesting to you. So yeah, thank you again for being part of it. We will publish both the full Spotlight video and a seamless article very, very soon. So look out for that and looking forward to seeing you at a future Spotlight. I believe our next one is in April, so we will see you there. Thanks again.