Narrator [00:00:04]:

Welcome to Supply Chain Now, the voice of global supply chain. Supply Chain Now focuses on the best in the business for our worldwide audience. The people, the technologies, the best practices and today's critical issues, the challenges and opportunities. Stay tuned to hear from those making global business happen right here on Supply Chain Now.

Scott W. Luton [00:00:32]:

Hey, good morning, good afternoon, good evening wherever you are. Scott Luton and Karin Bursa with you here on Supply Chain Now. Karin, how you doing today?

Karin Bursa [00:00:40]:

I'm doing great. Hey, Scott, it's a great day to be in supply chain.

Scott W. Luton [00:00:44]:

It is. I like your tagline and I know, I like it even more because it's your mantra and you're absolutely right. And you know what, it's a beautiful day also to be in Georgia with these awesome early fall temperatures. It's gorgeous. Just outside the home studio here. But I digress. We've got an outstanding show teed up here today, folks. This is gonna be a special one.

Scott W. Luton [00:01:06]:

Get your notes ready. Whether you do on your phone or old fashioned pen and paper like me. We're gonna be talking with a couple of business leaders on the topic of key trends that are shaping today and tomorrow when it comes to the world of fashion retail, especially from a forecasting and demand planning perspective. We're gonna be talking about the challenges that supply chain leaders in the fashion industry have been facing. We're going to be talking about how artificial intelligence, you heard that word once or a thousand times. You go, stay tuned. You can hear a lot more about how AI and machine learning are being leveraged to deliver big practical outcomes. We're going to dive into the critical topic of day to day to data on a variety of levels and we're going to be learning some of the steps that fashion retail leaders got to be taken now to seize the massive opportunity that exists to change how business is done.

Scott W. Luton [00:01:56]:

Karin, should be a good show, huh?

Karin Bursa [00:01:59]:

Oh, I am looking forward to what our panel has to say today. When we think about challenges for supply chain, those are even amplified when it comes to fashion because the selling seasons are so short and we need to be able to maximize the opportunity to be in front of the consumer during those very short season. So really interested to see how they're seeing this transformation of data to insights to action.

Scott W. Luton [00:02:31]:

I'm with you. And folks, if you a lot of y'all know, Karin burst out there. She's been a mover and shaker across global supply chain for a long time. Amongst other things, her planning and forecasting expertise, I'm telling you, we've got a. I usually say 1, 2, punch. But we got a 1, 2, 3 punch here today on Supply Chain Now, so stay tuned. Hey, let us know what you think. If you enjoyed today's show, be sure to share it with a friend or your network.

Scott W. Luton [00:02:53]:

They'll be glad you did. Okay, let's get to work. Karin, welcome in our distinguished feature guests here today, we've had a blast pre show conversations with them. Ellen Meiner, Founder and Principal with the Ellen Meiner Consulting Group. And Kerry Fogarty, Senior Vice President, Client Relations with our friends at PartnerLinQ. Hey. Hey, Ellen. How you doing?

Ellen Miner [00:03:15]:

Good. I am doing very well. Thanks for having me today.

Scott W. Luton [00:03:18]:

You bet. Wonderful to see you. And Kerry, welcome in. How you doing?

Kerry Fogarty [00:03:22]:

Yep, I'm doing great. Ditto on the same. Just thank you for having us and looking forward to a bunch of banter on AI and demand forecasting. Well, the next five hours, one hour, one hour.

Scott W. Luton [00:03:34]:

Hey, that can be arranged. That can be arranged.

Kerry Fogarty [00:03:36]:

I lost my mind.

Scott W. Luton [00:03:37]:

But you know, as I was sharing with Karin and Ellen and Kerry, the pre show folks, we had about a five minute stretch where I think I got a mini master lesson. So we're in for a great conversation. Before we do that, before we do, I got a fun one question for each of y'all and I want to start, Ellen, with you.

Ellen Miner [00:03:54]:

Okay.

Scott W. Luton [00:03:55]:

You know, we're coming off summer and it's been a hot one, so we're all leading into the cooler temps. I think what's been one highlight of either the summer that was or early fall so far this year.

Ellen Miner [00:04:04]:

Oh, well, I've had a lot of changes. Not only did I launch my business, which we'll hear a little bit more about, but my husband and I, we are empty nesters. And after raising our family in the suburbs, we just relocated to Manhattan. So we have been exploring the city again like tourists. So going to Broadway shows, going a restaurant, finding fun happy hours. We've been like kids in the city again. So it's been great.

Scott W. Luton [00:04:33]:

Ellen, that is wonderful. And do you take visitors? I think me and Amanda would love to fly out and hanging out with you and your husband maybe before weekend.

Ellen Miner [00:04:40]:

What's funny is my children don't live in New York and now they're finding excuses to come visit more often. So I am not complaining about that.

Scott W. Luton [00:04:48]:

Love it, Ellen. All right, so folks, I'll tell you, we got some dynamos here today. Now, Kerry, same question. Summer, early fall, what's, what's been a highlight of yours.

Kerry Fogarty [00:04:59]:

Sure. So Scott, right before the call, right, we had met, you had mentioned on another webinar a panel member had mentioned the thing with a, with a fox in the garden. Well, my story on this is deers that just permeate our area where I live and they just buzz through our foliage time and time again. And one instance that we had was my wife had gotten a beautiful. Two beautiful planters, huge plants. And my mission was to order these plants every single day, which I was doing. And then one day I kind of walked by our door and you know when something catches out of the corner of your eye? So I look and I oh go. These plants don't look the same that they did yesterday.

Kerry Fogarty [00:05:38]:

The deer actually came up to the stoop, buzz saws, both planters, so that there was only a little patch on the back. And I'm like, unlike this and this is not so. As the story evolves, the deer have become so accustomed to people. They. You walk out and they're literally five feet away just looking at you like, come on, I'll take you out. So my, my story between the short lived planer stories to now we have the deer with no fear. That's what, that's what my world is living in, living in. And it's rubbing season.

Kerry Fogarty [00:06:11]:

So you just kind of like be careful that you don't walk out and you see a buck ready to, you know, spear you. But is this what you're teaching your little, your little fawns just to come up to people and eat your plants? So, so when we talk about AI and adaptability, how we overcame this is that my wife got these beautiful plastic plants, okay. And they look beautiful day in, day out, season four.

Ellen Miner [00:06:34]:

Love it.

Kerry Fogarty [00:06:35]:

They'll go through there.

Scott W. Luton [00:06:36]:

So different take on sustainability.

Kerry Fogarty [00:06:38]:

I love it.

Scott W. Luton [00:06:39]:

And folks, if you don't know, Kerry mentioned the rut right now in the southeast deer or you know, the cold weather gets them going a little crazy. They're running across freeways, so drive a little bit slower. Karin Bursa, now I'm gonna shift gears a little bit. Most of our audience, the smartest global community, all of supply chain, knows that you're an Auburn tiger. And I wanna ask you. Cause we love talking food around here. What's one food dish that's been a big part of your fandom at tailgates and whatever over the years?

Karin Bursa [00:07:11]:

Yeah, absolutely. Well, War Eagle, some years are easier to be an Auburn fan than others. It's a little tough this year, but when it comes to tailgate, the Auburn fans will never fail you. But I would say my go to is a buffalo chicken. D. It works with vegetables if you're trying to be good, or crackers and chips and everything else as well.

Scott W. Luton [00:07:31]:

Sounds delicious. We're going to. You know what, folks? We've been playing around with this supply chain chow idea for years. We're going to, we're going to put some recipe videos up on YouTube and we'll see. We're going to challenge you all to a dish cook off. But I digress. Today it's not about food. Today we've got an outstanding topic.

Scott W. Luton [00:07:50]:

So let's do this. Let's offer some context to the smartest audience in all of the globe. Kerry, I'll start with you if you would briefly tell us about both your background as well as what PartnerLinQ does in a nutshell.

Kerry Fogarty [00:08:02]:

Yeah, perfect. Thanks, Scott. I'll say I'm a fashion IT industry veteran. I will not mention the number of years or decades in the industry. But I covered enterprise applications. So that would span everything from design systems, merchandising systems, the planning system, sourcing, analytics, distribution covered the whole enterprise application, both on the wholesale and retail side. And the companies that I have in that corporate world was tapestry, Kate Spade, 5th and Pacific, Liz Claiborne. And that's where Ellen and I had the great opportunity to work together for so many years.

Kerry Fogarty [00:08:38]:

And then I had the opportunity to jump from the corporate IT world over to the technology provider world. Two different words. And I've been here with PartnerLinQ since I'm going to say the beginning of 2020, and it's been a rocket ride ever since. So I'm enjoying it and loving it. And it's just amazing what we'll talk about as far as our technology solution. And then Speaking of that, PartnerLinQ is a native cloud. And reason I emphasize maybe that native cloud is because there could be solutions that just get ported to a cloud environment and the vendor says, hey, they're cloud. So this is architected from the ground up.

Kerry Fogarty [00:09:16]:

It's a composable platform. So things that I'll talk about maybe through our conversation today is that there's elements of digital connectivity. So whether you're connecting out to your trading suppliers, internal systems, e commerce systems, social media platforms, it doesn't matter at all. Our platform can connect and integrate to pretty much anything. Another piece of that composable platform is the visibility. So when we talk about supply chain data and all that, we can, we bring that and we bring that to life in our platform. And then the third element is decision intelligence, which really pertains to an area where Ellen's expertise is and that's in demand planning and forecasting. So we have decision intelligence applications that now leverage the magnificent beauty of AI machine learning, that whole ecosystem of that.

Kerry Fogarty [00:10:07]:

And it's really to drive. Give the company the ability to drive significant results in forecasting, managing their supply chain a heck of a lot better than they did on spreadsheets, you know, years ago, which still. We still exist, right? Like it is. There's plenty of spreadsheets that are still around. So it's really a very, very unique platform covering digital connectivity, visibility and decision intelligence applications.

Scott W. Luton [00:10:35]:

I love it. And I must tell one thing you said there because it reminded me the good old G commercials in the 80s. Sounds like you're bringing good things to life. Remember those commercials back in the day? So, Ellen, if you would, same thing. Tell us briefly about your background, including what your consulting firm is up to.

Ellen Miner [00:10:50]:

Okay, terrific. So I am Ellen Meiner and the founder of Ellen Meiner Consulting, and I am thrilled to be here today. And basically, after a long career doing functional roles in the fashion apparel industry, I decided to start my own firm. And the reason for that is because I thought it was time for me at this point in my career to collaborate with businesses both big and small to help them envision their futures and achieve their objectives. Prior to that, I had a long career spanning leadership roles in business planning, demand planning, merchandise planning, sales, and most recently, I was at Tommy Hilfiger North America leading the North America Wholesale planning team, working with some really, really talented people in a great organization, pbh. I've always had an interest in how technology could enable us to be more agile. And that's what led me to reconnect with Kerry. So Kerry and I, as he said earlier, worked together many, many years ago where we were tasked as part of a team to envision what a planning system could look like at Luth Clayton.

Ellen Miner [00:12:04]:

And we did some great work and we really had a good time. We enjoyed the whole group that we worked with. We had some consultants we worked with, we had other business leaders, and then we moved on to other things. And as I was envisioning my business model, Kerry and I reconnected and he introduced me to the leaders at PartnerLinQ. And I was blown away. I took a trip down to their headquarters and the work they're doing in digital transformation, the work that they're doing in demand planning really impressed me. So Kerry and I now are doing some work together. We're going to be writing some articles, doing some blogs, doing events like this.

Ellen Miner [00:12:44]:

And as far as my business model goes, I'm looking forward to being able to share my knowledge and to help organizations, particularly smaller organizations that may not have the infrastructure to have a large planning organization or they just need a thought partner. So as Karin said, this is a great time to be in supply chain. It's a great time to be in demand planning too.

Scott W. Luton [00:13:08]:

Ellen, this is so exciting. And I love Yalls. You know, relationships make the world go round, especially in global supply chain. And I love yalls joint successful outcome inducing relationship.

Kerry Fogarty [00:13:19]:

Yeah. Kerry and Scott, can I interject something? I know this will drive that one maybe a bit crazy. So when you talked about when we were building planning systems, we built this, this magnificent, magnificent tool years ahead of its time. The joke was that you had to be a nuclear physicist from certain countries in order to lung this thing.

Ellen Miner [00:13:37]:

We could have used y then back in the early 90s, should I say?

Scott W. Luton [00:13:42]:

Okay, so Karin, so Kerry and Ellen, what an incredible background and cool things are up to now. But you know, Liz Claiborne, of course, was a common element of their journey. Takes me back to my summers working at JB White in Aiken, South Carolina, where Liz Claiborne was everywhere, including on JB White radio in my ears all day, every day. So I feel like I'm an honorary team member. But Karin, when you hear what Kerry and Ellen, what they've been doing, what they're doing now, it's really exciting. What'd you hear there? Especially in terms of expertise on what our audience is gonna hear from today?

Karin Bursa [00:14:17]:

Well, clearly they've got credibility. Been there, done that. Secondly, they're very excited about the opportunity and what's happening from a tech technology perspective, which I love. And then finally, what they didn't say is that fashion is one of the toughest industries to forecast around. You've got to have your always available and then you've got your high seasonality and your new collections. So this is really going to be interesting on how they're driving new insights and transforming this data into AI driven plans for the business.

Scott W. Luton [00:14:53]:

Excellent point, Karin. And you know what? All other sectors of supply chain, you probably can learn a lot from this conversation here, given how challenging it is. So we're talking about challenges, right? Because challenges, they abound. They go with the territory. Right. Supply chain fashion, retail is not for the faint heart. But that's okay. So let's set the table a little bit more.

Scott W. Luton [00:15:12]:

And I want to ask, starting with Ellen, what are some of the challenges that leaders in the fashion world, especially maybe folks in supply chain roles, have been working to overcome in recent years.

Ellen Miner [00:15:21]:

Yeah. So I loved how you started out before with my favorite expression, data data data. That's sort of a headline in an article that Kerry and I are working on. So data management has been a challenge as long as the industry has existed and probably in any industry. The accuracy of the data and the ability to manage the data. How do you get the data? Now couple that with multichannel complexity. Gone are the days where one silo can just look at their own data. The wholesale channel, retail channel, the econ channel.

Ellen Miner [00:16:00]:

What's going on in social media, what's going on in a fashion show. What are the bloggers saying? We need a way to combine it so that we're not buying inventory for one channel and leaving out another. The other issue we have the big one, economic volatility and unpredictability. That's something that we again every industry deals with and crisis management, we all live through that with COVID supply chain disruptions. And one of my favorites because I love supply chain executives aligning demand planning and supply chain realities. Demand planners and supply chain executive need to be inextricably linked.

Scott W. Luton [00:16:43]:

Oh, I love how you set the table. And being not fooling ourselves with those supply chain realities is so critically important when it comes to everything, not just the band planning. Kerry, same question to you. And then I'm gonna get Karin to comment on what we're hearing here. Carry challenges that fashion, retail supply chain, you name it have been faced in recent years.

Kerry Fogarty [00:17:03]:

Sure. So Karin had touched base on a little bit. But the speed at which the consumer's preferences and desires is changing overnight. Certainly things like with the social media TikTok. I have a niece who they're on TikTok all the time. The how quickly something can shift as based on influence, influencers, how a product or how a brand can get introduced. It's amazing at which that speed is going. Ellen had mentioned it.

Kerry Fogarty [00:17:32]:

The multichannel complexity, the ability to manage and optimize inventory is critical. And we'll go through and maybe somehow have some stats later on in our discussion here. But if you plan and some of the seasonal cycles are very, very long, if you forecast or predict or plan raw, you could be off by millions of dollars in your inventory. And then comes on the horror with that and then we're not necessarily going to touch it in today's conversation is the element of sustainability with that. Right. If you're overproducing, what have you really done? So we're not going to go into that today. But but it your demand Forecasting and the speed of which you have to adapt to this has tentacles throughout the whole supply chain.

Ellen Miner [00:18:16]:

Yeah, I think Kerry just set up part two for us, I think.

Kerry Fogarty [00:18:20]:

Yeah, yeah.

Scott W. Luton [00:18:20]:

Definitely. And just I want to call one thing out and get. Karin, get your take on what we heard there from both Ellen and Kerry. But velocity, oh, gosh, the speed which everything is moving, including the North Star, which is what customers want. Those expectations are evolving, of course. Karin, what'd you hear there from Ellen and Kerry on challenges?

Karin Bursa [00:18:42]:

Yeah, I heard this is going to be now a mini seminar. We're going to go all afternoon. Right. Because there's so much to talk about here it is. I love the focus on transforming that data. And when I think about some of those challenges, we always talk about the time value of money. I want to start talking about the time value of data because it's not just unleashing that data by getting the most current read on the market. So whether that means bringing in your point of sale or your E Com data, your sell through information so you can expedite replenishment, there's just huge opportunities to create a more efficient experience and a more profitable experience in the fashion industry.

Scott W. Luton [00:19:25]:

Excellent point. And the drive sustainable, really big traction and new gains when it comes to sustainability. Excellent points, Karin. Okay, let's get into the first big trend. So our topic today, key trends shaping the future of fashion, retail forecasting and demand planning. So like many other industries, this won't surprise anybody. We're seeing business leaders in the fashion industry leveraging artificial intelligence and machine learning. Right.

Scott W. Luton [00:19:51]:

In fact, as we're going to be learning here from Ellen, Kerry and Karin as well, artificial intelligence, machine learning are becoming increasingly central to forecasting and demand planning in fashion retail, extending well beyond just the data analytics. So Ellen, tell us more if you would.

Ellen Miner [00:20:09]:

Yeah, absolutely. So disruptions can happen on a moment's notice. We all know this, we've all lived this. And planners and supply chain executives need to be flexible and often have to change strategies on the turn of the dime. So they're using AI and ML to help harness the power of that data. The challenge that we are all facing right now is how do you do that in such a complex environment? So, but what is particularly exciting about this is that craners are going to become more strategic versus just number crunching because in the past you had, and I mentioned this before with the silos. But even in the fear of having so much data that without the ability to consolidate it and provide actionable results and actionable strategy how do you work with this data and do you have the right people on your team to do that? But AI and ML data, data, data that it is so critical to helping us amass data everywhere.

Scott W. Luton [00:21:29]:

That's right, Ellen, really quick. First off, they're on to you. I heard the good police folks behind you, I think they're. They're coming to get you, Ellen. Coming to get you. And then secondly, more seriously, actionable, actionable, actionable. You know, you can have all the data in the world, but if you don't have the insights and observations that drive better decision making and actions and wins and outcomes for the business, what do you have? Karin, quick comment. What we heard here from Ellen before we go to Kerry.

Karin Bursa [00:21:57]:

Yeah, Ellen, you said something like, how do you do that in a complex environment? My question is, how can you run a complex business and not leverage artificial intelligence? You can't throw enough talent at it that it's sustainable over time without effectively leveraging technology.

Ellen Miner [00:22:16]:

Oh, you're absolutely right. And along with that are what, what do you do if you are a smaller company and you don't have the resources or the budget to start exploring these big implementations? The truth is, and Kerry's going to talk more about this and he and I have been battling batting this around. Not battling, we don't battle batting this around, is that there are ways that you can do this without huge implementations. You could do it in bite sized pieces or open source technologies. The most important thing that you can do today is data attributing and making sure that your organization is looking at data as a true initiative, although for the value.

Scott W. Luton [00:23:05]:

Excellent points. We're going to dive deeper into all things data here in just a minute. We're shooting through this masterclass quick going back to AI and machine learning and how that's being used and how to Karin's point, how it's got to be used because we can't throw enough human talent at the challenges that we're faced with. Kerry, your thoughts?

Kerry Fogarty [00:23:24]:

Yeah. So a couple of things. Maybe I'll hit some stats first. I got some information off the Internet. So if it's on the Internet, it's gotta be true, right? So, but in a recent published article from the Business of Fashion, right, that's done with McKinsey, they had a stat that said 73% of fashion executives plan to prioritize generative AI, which is a little bit different in its schema of taxonomy of AI stuff. But that kind of shows you just the speed at which AI and types of AI are being adopted within the industry. Karin even go back and to the lengthy duration of a lifecycle of a product. Boston Consulting Group had published an article that said the average times between beginning to getting on the floor is anywhere from 37 to 45 weeks.

Kerry Fogarty [00:24:12]:

So that's, I mean wicked said that's unexpected. But it's crazy, right? That's, you know, it is. Things vary, right? You see the folks like Shields and Sarah, that right. Have a much different scalability to turn your product faster. But here's when I, when I mentioned things with the inventory optimization, a stat that came out also is that US retailers had about $740 billion in unsold goods in 2023. Now that isn't just fashion, that's obviously a variety of things. But it goes back to the thing Mark, how the hell did you have that much unsold inventory? So it goes back down to how accurate is your planning and forecasting across the board. And then just to give you an aspect of how AI just is just so incredible is that it analyzes about 3 million social media images on a given day to analyze hopefully in an unbiased market interpretation.

Kerry Fogarty [00:25:07]:

So it's incredible what this can do. So it's an element of data, but the AI brings the elements of interpreting designs that are just based on imagery. So it's just, it's crazy. When we talked about when we looked at how long it took the Internet to evolve and mature, it's AI is just across the board. But then specifically when we talk about, you know, in the fashion industry here again going back to the accuracy of predicting consumer preferences. So when you take point of sales data, you take your supply chain information, you take your social media information, you have to bring this all together in a very cohesive form, vast volumes of data and then be able to interpret it a hell of a lot faster than it used to be done by humans. The production and the accuracy to help demand players get this is all based on this element of data automation, the ability to automate this. We can process millions and millions of transactions in minutes, which may used to take weeks when you're looking at the coding, the product, attributing all that.

Kerry Fogarty [00:26:09]:

So the ingestion of this data into these machine learning tools and algorithms is incredibly fast. When you talk about right within fashion style, color, dimension, size. Back in the day when I was with a former company, they actually did production in country, so to speak, and then had issues and there were small batches and they had lots and the colors were off and so Then you went into shading and lot management. Now, that may be a little bit lesser, but when you look at the complexity of a product in a fashion industry, style, color, dimension, size, fabrications, right? Whether Ren Yuan mentioned it, whether it was fashion replenishment or an ongoing type product, how does this all melt together? So AI is able to bring all this data and rifle through it, bring out predictions, forecast, and then one thing I won't talk about when we get ready to get onto our next topic and elements of what even our product is doing, is that as AI evolves and all these learning models and tools are behind the scenes humans, unless you're a data scientist, you may not know actually how the hell it does this. So the term explainable AI comes into the thing to say, if I'm a demand player and I'm going through this, and Ellen will talk about the science versus the art, and okay, here part really comes along, and now you're spitting out all these predictions in a nice data in or graphical form, and I'll be like, how the hell did you come to this? So even explainable AI is pretty well when it comes to the use.

Scott W. Luton [00:27:37]:

Kerry and Ellen. Goodness, Grace, Karin, I need a nuclear physicist to figure all this out, and you're not one, Karin, but you're close.

Ellen Miner [00:27:46]:

We know.

Karin Bursa [00:27:46]:

I love it. I love this. Just so you know, this is. This is awesome. But when Kerry was talking about some of the different kinds of data, you know, in two broad buckets, we're talking about structured and unstructured and the ability for AI to use that imagery or to pull in sentiment data from social channels, that is like liquid gold, because that is going to add color and texture to the plan. And it may also direct inventory to specific regions where influencers are driving the desire for certain colors or styles or specific items. But the other thing that Kerry mentioned, and he said it really quickly, and if you're not in the fashion or apparel sector, you may not have picked up on this, but style, color, size, dimension, these things make apparel even harder because we have to have a quantity, often a vendor minimum quantity that gets sourced for each of those dimensions. So even if you think of shoes, right, where shoes have a.

Karin Bursa [00:28:56]:

A gender, a style, a gender, a size, they may have a width associated with them.

Kerry Fogarty [00:29:02]:

Yeah, absolutely.

Karin Bursa [00:29:02]:

All of that complexity comes in. So we're back to why is fashion so hard? It's hard because humans are shaped differently and they want products that fit. But it makes what's tough already demand planning and forecasting even more difficult. As we look at regional needs, believe it or not, people are different sizes in different regions, right, Ellen?

Ellen Miner [00:29:27]:

Yeah, absolutely. And this is something that we have been, we've been grappling with for years. And when you talk about sizes, the quick, funny story is that at one point in my career I was asked to be responsible for accessories. And I was so excited that I didn't have to do size analysis. No. Because doesn't matter. They have one size. So I thought, well, that's one thing I don't have to do.

Kerry Fogarty [00:29:52]:

So that was 18 chain, the 24 inch chain.

Ellen Miner [00:29:57]:

But I mean, there were other things, but size was off the table. But yes, the number of dimensions and the easy to get caught up in that analysis paralysis. So what I think Lei and ML are going to help us do is rise above that.

Scott W. Luton [00:30:14]:

Yes.

Ellen Miner [00:30:15]:

And I think all of us are very, very excited to see what that's going to look like in the future and how we can help fashion companies because the trends are moving so fast, how we can help them pivot more quickly.

Scott W. Luton [00:30:31]:

Yes. Okay. I just want to add as, as Ellen and Karin both were kind of talking about all those different options, I thought of the word permutations, which scared the heck out of me. Way back in Math class with two Fs, Kerry mentioned millions of social media images per day. And Karin, while it's not fashion. We've talked about this before. We had an interview with a manufacturer that is analyzing trillions of data records per day. And the only way you can do that, the only way is leveraging technology.

Scott W. Luton [00:31:01]:

Right. Okay, so Ellen, Kerry and Clint, I'm.

Kerry Fogarty [00:31:06]:

Going to hit through my one of my stats. Sure. So currently the fashion industry generates 2.5. I don't even know if I can pronounce this correctly. Quadrillion bytes of data every single day.

Scott W. Luton [00:31:18]:

Wow.

Karin Bursa [00:31:18]:

Oh, my gosh.

Kerry Fogarty [00:31:19]:

Then according to a report from IDC is by 2026, just not too far away from that, the projected amount of data generated by the fashion industry, or she's banking in healthcare industries.

Scott W. Luton [00:31:32]:

Goodness gracious.

Kerry Fogarty [00:31:34]:

Because you look at, you look at the TikToks, the social medias, and just the element of structured data, unstructured data and imagery.

Scott W. Luton [00:31:41]:

Yeah. And all of that, that influences like what all you all were talking about earlier, the fashion world, which is so incredibly and uniquely challenging in many ways. Okay, we got to switch over to something we've already talked about, but I want to take a little deeper dive. Data, data, data. Because there's an ever increasing need and dependence on more reliable and fault Tolerant data integration from that wide array of data sources that I think all three of y'all have touched on at least. So Kerry, let's start with you. Speak to data data integration and some of the trends and requirements that we're seeing here today and moving into the future.

Kerry Fogarty [00:32:18]:

Sure. So it's, you know, something that they had mentioned, I'm not sure. But data, obviously it may be a cliche at this point is the new oil. Right. It is so valuable in its or aggregation, adoption, evaluation and usage. So when we look at that, all this has introduced a variety of data types that may not cohese into something common when we talk about things like traditional edi. Even with edi, based on the templates of how data is structured and transmitted from training partners, it can vary, call it almost like a dialect. So the ability to ingest this from a variety of these different sources, have the mechanism to analyze it and then not just analyze it, but then give the trust or the capability of the consumer, say being a domain planner, to know can I trust this data? So I'll give the example right.

Kerry Fogarty [00:33:12]:

Even if we're doing polling from point of sale stores, what happens if you didn't polling 1% of your stores or 5% of your stores or 10% of your stores. So you now have an incomplete data set that someone needs to be aware of so that it either may allow them to continue or not continue analyzing data in a demand planning function. So it's the element of the ingestion of this vast amount of diverse data types, the ability to analyze and bring it all together too is then also give a picture of whether or not this data is accurate for somebody to consume and use in their planning function. I'd have to say that's one critical piece of the puzzle. So the ability now, right, and Ellen had mentioned it, product attributing consistency processes to do that. How can some of that be automated? Taking something that may be manually done, but also then automated so that the AI itself is filling in pieces of the blanks in order for that data to become consumable.

Scott W. Luton [00:34:09]:

So you know, trust, trust, trust. I love how that word keeps coming up in all of our conversations, Karin. Because if we don't trust our systems, our data, our decisions and a whole bunch more things getting, we get in trouble in a hurry. Karin, quick comment on what Kerry shared and I'm gonna switch over to Ellen.

Karin Bursa [00:34:28]:

I couldn't agree more. And that data is the new oil for business. And that AI is the only way to activate that oil really to drive our business and to accelerate that decision making. My final point would be something that Kerry mentioned just in passing, and that is spreadsheets. We have got to get our planning team out of spreadsheets. We've got to stop plugging our process holes with those spreadsheets because we can't automate. It is going to hinder every opportunity for automation.

Scott W. Luton [00:34:58]:

Excellent point. Because the way to garner alignment and trust is not through 37 different spreadsheets. Excellent point, Karin. All right, so, Ellen, data, data, data. I can't wait.

Ellen Miner [00:35:10]:

I want to jump on something you said which is trust. So trust. You can tell I have a special interest in organizations, which is organizational. Trust is critical, especially when we consolidate all of our channels into one. You have leaders of all of them. Everybody is going to have their own opinion. It is critical that we have trust across these silos as we integrate into one organization. Not easy.

Ellen Miner [00:35:41]:

Easy. It's easier said than done. The other thing, discipline, spreadsheets. We love them, we hate them, we lead them. I had worked through more system implementations where the work was done on the spreadsheet and then implemented into the new system. That cannot happen. And that goes back to discipline. So what I have often dealt with in organizations is this challenge where we are implementing, while we're doing the work, changing the tires on the tractor trailer as it's going down the highway.

Ellen Miner [00:36:19]:

Right. So how do we enable our teams to take the time to learn the new system while they're currently running the business? Another easier said than done. So that can be a good plug for consultants. But I think that it's. It's also cultural and starts at the top.

Scott W. Luton [00:36:37]:

That's right. You know, I was driving down to 85 and I saw just that happening. Ellen, the truck driver changing tires as they were driving down at 100 miles an hour. It's amazing what we do in supply chain. All right, Karin, I bet you love what we heard there from Ellen. Your thoughts?

Karin Bursa [00:36:50]:

I did, Absolutely. I am. That this trust and confidence, the reason it is so important is because we are asking them to replace inventory with AI driven insights. Right. With data. We want to do that so we're getting greater precision. And that can be scary because they think I can't ship that product or are you sure that's all I need? Or do we need more? Because this particular item is going to take off like wildfire. And that's where that trust and confidence and breaking down some of these barriers come into play.

Scott W. Luton [00:37:26]:

Excellent point, Karin. Especially after the pandemic, getting folks to Move from just encased back to just in time, where there's massive gains to be had. It's very difficult.

Ellen Miner [00:37:35]:

You almost have to have a flow here for AI, which is what Something Kerry and I have been talking about, scenario planning. So anticipating the what could be coming down the pipe. And that is impossible to do if you're doing everything manually.

Scott W. Luton [00:37:52]:

Yeah, excellent point, Ellen. And this is where we would go next. And by the way, we forgot to mention, folks, I bet Kerry's got some musical bones in him, but he's not related to John 30 with CCR. Just heads up. Just heads up.

Kerry Fogarty [00:38:06]:

And the rumor is on the eighth Beetle. But let me. That's just a. That's just a rumor.

Scott W. Luton [00:38:12]:

There's a supply chain orchestration joke somewhere. I can't quite find it. All right, so Kerry, Ellen, and Karin, what I want to get to is giving some really good, actionable advice to our audience. We've laid out so much on the table, and y'all are. All three of you are such a wealth of been there, done that expertise to help not just fashion retail leaders get through these challenging times, current disruption, and what's around the corner. But really, there's so many universal lessons here, I think. So what I want to do is get you all to speak to the art of the possible that continues to evolve. Given all these massive opportunities for real new outcomes and innovations, what actions would you suggest that fashion retail leaders take? And Ellen, I want to start with you.

Ellen Miner [00:38:57]:

Okay. And I love that expression, art of the possible. I think that that is. That's where it starts. It's the dreaming, it's the envisioning. And especially in. We can't lose sight of the fact that in the fashion apparel space, in the retail space, in the wholesale space, we are a fashion industry. We don't make widgets.

Ellen Miner [00:39:21]:

And I grew up in this industry being told that back in the. I won't mention the decade, but back when I started learning about this business. We cannot lose sight of that. Hence the art versus the science. So if I was currently a business leader, I would absolutely get my colleagues together, we would envision where we believe we should be. And what are some bites size peafoods we could take because it's so overwhelming to think about a huge transformation. But there are things we could do today, such as the attributing your data better that I mentioned earlier, or just looking at your organizational structure, doing some research to see what's out there from an open AI standpoint, as well as bring some partners in just to pick around some ideas a little commercial for partner lake just have them share their knowledge with you with for ideas. You know there are things that you can do today even if you don't have the big capex budget LS that's.

Scott W. Luton [00:40:29]:

A great point because oftentimes with problems big and small, we don't have the expertise inside the proverbial four walls. And it's important if at least having the conversations with potential partners or experts who are out there solving a bunch of problems for a variety of industries. There's a lot to be gained there.

Ellen Miner [00:40:48]:

Absolutely.

Scott W. Luton [00:40:48]:

So Kerry, same question. What was some actual advice you'd like to offer up in light of all a lot of these trends and challenges. Yeah. Possibilities.

Kerry Fogarty [00:40:58]:

So maybe I'll raise it and break it down in a couple of key points here.

Karin Bursa [00:41:03]:

Okay.

Kerry Fogarty [00:41:03]:

One is obviously being Mr. Obvious right. Assess your organizations. I want to mention the mission, the objective near long term goals even in the dialogue of this is staffing capabilities and then the technology platform itself. But I would say start with a clear data strategy, establish that align with those what that may be and that includes the integration. I think there was a comment from somebody just on data and the integration. So look at that overall in its ecosystem across anywhere data is coming from look and try to bring a foster a data driven culture in the organization. So it's taking the element of the art and the human aspects of it, but meshing it obviously with the data driven culture itself.

Kerry Fogarty [00:41:45]:

Things like process, right. The data management look at and reviewing how the processes in the organization review data in its entirety from a technology standpoint, right. There's large scale budgets, small scale budgets but whatever you do, you need to look at something that has scalability. Especially if you're a company that's coring brands not only just growing organically, acquiring brands, going international. You then have to look at the scalability and the natives to bring on across the board. And then you know, Ellen had mentioned it, right. Things like the collaboration across department demand planning isn't in its own little silo of ecosystem. It's collaboration across every team that operates that comprises the supply chain across the board.

Kerry Fogarty [00:42:28]:

And then an element of like when you're taking you on this data from a technology perspective which we do is that we implement where we have the data security measures on it itself. Right. Data is flying around. How do you make sure you know you're not taking data that isn't shouldn't be there? And certainly even in your human region, right. There's much more tighter controls what's going across the pond as far as what data is there. So it's, it's, it's fundamentally broken down into some common building blocks. Right. Start with your strategy.

Kerry Fogarty [00:42:53]:

Look at building a culture that's data driven. Bring those items of collaboration across department structure and processes would be my starting points.

Scott W. Luton [00:43:04]:

I love it. Ellen and Kerry, goodness gracious, quite the one, two punch. Karin, what did you hear there? What you what do our audience members, smartest ones around the globe, need to make sure they focus in on?

Karin Bursa [00:43:17]:

Yeah, I think there are a lot of good pearls of wisdom there. I think this, the, the points that have been made about data, not just structured data, but unstructured data, especially in the fashion sector where the visual elements are so important. So being able to harness that, not to stifle creativity but to inspire it. So where Ellen talked about both the art and the science, the desire is not to take the art away, it's to inspire the art in the direction that the consumer is interested in or most interested in at this particular time so that you've got that inspirational element to your collection. And I just think it's really exciting. You can't do it without harnessing artificial intelligence. You just can't find the signal inside of these massive data streams fast enough to do something about it.

Scott W. Luton [00:44:12]:

Excellent point, Karin. Excellent point. The biggest magnifying glass is not the tool you want to be using to your point. So I hate to wrap this conversation. I wish we had time for that five hour conversation you had. Kerry. We'll have to have both. Let's see here.

Scott W. Luton [00:44:28]:

But let's make sure how our audience knows how to continue the dialogue with both of you all. And Ellen, we'll start with you. How can folks connect with you? Ellen?

Ellen Miner [00:44:37]:

Okay, I am on LinkedIn. I'm just in the process of building a website but Ellen Meiner right on LinkedIn and I have been highlighted in all of the Supply Chain Now posts. So you can just click on that and you will find me and I hope you do.

Scott W. Luton [00:44:54]:

I do too. I do too. It's been an absolute pleasure talking with all three of y'all. Of course I've known Karin forever and I expect that what I learned from her. But Ellen, Kerry, the pre show conversation folks, you're seeing exactly the same behind the camera, in front of the camera sidebar conversations. Wonderful, wonderful fountains of knowledge and good, great people. So connect with Ellen and Kerry Fogarty. How can folks connect with you? Kerry?

Kerry Fogarty [00:45:17]:

Yeah, sure. So connect through my business email - kerry.fogarty@PartnerLinQ.com and PartnerLinQ is spelled with a little unique twist. It's the last letter is a Q, not a K. And it shows the link within the supply chain. So a little play on the terminology there. So that would be the best way. And I'm on LinkedIn too.

Kerry Fogarty [00:45:41]:

But if you did John Fogarty versus Kerry Fogarty, then you know that you gotta do a different search. I don't know if John Fogarty's actually there.

Scott W. Luton [00:45:48]:

Yeah, John Fogarty, LinkedIn. You're really teaching some things. You know, one last point. I was trying to find this earlier, but I just want to call out one more time. It was on my seven pages of notes here that explainable AI. You know, what's old is new again. The power of communication. Especially as we're moving faster, as we're got a mix of all sorts of different learners and leaders and professionals in the workforce.

Scott W. Luton [00:46:14]:

You would think intuitively that communication has gotten easier. I would argue that it's gotten much more difficult. And I think that is an important bridge and element to a lot of the change that all three of y'all have been speaking to here today. So leave no one behind. Okay, so we're gonna get Karin's patent key takeaway in just a second. I want to share resources, folks. Y'all know we love shared resources here to help you on your journey, check out this neat recent white paper from Kerry and the PartnerLinQ team. PartnerLinQ with a Q.

Scott W. Luton [00:46:43]:

The role of composability in the supply chain. This is something Kerry touched on earlier. So how can your business not only survive all the current and future disruption because you know it's going to keep coming, but emerge stronger. The answer lies in composability, A game changing approach that enables your supply chain to be agile, responsive and resilient. Good stuff. And we dropped the link to that white paper right here. You're one click away. And we want to help make y'all get y'all connected to great resources.

Scott W. Luton [00:47:12]:

Ellen's dropping that book, the Arthur C. Brooks from Strength to Strength. Love that. And we encourage y'all to connect with Ellen and Kerry and keep the dialogue going. Okay, Karin, I knew this was going to be home run stuff. By assembling the three of y'all, we need the fourth. We'd have the supply chain Beatles, but we'll work on that later. Karin, what's your favorite key takeaway from today's big, big conversation?

Karin Bursa [00:47:37]:

I just think there is tremendous untapped potential in the industry as a whole. But these examples that Kerry and Ellen have provided are so tangible and they've given us some steps that we can take without like eating the whole elephant. Right. Get started.

Kerry Fogarty [00:47:51]:

Exactly.

Karin Bursa [00:47:52]:

Get your arms around some of that data now. Think about both structured and unstructured data. Leveraging cloud based solutions are going to accelerate that insight. So just a number of things I think that small companies and large companies.

Scott W. Luton [00:48:08]:

Can take advantage of completely 1000%. I'm illustrating my ineptitude. It comes to math. Wholeheartedly agree with you, Karin. And it starts with taking the first step and having a different conversation. And I know Ellen and Kerry and Karin welcome those conversations. So reach out and make that connection. Folks, I hate to wrap up here today, but I want to thank, of course, Ellen Meiner, founder principal with Ellen Meiner Consulting.

Scott W. Luton [00:48:35]:

Ellen, thanks so much for being here.

Ellen Miner [00:48:37]:

Thank you for having me. This was enlightening and really fun. So thank you.

Scott W. Luton [00:48:42]:

I agree with you as well. Thanks for being here. Kerry Fogarty, Senior Vice President, Client Relations with PartnerLinQ. Kerry, thanks for being here, my friend.

Kerry Fogarty [00:48:49]:

You're welcome, Scott and Karin. And when do I expect my $500 Amazon gift card to.

Scott W. Luton [00:48:55]:

It's coming soon.

Kerry Fogarty [00:48:56]:

It's coming soon. I'm only horsing around. I'm only dealing around.

Scott W. Luton [00:49:02]:

Oh, I saw what you did there. All right, Karin, we might be cousins, Kerry and I might be cousins, but Karin Bursa, always a pleasure. Really appreciate you being here as always. And folks, connect, follow, you name it with Karin Bursa on LinkedIn. But thank you for being here, Karin.

Karin Bursa [00:49:18]:

Thank you. I enjoyed it. It was a lot of fun.

Scott W. Luton [00:49:20]:

I did too. All right, so folks, we are dropping all the links, including you can check out PartnerLinQ there. I mentioned the white paper that we talked about on composability. You can even learn more about Supply Chain Now and all the different programming we have. Check that out. But whatever you do, here's the homework. Very actionable episode here today with Kerry, Ellen and Karin. You gotta take one thing, let's keep it simple, one thing and take it back.

Scott W. Luton [00:49:46]:

Sit down and have a different conversation with your teams. There's an immense opportunity to change how business is done, making it easier on the teams while leveraging this new technology is changing global supply chain fashion, global business. But it starts with that first step. So on behalf of the whole team here at Supply Chain Now, Scott Luton, challenging you do good, get forward, be the change that's needed and we'll see you next time right back here at Supply Chain Now. Thanks everybody.

Narrator [00:50:12]:

Thanks for being a part of our Supply Chain Now community. Check out all of our programming at supplychainnow.com and make sure you subscribe to Supply Chain Now anywhere you listen to podcasts and Follow us on Facebook, LinkedIn, Twitter and Instagram. See you next time on Supply Chain Now.