Engaging Deeper & Scaling smarter with Andy Laudato

[Music] Hello and welcome to the Engaging Deeper and Scaling Smarter Podcast series brought to you by Fujitsu. I'm Brian Ameral, CEO of Planetricity and the Host of Today's Podcast. Today's guest is Andy Ladato, who I've had the pleasure of knowing for many years. He is EVP and Chief Operating Officer of the Vitamin Shop and a seasoned and mean truly seasoned retail and technology executive thought leader with deep experience leading complex and a price scale operations. He also co-founded and chairs the retail AI council helping guide our industry's adoption of artificial intelligence. Andy began his career in technology leadership building and transforming retail organizations before stepping into broader executive roles that span operations digital and strategy. That dual lens of technology and operations gives him a unique perspective on how retailers actually scale innovation inside real world constraints inside of what's happening today in retail. He is also the author of a book called Fostering, oops backwards but there it is, Fostering Innovation, how to build an amazing IT team where he shares practical insights on cultivating culture, leadership discipline, and innovation within large organizations. I think his people first leadership approach makes this book a must read, but not just IT people, but for every retail leader to really understand what is happening at that side of the organization. He is passionate about leadership and innovation which you're going to hear today, but he also speaks quite frequently at industry events and is recognized for his candid perspectives on what truly works, what doesn't, and then how to get navigate change inside of an organization. So let's welcome a true luminary in our industry. I know I'm very excited to have him on this series so hello Andy. Hey Brian thank you and that was a great intro. I'm glad we were recording this. You can use it for whatever you need. Alright so you know Andy I wanted to start really, I mean you've had a unique path right and you have these deep technology roots you're very tied into the entire operational, the public traded company, you're doing some great things. How has that journey shaped the way you think about leadership and running a retail organization scale? Yeah I'm going to go way back to the very beginning of my career. So I went to college to be a computer programmer. I was all in on the nerd and I used to say I was a nerd before it was popular being nerd right now at Navy Spitz. It's kind of cool to be a nerd which I really love. Back then not so much, but I had two job offers out of college. One was at a limited which is now called L Brands. It's a big retail, tarot and the other job offer was at a bank. But the bank offered me $1,000 more a year so I decided logically just to go work at the bank. However my father said to me you know you got to think more than about a thousand dollars. You got to think about long term in your career and use the bank sounds kind of stodgy and he goes I bet you'd have more fun if that woman's clothing company and so honestly I had no thought of myself as a retailer or a banker and it's sure person. I was just a computer nerd. When I listened to my dad and I took that job at the limited and I'm so happy that but that's my first step into retail was taking that job. A couple years into it they came around and said hey we're starting this new company and it's going to be like a startup inside this big organization and we need someone to lead the project to get it ramped up. Not too many people were that interested. They were kind of like well because it was going to be a big job in a lot of hours but I was like me me me and that company is called Bath & Body Works which is now what are they an eight billion dollar juggernaut. Right. So that was like 27 years old I want to tell you how little I was making but it was so much fun. It was a very small group and I got to meet every day with the CEO and the CFO and we go to late dinners enough to work in nights and days and weekends just starting up this company. We did it by spinning it off of another retailer called Express which is still around. Took all their systems and the processes right and stood up our own version of it. So that moment in my career really really young and really early I flipped from being a technologist that worked in retail to truly being a retailer. It happened to be a technology person and had that not happen I don't think that the rest of my career would have happened because my whole mindset shifted. From there on out yes I'm a tech expert but I don't lead with that I lead with I'm a retailer because that's my true passion is retail and I just happened to know technology and now obviously supply chain and operations and P&Ls and all the fun things that go with running a successful retail. Yeah you know that's an interesting place to start your career and to get that kind of perspective early on because to your point a lot of people that come in from a technology perspective end up getting pigeonholed and don't really think about the broader problem. I'm even building software companies. It's hard to find people to get that broader perspective right both sides of it and you want to partner with people to do. In terms of kind of your overall philosophy on management we're going to be talking a little bit more of that but whether any management lessons at the very beginning that you learned that would be interesting to share right now. There's a couple things one is actually kind of happening again so one of the things I like to say is let's not solve tech problems with business. Yeah and the idea is like oh it's the cloud how can we use this at our business or no it's mobile it's not like that and it's like someone has a new new programming language like oh all the rage is Python no we're all coming to play Python and I kind of thought we'd gotten away from this but it's all happening again with AR. Yep. Everybody's trying to say how can I put AI into my business and it's a hundred percent backwards backwards you need to say what I'm glad to hear you say that Andy you have no idea because I've been making the same statement they people aren't looking at the problem and then how can what technology solve it they're looking at the technology and saying where can we go put this. I mean through micro people say which your mobile strategy and only I don't have one I have a some more vitamin strategy that will use mobile right we have a very successful app which are cloud strategy I don't have one I have a so more vitamin strategy that we rely heavily on the cloud and SaaS and you know all day long every day and it's the same thing with AI you know I don't have an AI strategy or say I mean we're having an approach to it in the comment but it's really about selling more vitamins and we're going to use AI to the fullest to get that done. Yep. Okay great. Well that's number one the number the second thing is no matter what job you have IT supply chain operations e-commerce digital marketing these are all people jobs 100% every day all day you know the work that gets done under me the people that work for me I can't do most of it or maybe arguably any of it right I just can't write computer programs anymore or you know working the warehouse I'd get I'd be you know I had to stand up my feed eight hours a day helping boxers who knows where I'm not but yep so you learn that as you move up is become a leader in a lot of first-time managers they really struggle stepping out of that hands on yep you know you'll hear I can do it faster myself I can do it better myself but you can't scale yourself right even if you're twice as fast you get four people they're going to be four times faster so that's the big leadership lesson is you got to be all about people no matter what the job is and get the right people and trust them to do the best job yeah that's one of the things I know you talk a lot about in your book is really you know but identifying the kinds of character traits that that make great people we can't go into that in a whole lot of depth today but but there's some some great stuff there that I felt you articulated and encapsulated really really well what do I want to switch a little bit here and kind of talk a little bit about scaling smarter you know this this podcast series is engaging deeper and scaling smarter and when we use that phrase you know just kind of thinking like look for an operator standpoint what do you think that actually mean and how is that different than just kind of growing a business how do you think about scaling yeah and then retail you think about hundreds or you know we have right now the vitamin shop 650 stores other people have thousands or tens of thousands so you know someone brought me their computer defects I could probably do it pretty easily but to try to do all that remotely or make sure it doesn't you know it's a whole different ballgame right one of my things and I got a million things you only have one chance to do it the right way so I think one of the mistake people make is they'll slap something together for a prototype but then they try to roll it out and it crumbles under the pressure whether it's performance the other thing is just use the phrase happy path grumpy path we just deployed at the vitamin shop same day delivery so you order on vitamin shop calm and it'll get delivered via door dash to your home you know later that day and it's pretty easy to do this when it all works properly the customer orders and it's in stock at the store the store picks the order puts in the bag the door dash api's work and they get the order the person shows up and they drop it off in the person's home right so that's not hard and you can say oh we can probably build that in weeks but every one of those steps and phases could have a hiccup right my website could have a problem right order management or the api's or the store really says it's in stock and it's not or door dash is you know on and on and on and every one of those grumpy paths have to have messages and emails so you don't frustrate your customer right right if something goes wrong oh there's a problem with your order we'll deliver tomorrow or give you a substitute item that's what takes the time on these scale projects, dealing with the exceptions, and really doing your best job up front to identify the exceptions, so you don't get into production and have these things occur and start making people angry. So really understanding that the happy path is the easy path, but spending the effort energy to not only design around that rumpy path, but to test every one of those scenarios. Right. Right. Yeah, it's the vision of something building a prototype to the vision is the easy part. I used to call it the difference between the white paper and reality. We have an idea of what you want to do. You can tell that story beautifully, but when you actually put it into production, I don't think people, a lot of people that are consumers have any idea of how complex it is to deal with just even just that that same day delivery problem that what really goes on in the background, all the areas where they can be failure around that, how you create ways to capture, you know, the problems before the customer sees the problem, right? You know, they being able to build that and of course customer experience is always built around doing good job serving those customers. Yeah, we're part of the business tends to break first in your opinion. When when where do you see when you increase complexity, do you have any thoughts about that? I know it's kind of an abstract question, but it's it just seems like something you've probably thought of. Well, if we're going to get specific in the Omni channel retailing, you know, we want to sell we want to sell we want our customers build a shop where, when and how they prefer it. Right. It could be in my store, it could be on Amazon, my website, pick up them. We get shop on Instacart by the Meshop products, right? So all of these things really break down with inventory, accurate inventory. Yep. I look at. And you know, a lot of people try to solve it with RFID, but every product doesn't make sense for RFID, now computer vision. But we're promising inventory in real time to all these different channels and all these different people. I once wrote a paper called 15 ways inventory goes awry. Because there are a lot of different ways that, you know, your inventory gets out of whack. So I'm sure you can come up with more than that now, if you actually took pendant. Yeah, let me tell a quick story. So when I bought my first home, it was in Ohio, and I wanted to put my last name on the mailbox. So I went to big box. And I bought the letters and I get to check out in the the cashier rang the first letter to the L and hit the seven button. And I go, Oh, hey, stop, stop. Like, well, you got to ring you, you got to scan each one of these letters separately. She was, what are you talking about? I go, well, you're going to get back seven Ls. But I bought two A's in the U and a D, you know, a lot, like, got to choose, it's okay. The price is the same. I go, no, it's, it's not okay. It's just getting anger with me, right? And she's like, why do you care? Like, what is, what is this to you? And I go, it's people like you that ruined my life. I'm back at the office dealing with this stuff. So yeah, that's one way goes awry. I mean, that happens. Right? Yeah. Yeah. No, the other joke is, you know, some say a little kid breaks something that's over, you know, vase or whatever. Sweeps it out of the rug. No one knows until six months later, you do a physical inventory. And that you're stepping a lot at pier one. And I have another joke. If you're going to steal from us, you know, we get it. But just tell us in the way out so we can replenish the inventory. If something is stolen again, the computer doesn't know, right? Right? That's true. That's true. You know, I think it's not selling. And then an algorithm would say, oh, let's not give any more that item to that store because they're not good at selling. Yeah. No, that's the great inside real real stories. Right? Yeah. Yeah. That's great. That could be the next thing I really wanted to say is it was talking a little bit more about the engagement side of things. And I know that you have to deal with with the full breadth of this often customer engagement is positioned as a marketing decision. But I think in reality, it's deeply operational, right? And you know, where does it become in your opinion, an operational challenge to do a great job with customer engagement? Yeah. So like all retailers, we like to survey our customers. There's lots of different ways to get feedback, whether it's product reviews or standing outside with a clipboard or putting technology in stores. But the first and foremost thing you got to think about is consumers vote with their wallets. So are they buying the product or not? And if they are not, why is the product not up to par? Is the price wrong? You know, what's going on? Did you not promote it? So I think the quantitative, you know, is this product selling at this price at the right rate that we have predicted or better such a simple metric, but so important. And that's what you start with. There's winners and losers product and there's winning and losing channels. And I think it was Ralph Waldo, Ed Mercen, that said, if you build a better mouse trap, they'll beat a path to your door. But we all learn to see this is cool. I don't think that's true anymore. No, there's lots of different doors, right? So I don't think that that's why I get back to yeah, we want to be where the customers are. Yeah, and make sure that it's convenient. Convenience comes up all the time, convenience, value. And that's a word we use a lot retail value. And I just consider value the intersection between quality and price. Yep. And that's really important to, but I also think that there's a component to value today that is simplicity or ease of transaction, you know, and when retailers, I mean, you guys do this, you take responsibility for the customer's satisfaction throughout that entire want it by it and use an experience. I mean, you guys are really good at that. As goes into value, trust. Yep. You know, and then you know, when you're talking a little bit earlier about all the complexity and consumers don't know if we do a great job, they'll never know. Right. Like when you do really good job is something you should look easy. Mm hmm. And like these Olympic athletes, it looks easy. Like, oh, I could ski down that hill. Yeah, but try real bad. And I look easy. Well, they did it. Yeah, yeah, that's true. I guess the question that was going to ask here is it as it relates to this is there are breakdowns that happen at the store. There are breakdowns that can happen through the online experience, you know, through mobile versus traditional e-commerce landing pages, you know, traditional pages. Where do you think? Well, I guess the question is, do you believe that they are unique problems across these different touch points? Or do you think that a breakdown in one generally is a breakdown across all the different channels? Well, let's start in the store. So, you know, it all starts with the air store associates. We call our store employees health enthusiasts. Uh-huh. As we tend to hire people that are passionate about health and wellness. And then we spend a lot of time, energy and money educating them. We actually have a gamification AI that play little games. One or two questions a day. And for each individual, it knows what they know what they don't know. So it's like, it's a commitment to education. And you know, retail store turnover is what it is. So it's not like you teach people once in your gun. It's always educating them in the industry changes. But for me personally, like there's certain products I would not. Be comfortable working for like I wouldn't work for a committed soul cigarettes. Right. Right. Personally, right. I care a lot about what I'm representing and selling. And that's why I really enjoy being in health and wellness. And I think that's really important in stores. If people are passionate at whether it's a peril. Or it's, you know, home furnishings or whatever it is. So it's a huge thing for us at the vitamin shop that are health enthusiasts in our stores are very passionate about the product. Yeah. So now that we get there and you know, they're going to have a great conversation with the customer about their needs, what they're looking for, what their options are. What's going to get in their way? Right. Are we bearing them with tasks? Are the things we send them? Are there inventory challenges or the system crashes or the network doesn't work? Or the truck is late? You know, all those things take away from the desire that we have knowledgeable, passionate health enthusiasts, you know, talking to customers about the customer needs. So you look at what I do as a CEO, it's cleaning up every one of those things and make sure that they all work. Yep. Yep. And do you spend a fair bit of time? I would assume getting feedback back from the stores around where they're finding their challenges. I mean, some retours down, but I'm guessing actually well, tonight either does that. So fun story. We are one of our regional leaders. His name is Jake and he was gathering feedback from stores on Sunday nights, about the fire week, spending his Sundays consolidating that and sending out a report every Monday. And he was time consuming and it was little biased, even Jake would admit that maybe he'd leave something out or emphasize something. And he can only talk to so many people. So right now, every other week, we send a survey, every one of our store managers, every other week, just a five question survey, they fill it out. Then we have an AI that we named Jake bot after Jake, the real person. And Jake bot summarizes what went well, what didn't do so well, what competition and what we can do for that store. So it's really exciting that it's always been difficult to get feedback. You know, from every single store, and now we haven't automated, not a lot of burden on their part. And the real Jake's really happy is that he's actually spending this time to get spend more time in the gym, right? So he's looking pretty slow. Now that's one thing we absolutely do is use that tool. I personally spend a lot of time in stores as do it does our entire exact team. Yep. Spend a lot of time in stores. We have a, you have to listen to right, you have to, I just actually read this warning. I saw a stat that I headquarters voted themselves 9.3 out of 10 of being in two with stores and storage voted five points. Yeah, that sounds about right. Yeah, as a huge mismatch, you know, yeah. And so as much as you can keep talking and to listen and do feedback. Yep. No, I think it's so important. You know, one of the things that I mean, as you know, I've done a lot of work directly with retailers where I go. out into the field around instur customer experience. And I invariably bring back information back to management. They had no idea. But the people, you know, what I find is the people that are interacting, particularly in an educated, kind of sales associate that you have, that really is passionate about the products, knows a lot about health and wellness, has a point of view on products and makes recommendations. And they're trained well, you know, but there's a lot that they learn and do that's almost, I guess I would say tribal knowledge, and not deeply understood by the rest of the organization. Being able to build that channel of communication between the people that are really at the front line engaging with customers all the way back to and having the organization making strategic investment decisions based on what they're learning from that touch point. I think AI, your point, the Jake, I don't know what the five questions are, but I'm assuming that they're surfacing the most important things that are going to move the needle the most inside your organization. But the more time I think that you did an organization can learn from the front line people that are engaging with customers, particularly in categories like yours, where there's so many outside forces that are influencing people's buying decisions, right? And, you know, trends and all kinds of things that are happening around health and wellness products, I would think that those people in the store are the ones that are the first to hear it. They capture those trends. Well, and we all sit around and retell and pick her over if we're going to call it Omni-Channel or Multichannel or integrated or hominized or seamless, you know, I would ever adjective we put on it, but it's not the web in the store in the call center, right? And these things are so integrated, and you really have to think about it being integrated. And one thing that I'm passionate about is, you're not going to be seamless to your customer if you're not seamless on the back end. And that means your technology, and it means your org structure. Right, so you gotta really think about aligning your org structure, your technology around that integrated commerce and not separate these things. Yep, yep, that's great. Not so much can see through it is kind of how I think of it. Yep, no, that's great. Yeah, you know, in your book, Foster Innovation, you talk about building teams that can innovate inside, the constraints, there's always natural constraints inside of every organization. What's the biggest misconception leaders have about innovation and large enterprises? Do you think, when you're out there talking to a lot of people in our industry, you're at a lot of trade shows, you're at a lot of councils, you're involved in a lot of things? Where do you think their biggest misconceptions are about innovation in large enterprises? I think that we'll run around and say, "Fail Fast," and it's great to fail, and we learn from failure. I hear that non-stop, but I don't see it in real life. I'd say, you know, it's my joke, you know, "Fail Fast," but not always, because in order to be willing to have failure, which means that you spent money, time, and resources on something that did not work. We put money, energy, we got excited, and we hyped it and it did not work. How do you get there? One, the people working on it have to trust that if it doesn't work, they're going to be OK. They're not going to lose their jobs or get a bad review, and we'll call that psychological safety. So, and how do you get that? You only get that if, how I say it, is your house is an orb. So, you earn the right to innovate when everything else is working, when the basics are working, when the emails are emailing, the waters are flowing, and all those things, and the networks performs, and you know, when you hit change, it gets the right amount. And that's not the exciting stuff everyone wants to innovate. Yep. I always think it's a huge mistake when companies separate innovation from day-to-day operations. Mm-hmm. Like, oh, let's take these five people and stick them in the lab, and they're going to come up with stuff. Yep. First of all, they're out of touch. How does that get integrated back? Back in, right. Third, you know, if people aren't owning it, they don't know, like, kind of what you said earlier, the realities of the day-to-day. So, I think earning the right to innovate is having your house in order, having your budget in order, getting your projects done on time and scope, and then you get to innovate. So-- And keeping costs under control for the keeping the lights on part of the business, right? I mean, you've got to-- Yeah. --other else, they're not going to be any budget to do anything innovative. Oh. And if you can do something cheaper than the budget, you can free up some money, maybe, and say, hey, a little bit of money. Or if you weren't trust, there's some innovation work. You could carve out some R&D funds. Yep. But ultimately, yeah. But if all the projects are late and over budget, and you go to the CFO, and go, oh, give me $x dollars to do innovation, if I get laughed at. Yeah. Yeah. Or yell back. But neither of those fun conversations. You were talking a little bit about the thought here around pilots of different things and trying different things out in-- in-sut-up organizations. Why do you think so many pilots look promising at the beginning, but never scale? I mean, is it back to some of those fundamentals? Or maybe you can share kind of your thoughts. You obviously have tried a lot of stuff, and it hasn't all hit the mainstream through your stores. A lot of times, people will pilot new things in their very best stores with their very best teams, and their very best leaders. Yep. And I go, we want to make it successful, but that doesn't scale. Because now you go to-- not your very best, more your average team. So I think it's important to try things in maybe a nice balance of support with a different level of 10-year leadership, customer. I think that's a big mistake I see people make. Unrealistic expectations. Another one of my favorite things to say is if you build it, they won't come. Just because you stick some new tech or process, what's the reason you had a start? Is that part of the law? Yeah, probably. I mean, think about how many websites there are. I don't even know. Millions, tens of millions of websites. So you know, you spin up a website. I have one. No, it comes to it. You know? Yeah. Yeah. It's got to be the message. And then sometimes the harsh reality of tech that works great in the lab. Customers are smart. I'll tell a story. It's old, but hard and something. I think within the first day, someone had kind of hacked it. And they're watching a baseball game on it. Or something. You know, they're pretty smart. Sometimes you put in a touchscreen and no one knows to touch it. You know, they're afraid to. We deployed touchscreen during COVID. That was a really bad idea. What? Well, that just-- you know, that pilot failed because of bad timing. Right. It was time to get people touching things. Yeah. Yeah. No, it's not. Touchless was actually very big at that point, if I remember correctly. But ultimately, I think it goes back to what we talked about earlier, not designing it to scale from the beginning. So when the rush to get something out there, it's really hard to go. Sorry. OK. This is great. Now go broadly, go to 1,000 stores, and it wasn't sized right or scoped right. So now you're showing off going, OK, I need X more dollars and X more months. And no one wants to hear it because they saw it working. I saw that working. Right. How can you tell me that, you know, to go from one store to a hundred is going to cost me a lot more money. So being really clear about that early on, it is really. Yeah. It's innovation harder technically or is it harder politically? Because I think that you can do the primary use case. You can prove that. But then getting the organization, the operational change, getting the decision makers in the organization to put the appropriate amount of capital and go from an idea to something that is truly hardened for a business like yours. There's both sides of that. Any advice in terms of how people should be moving from, hey, we just-- could be an AI project, right? We just tested this. We think we're getting some great value around this. For us to scale this, we think that this is what's going to be required. How should they navigate that inside of an organization? And what should they expect? First and foremost is start with why you're doing it. You know, back to-- oh, because everyone's doing AI or the board said to do AI or my cousin said AI, you know, but why are we doing it? How is this going to help our customer? Yep. So I would start with a customer and the why. And I think that's super important. And then define success upfront. What is success? So say you're building a shopping assistant to help the store employees have more data. How are you going to measure that? Is it sales? But you could say people use it up more sales. Is it more throughput? Is it just going to survey them? Is it turnover? I mean, all of these are valid. But if you don't decide upfront, then it's just going to become-- I thought this was greater. They liked it. I thought we'd get more from that. So-- and even if it changes, you may get more benefits than you thought in one area and listen to another. Start up front going, we're going to do this. This is going to help our customers. Here's why we're doing it. And here's how we're going to measure success. Yep. When I've done work in the past, I've always start with what I call a business impact model, where we actually look at if this was implemented. Where are the-- what are the levers that were being pulled? Where are we going to see movements in the KPIs that matter inside the organization? And if it happens at this frequency, so using your shopping assistant app, what are the use cases that they're going to be using it for? How contribution do each of those use cases have to margin or cost? Whatever it is, right? And then ultimately, you have that framework. Then when you do a pilot, you're measuring against the framework when you scale it out and doing change management. You're going, yes. And I think so few retailers really think about it from that perspective of really building a metrics-based approach to change inside their organization. So they know that if I do this, I should expect this. I tested that. It looks like that's true. And when I scale it, now let's make sure that those behaviors are being driven or those things are happening at the scale that we thought they were going to happen, therefore giving us these outcomes that can be mapped back to the cost. So you get your IRR and your ROI out of the back end of that. Absolutely. The other thing is the definition of innovation. I mean, we've done it a little. I do it because of my background. But innovation just isn't about technicality. technology. It could be a process, right? It could be boring things like, oh, we found a better way to unload the truck. Yeah, it's saving 10 minutes every time, but times two deliveries a week, time six hundred and stores, right? Or, you know, better way to put things on the shelf or take inventory down or even how to interact with customers. So, and back to what you asked about, communication. These people in the stores are innovating every day. They're out there. And there's some store doing something really, really well. Yep. You know, and I think that managing retail stores is a lot about managing and reducing variability. Mm-hmm. If every store got to the top in sales and an average order value and in conversion and a customer engagement, right? It really wouldn't really help. Yeah. I love, I love we're talking about stores so much because I think in this AI world, not getting talked about enough. Yeah. A lot of it's just the same. I don't know what the percentage is for you in terms of how much of your business is online sales versus in-store sales. I'm sure a lot of people are exploring products online that are coming into the stores. But share that number. Is that something that you guys talk about? We don't. But I will tell you that almost every sales influenced by online people start their journey doing their search. Yep. But so much of our online people that transact online, there's some nature of a film. And either they're picking it up in the store, the same day delivery we just launched is getting delivered from the store. Right. If it's not in our distribution centers, we're shipping it from the store. So they're intermingled, right? So when you ask me the percentage, there's five or six different numbers. Like, what were they placed on the list? Part of the internet. Well, we're on yeah. Well, part of the product journey to the customer, are we talking about here, right? It's integrated. So you know, I'd like to say it's this much in that much. Yeah. You know, obviously everybody's talking about AI, right? I mean, it's gotten to the point where it's the trade shows or the AI shows now, right? Everything is that. But delivering real operational value is happening sometimes and other times it's really not happening to some retailers or some projects and some areas. I mean, you have to have some opinions. You're on this retail AI council. I know you have visibility into all the different kinds of use cases of people who are applying this technology to. Where are you seeing real value and where are you seeing at the industry might be a little ahead of itself or that the idea is? Really, they're interesting, but they're not necessarily. Yeah, not valid enough. I guess is what I'm trying to say. The AI we've had before the LLMs, right? So that when we say AI, we're thinking of all the old models. All that AI is pretty mature machine learning, forecasting, so predictive for AI. We've had deploy or deploying for things like that, like replenishing stores, forecasting, some bot management, that kind of thing. Those are really mature. They're built into the baked into the products and they just work and you're buying software that is using that. So that old school, whatever one it called, legacy AI is rock solid. Specifically when we get to LLMs, the most success I'm seeing is when they're still a human in the loop. Yep. So basic productivity. You drive the store feedback thing I talked about, whether it's helping people write or do a project plan or come up with an agenda. So I'm not ready to have AI teach a whole class. Right. Maybe I want to do two days thing on leadership, but I could go on and say, give me a curriculum for two day class on leadership. It is going to inspire me to talk about things or things I didn't think about. We're using it a lot for translation. You know, you used to pay services, but it can translate really well. And you got to write your query smartly. Like I was just in Phoenix and you can say, you software's United States Spanish. Oh, okay. Yeah. You know, that's Spanish or Puerto Rico or it could mean South America. You know, the Spanish is speaking Arizona and my am here completely different. You know, it's not completely different, but enough nuance. So it's smart enough to have that query. Just getting people, we have people that a customer care can now do email support or maybe they couldn't before. Right. You know, that comfortable writing so they would talk on the phone, but now they can type an email and the AI can kind of clean it up. Taking a bunch of different data that's in desperate systems and presenting it to someone. So building your own MCP and saying, you know, we're doing one just for basic ask HR. You know, the benefits, the company policies, so all that stuff. And what this is doing is it's not replacing people. It's freeing them up to do the better thing. The more analytic work, productive work. Right. Oh, that stuff I see is right now where it's -- Doing the most. Yep. For customer facing AI, I'm saying, I don't have it yet, but I'm seeing people succeed on very basic questions. Yep. Number one call center question is always whizm -- Where is my order? Yeah, where's my order? Right. And there's some AI's that are doing that pretty well. Yep. Yeah, because it's there and the customer doesn't always know they're 15-digit tracking number or they're -- Right. And did you order a number? But the computer can know -- oh, it's Brian, a gaming phone number. He's only placed one order. I bet you're talking about that. Yep. Yeah. Well, look, there's a creepy factor. Yeah, there's always a creepy factor, right? Yeah. No, it's good. Customers want you to personalize what they don't want you to know. Yeah, I will think -- obviously, AI, what it can do in terms of aggregating large amounts of data, normalizing it in a way that it would take a human being a long time to make that data useful. Right. There are so many use cases around that. I think we're still very much in the early days. I actually saw a study the other day about where retail is versus other industries like financial industries and banking and manufacturing and other. Retail is in terms of -- there are hundreds of use cases. But in terms of the application of use cases at scale, it's still relatively small. Having said that, I think that more of these agentic workflows in certain areas are going to become very, very valuable. Right. And we're able to start kind of driving just streamlining and speeding up a lot of things all the way back into manufacturing and out. Whatever it is, right, given the inventory issues. Some of the agentic workflows around that whole inventory problem are, you know, pretty powerful use cases. I don't know that a lot of people have fully built this stuff out yet in retail. One of the challenges in retail -- and I say this all the time -- is that there have never been adequate technology resources to really do what is possible. You know, when times are good, retailers don't think they need new technology, when they're bad, they can't afford it. So there's always been a bit of an issue with that. But one of the things about AI that a lot of people are talking about is around governance. In your role, AI governance is going to be a very important part of your thinking. Maybe you could share a little bit about what you think about that today and how you think that's going to change over time, even. Yeah, so for us, we started with a policy. Yep. So that's a lot of debate about, you know, what we're going to allow people to do, not do. And then the policy turned into education. So let's reach out and then we made it mandatory. So everybody has to be educated on, you know, the simplest don't put private company data into public outweigh them. Simple as that. Yeah. And then we want to make sure that we're not deploying AI to individuals without training. Because we don't want people to either build prompts that you know, bad results. Or just become frustrated because they're like, they're treating it like Google and not happy with the results. Right. A little anecdote about saying Southwest Spanish or giving it up for someone. So we're saying, hey, we're going to issue you a license and we use co-pilot. But only after you go through this basic training. And then once people get on, then we have more training, more and more, to get more productivity. So that's a big part of governance is the policy, the sign off, the education, the requirement. And we also have a no guilt reporting. Like tell us which AI you're using. So when I was a kid, they used to have free library day. If you had past two books, they just wanted their books back. So it's kind of like that. Yeah, there's no penalty. But we want full disclosure so we can understand exactly who's using what. We'll document it. Because the whole industry doesn't know where this is going to go with copyright. There's already been some lawsuits. You know, can we trademark things? Sure people are building legal documents and sending them out for signature and AI without, you know, an attorney reviewing it. Because we've heard some stories about that. So governance is about AI education. But also, AI is changing so fast. I always say none of us are behind because it changes anyways. We have a commitment to having to keep up with it too. Because everything I just said could be nullified as the technology evolves. Yeah, right. I think that there will be better best practices around AI governance in the retail industry over time. I suspect some of the councils and things that you're involved with are thinking through that. I know that in her rep is trying to think through that right now as well. But you've got to imagine that we'll end up with at least a best practices, a model that we can follow. As we start to think about these things inside of organizations because the technology is changing so quickly. It has to be addressed, I think, at a higher level. Almost at an industry level. How are we going to deal with all of that and get it in place? And that's some of the things retail AI councils are trying to bring together so we can band together. In my industry, we're recommending supplements, vitamins, things that people ingest in their bodies. There's an additional layer like an AI recommends a shirt for you and you look silly. No harm to fall. But if you take the wrong supplements, you know, there's a big risk. - We have extra care that's gonna go into our-- program before we have an AI recommend. Yep, that's why I haven't person in the middle. Yep. So important. Prove human in the loop. Right. No, that makes that makes great sense. Or we're kind of getting to the end here. And without any buzzwords or anything, I mean, what capabilities do you think Reto should be investing in now that are going to still matter, let's say, five years from now? You have any thoughts about that? Like what's really, you know, kind of has a staying impact, a long-term value impact that they should be. Right now. Not a direct answer, but, you know, it's a lifelong commitment to learning. Things are just changing so quickly. You know, when I talk about hiring in the book with integrity and ambition, but also just the desire to keep learning about new knowledge. To get more specific, I'm really a proponent of composable. So I think my IT environment now is a big stack of legos that we snap together. Right. Really moving away from monoliths. So if you want to call it a service, you know, we have one inventory service and one customer service and one promotion service. I mean, we used to have a different promotion tool for the stores and for the web. And now we have one. So we can be consistent. And so if you have two different tools, you have twice the maintenance. They're not all going to have the same feature or calculation. So I think having in the phrase we like to use as deep platform, instead of replatforming or deep platforming, we did it for itemishopt.com, we did it for point of sale. We're looking to do it for order management. And then building a library of services that when a new idea comes, you just snap them together. Yeah. So I think the best future. Yep. Now I agree with you. And it's going to be pretty destabilizing in our industry when we get to that point because a lot of vendors and whatnot have either been selling the monolithic approach or have controlled the entire stack all the way up. I think we're going to start to see is we're going to be exposing capabilities, allowing people to write their own capabilities on a transient layer that lives above all of them. Some of those existing parts of our architecture are going to stay in place. So let's be honest, recharge camp, rip and replace. They just can't. Right. They're going to put a layer on top of that. And it's going to allow a lot more capability over the long term. Whatever way we want to think about that layer, you're pointed about promotion happening. One platform of promotion across all those data elements that are going to be able to drive whatever those value propositions have to customers across whatever channel. That wasn't thought of five years ago, right. People were able to do this. We now know today that that's pretty much standard. We're going to be able to get in there and play with it and do a lot of things. Come my last question for you. So if you're advising a retail COO today, what do you think is non-negotiable in terms of this area of engaging customers and scaling more deeply? Yes. Starts and ends with a customer. You said customer or I say customer or try to think about every conversation you have with the customer in mind. I guess I start with understanding who your customer is. You know, we do some AI to kind of dig deeper into our transaction database and really understand who our customer is. But none of it matters if your customers don't show up. I can sell my products in 50 different marketplaces, channels, LLMs. But if it's not the right product, the right time or right price and the customer doesn't resonate and they don't believe in our trust and all that, it won't work. Just don't try to solve a tech problem with business. Try to understand who your customer is and give them what they want. Andy, you have an extraordinary reputation because you have such great insights. Honestly, I really appreciate you finding a few minutes to come on this with us and keep doing the great things that you're doing until I can say, "Well, well, my favorite subject, you know?" I don't know. And for anybody that hasn't picked up the book, it's fostering innovation, how to build an amazing IT team. Honestly, your book is great. I really wasn't impressed with it. There isn't a lot of good reading in our industry. It's definitely worth the time and there's some great insights to come for it. I want to say I wrote the book before AI, so it's my real work. Yeah, but you know, that's really, and maybe that only comes with perspective, the core principles are what's going to guide how AI gets implemented. It's back to that issue you said before, right about don't take just because it's a buzz word. It's the hot thing right now. Like, how are you going to use Moe? How are you going to use AI? It's really about how do we solve business problems? How do we build an organization that can scale? How do we address the human side of building an enterprise and where does that technology fit into all of this? And I think that that makes it timeless, candidly. So, well, I'll say that. And I want to thank Fijitsu for sponsoring the podcast. Continue success and good luck, and I will see you at the next show. All right. That's right. All the best to you. Thank you again. Bye-bye.