AI Mucho Arte. Román Sánchez

Say the role for any of that capability only makes sense when you add one and one and it becomes three or more. Not two. Welcome to Technovation, I'm your host Peter Hai. My guest today is Kumar Khartakaya. Khartak is the Senior Vice President and Chief Digital and Technology Officer at Catalyst Brands, a retail platform created through the merger of JC Penny and Spark Group. The company operates a house of iconic American brands including JC Penny, Brooks Brothers, AeroPostal, Lucky Brand, and Nautica bringing together a broad portfolio that spans department store, especially retail and direct to consumer channels. With more than $9 billion in annual revenue, approximately 800 store locations, and a customer base exceeding 60 million Catalyst Brands represents one of the largest multi-brand operators in US retail, combining physical stores, e-commerce platforms, and wholesale distribution into a unified ecosystem. Khartak's been in his role for just over a year and is responsible for shaping the company's technology strategy and advancing its digital capabilities across this diverse portfolio, helping integrate platforms, modernize operations, and elevate the customer experience at scale. It came to this role after product, technology, digital transformation, and AI leadership roles, a company like AT&T and Levi Strauss. Khartak, welcome to Technovation. It's great to speak with you today. Good morning. Thanks for having me here. That's a great pleasure. I'm looking forward to hearing more about this tremendous story of a relatively new brand-wise company in terms of the parent brand that is this house of brands that are not new by any stretch to the imagination. Some of them going back multiple hundreds of years. Talk a bit if you would about an overview of Catalyst Brands business in your own words. I'd love to hear more about it. Absolutely. The way we see ourselves, we report fully of consumer brands, but what differentiates us is we're not just aggregating the brands, but we're actively building a shared operating model that allows us to brand scale more effectively together than they could independently. As an example, when we centralize capabilities, specifically around data, technology, AI, supply chain, fabric, customer experience, they all can scale independently. However, the shared capabilities are much more stronger. And then what we have to make sure that we are keeping the each brand ethos and we're preserving it instead of having a common user experience. So in so many ways, we think ourselves both as a brand house, but also as a capability platform. Talk a bit more if you would, given the diverse array of brands that come together, how you do think about what to be managed commonly versus what's naturally unique about each of the brands. As even the ones that I just mentioned, obviously anyone who's listening or watching to this would know the diversity of those brands as well. How do you think about the balance between those two, Cardic? Right, this is a great question. See the role for any of the capability only makes sense when you add one and one and it becomes three or more, not two. So we always focus on as an example data. Let's pick data as a foundation. You're talking about the scale of consumers. JC Penny has active millions of consumers. Airbo Stell has millions of customers as well. There was not necessarily overlap between these brands. So think of having a cross brand insights, which are driven understanding the same demographics and bringing consumers together and giving them more meaningful experiences and products which will elevate their lifestyle. So the goal isn't necessarily a uniformity in that, but it is more selective standardization, where it creates value combined with brand level differentiation. So that's one example. Other example will be not many brands on its own. They're all different sizes. They can afford say AI driven insights or analytics. However, when the economies of his scale come together, we build ones for a bigger platform. Every other smaller brand just latch on to those capabilities and scale it very quickly with very minimal investment. This makes sense. Thank you very much. Clarifying, talk a bit about just as the parent brand is relatively new. So is your role as a chief digital and technology officer. Talk a bit about your purview. What's within your responses set of responsibilities if you if you would? Yeah, I'm going to see my role sets at the intersection of technology data and AI and enterprise value creation is how I would like to describe my role. From particularly around our investments in data AI, more tech and digital so that we fuel the growth and then anything which fuels the powers the platform from examples to supply chain to HR to finance system. All of that is together part of my role. Also one of the big focus around my role is to get the alignment as you can imagine each brand has different size different value creation. So making sure that every brand is sufficiently invested into the growth equation or in certain areas just making sure that we maintain the pace of the crowd. So both at enterprise level and for each individual brand responsibility, I look across all and I also like jokingly somebody was asking me like so how do you describe it to one one line? I'm like well, I manage conference room technology. So if the telephone breaks my CEO calls me and if AI does not accelerate my CEO calls me as well. That's great. I wanted to ask you also how does your team extend into the brands themselves to do each of them have their own IT leadership team. How do you interact with them? How do you foster collaboration across that group and so on? Yeah, it's a great question. See, it's never easy when you have a combination of a lot of brands and different capabilities and priorities for each brand. So the way we have organized is we have created I would say we don't call it COE but almost think like shared efficiencies shared platforms which support all brands. So as an example, I have a leader in digital who would support all brand digital aspects. I've leader for data leader who looks after all data needs across the brand. So and then each brand CEO we have three of them. Each brand CEO has one go to technology leadership person who is aligned with their objective. And when they look at their long term plans that is a technology leadership person who is helping has a seat at the table to craft and help with their strategic business plans. Similarly, you know, from a support perspective where we make sense whether that's tier one or tier two support that's all common across all brands. And as I mentioned, your role is is new. And the formulation of your enterprise team was it a combination of bringing together people from from the existing businesses up to your level in addition to hiring from the outside. How did you put together the team that you now lead? Yeah, exactly correct. So a lot of these brands had their own technology leadership structure. So as we became one company at catalyst, we started consolidating and instead of having brand is specific technology teams, we started looking at what is catalyst is specific technology teams. So I have my existing leadership team. It's a healthy mix off a lot of internal, you know, leaders who know and understand the business processes and functions really well. And I have, you know, a couple leaders from outside who come from a bag and an off accelerating digital data AI and stuff as well. Interesting. And you mentioned as part of your purview data and AI enterprise value creation as these are topics that are fast moving. I can only imagine that you need to think about the upskilling of your own team to at least be at the same pace. How have you thought about that in this fast moving environment? Yeah, I mean, you know, everyone, every leader knows at least 50 60% off your success is dependent on the people you are surrounded with. So we are on a mission to upskill our team, making sure that there are a classroom life training based upon the functions they support. Not necessarily just a generic tool training. That's number one second. We are going very methodically after each engineering organization to see what the gaps are if they cannot be is, you know, gap cannot be filled by upskilling. Then we start looking at which long term programs you're creating, how do we hire and attract talent to fill that gap. So that's purely from a engineering perspective. Again, if you layer in from a business aspect or the functional aspect of it, there is a deep bench, which we have internal in the organization who have been in the organization for several years, they understand the good and the, you know, back part of doing the business. We still have, you know, believe it or not, we still have systems built into 1960s. So as we get into modernization and the right level of modernization, we continue to look at very nature scale set and attract them and make make ourselves attractive, you know, workplace. is to come and work for us. - Yeah, very interesting. And as Data and AI are a fundamental part of your purview, I wanted to take that in order. First of all, how do you think about Data and his diverse organization as yours? And how are you, how are you with a team laying in a appropriate foundation in order to take advantage of AI? I would love to get to AI next, but I'd love to talk about some of the work done to ensure that you are setting that right foundation in order to take advantage. - Yeah, absolutely. - And so as you said that each brand again has its own set of data. And we started looking at what makes sense to bring it together and is there a direct business value creation associated with that? So think of consumer became our number one priority. So we are on a journey of creating consumer 360 so that we understand customer behavior, we understand what they need, what are they talking about us, see set, all that together. And once we have a right 360 in place, any cross brand marketing or loyalty or personalization, they will all become very easy. So that became our number one priority. Other things to think of will be planning a location, big part of our go-to-market strategy, what are you buying, how much you are buying, where you are sending, which is store. So that is our another big priority in terms of bringing data together. Lastly, as five, six brands come together, there's always silos. So we're very mindful of not to bring everything together at once unless there is a clear business driving reason behind it. And that's where the prioritization comes into the picture. Now let's talk a bit more about artificial intelligence. I'd love to understand how you're taking advantage of it and what has you most excited in terms of the value that could be driven from it. - Yeah, there are several. So I'll just walk through what, where focus areas are for AI. But before I do that, one thing you ask previously about data, if we don't have clean data foundation, most of our AI is going to be either demos or pilots. That's pretty much it. You can't scale it. So we know that, we understand it. And most importantly, our senior leadership team, they understand it and they are behind all of our massive data initiatives. So it's less about the standalone AI initiatives right now. We have three broad categories is how we define our strategy. We call number one team experience, making sure that every team member, we're a few thousand people, corporate employees, we're making sure that every person, they get the right level of AI training. And as of yesterday, actually, 75% of our workforce, and I'm not talking about tech, I'm talking about entire company. They are actively using some AI tool for their day to day productivity and work. Whether that's creation of the email to creation of insights from the PDFs and data they get into a bunch of Excel. Second focus is consumer experience. So think of experiences around, you know, when they walk into the store, how do we interact with them? Are we giving store associates enough data about that interaction if they choose to identify? When they interact with us on digital, are we giving them personalized recommendation, search results around their wardrobe? And third, we call corporate efficiency. This is all about thinking around investors, shareholder value return. Any big transformation, like marketing, planning allocation, inventory, all those big areas, which is people might call it more traditional AI, but think of typical data science and machine learning type of big initiatives they fall into that bucket. Very interesting. I'd love to talk a little bit further about that middle consumer experience and tie it back to an area you described as an area of your responsibilities, enterprise value creation. What a fascinating topic. And I must say, Kartik, not the average chief technology officer or digital officer has that as part of their purview. I think it's a really encouraging sign that an executive like yours would have your hands on the steering wheel of a topic as valuable as that, in fact. Talk a bit about how you think about enterprise value creation and impact to customers, ultimately, who of course need to be the sources of a lot of that value creation as well. Right. So if you look at our brand, we have a very diverse businesses and again, very diverse demographics of customers who interact with us. So it's really important for us to understand first who shops at with us. Whether people come here for a style, whether people come here for affordable business, and you will find all of those examples. When somebody shops at Brooks, they're looking at really high end, couple thousand dollar basket values when they're shopping with us on JC Penny, they're looking at a lot more affordability and quality in the fashion. And having to have a strategy which works to bring both type of customers together, it's important that we have very clean data. We understand the business segmentation and then it start working with the brand CEOs to look at what are their top three goals. As an example, one of the top goals for us is we wanna grow the business. And when you grow the business, it's generally related to have more customers coming and shop with you. That's number one, retain the existing customers and increase the A/OVs. So we double down on creation of these two as a goal. And if you double click on saying, so what's the top level KPI you should follow? And the top level KPI for us is a CSAT. So if CSAT becomes your number one goal, the revenue becomes a byproduct for you. So we're doubling down on our CSAT goals. We're making sure that the enterprise is stands behind it and we just don't talk about the revenue in the e-bit. And that's the publisher's shift. You have to do when you become the customer experience, customer opsist company, versus a CSAT or other revenue driven company. >> Yeah, it makes a lot of sense in order to retain existing customers as you point out, but also to attract more of them. Customer satisfaction will be a great proxy for each of those. Can you talk a little bit about how the mechanics of developing the metrics that you have the KPIs associated with CSAT? How do you go about the collection of that data to understand data, current state, goal state, et cetera? >> Yeah, I mean, we look at across all channels, whether that's physical stores, having people encourage the customers to go back and give us the ratings or in digital is a lot more easier. You can nudge during experiences while somebody you can figure out if they're having challenges into the experience. You can nudge them with a very simple one or two questions or as they finish their shopping, you can nudge them. So we did a lot of work in the first few months when I arrived here to just set the standards and baseline to say what is our current CSAT across the channels and then making sure that and each brand again will have a different CSAT. And CSAT is such a broad category. People can give you good or bad rating depending upon how somebody greet it or not greet it in the store when you walk in, right? So you have to just be very objective around what those numbers are, you normalize them and then you make that as one of the top okay hours for the organization. And once you have a very clear objective defined your entire roadmap can be built around that. And that's the journey which we are on as we get into the more product-centric operating model specifically around digital data and more tech type of portfolio which are consumer facing. Once you establish those KPIs, every roadmap item has to have some element of that CSAT. And if it doesn't, that falls below the line. >> Yeah, very interesting. We've talked about a number of rising trends related to data, related to AI related to customer satisfaction and customer experience more generally speaking. As you look to the future, are there other trends that excite you topics that are making their way onto your roadmap that you would underscore? >> Yeah, I'm in fashion for quite some time. From Luleleman and Levi's to Catalyst now, I've always fascinated with two things. Number one is the digital fit. Unfortunately, no one has cracked the digital fit. And again, it becomes very difficult depending upon what type of a battle you're wearing, which is particularly difficult in the bottoms. And if you look at the Denima aspect of it. So I think that's one thing which fascinates me. They always keep it closed to understand how Gen/AI is going to help us in that. And the second trend is just blurring the boundaries between digital and physical. People will call it Omni-Channel. People will call it Figital. But again, that excites me. [BLANK_AUDIO] And the reason for that is as you can create something so seamless that someone starts browsing on their couch looking into your app and they walk into the store and your store, if they choose to identify the your store manager actually knows why she or he is walking into the store with what indent. And if you can serve them better in that moment, I think that's what the true seamless journey is. So these two trends are very close to my heart and I always keep looking into that. Really fascinating. Can we double click for a moment on the digital fit? What an interesting topic to raise. And you know with I one thinks about the tremendous progress that's been made in terms of like beauty for example and some of the beauty ability to try on makeup for example using digital proxies of one's order and other. How far along or how are things advancing? Are you encouraged by innovation that's happening in that space such that that digital fit might actually become more your prominent experience for all of us? Absolutely. As I'm in last few quarters I have seen a bunch of startups who are trying to get better every day. From my you know experience perspective, it's relatively easier to have tops on versus bottoms on and particularly you know the challenges also related to you know privacy and all. The beauty examples are people are taking the selfies of their face for you to have a right digital fit. You have to have the entire person is standing in the camera and taking the pictures and all. But you know the way the pace of technologies changing I'm very hopeful that you know the things is going to be mature and amazing you know stats which not many people know more than 40% of the returns are generally related to set in a battle. And if you can solve that problem which I think is really solvable depending upon the category and returns go down and that is the straight margin you know distance you're going to make even as going to get a lot more better. Well that's powerful that's very powerful I can see why that would be something that you're tracking with alacrity. I wanted to also ask you before I let you go, Karthik, what do you read or listen to that you recommend to others that helps you stay current? What are some things that you've consumed that you think others might gain from? Yeah I mean you know two things I do very religiously number one for any technology trends I keep the tech starters very close for example platforms like and recent industry newsletters just to understand what are these smallest startups up to because they generally will surprise you so just keep reading about that. When it comes to books and reading the podcast HBR business reviews fantastic I love that and recently from last few months I've been trying something very interesting which I would encourage everyone to do. While driving to work you open your chat GP, Bluetooth connection and it's not chatting it as as a fear chat GPT or Gemini or perplexity is your buddy and you pick a topic and just drill down and deep go into it. It is fantastic much more better than reading a book. It gives you a lot of insights around stuff at work, what's happening around the world, drill down into as deep as how a machine learning algorithm works. So I find it really fascinating and I do that in most of my drive time to work. Great suggestions certainly Karthik thank you for that great suggestions across all that you just mentioned. Well Karthik Karthik I really appreciate you spending time with me today. Not saying to learn more about this relatively new brand that is a house of esteemed iconic brands and to hear a little bit more about the justification of bringing them together to work you and your team or doing in order to ensure that 1+1 equals something more than 2 in the combination of these brands. And thank you so much for sharing your perspective has been a great conversation. That's great thanks for having me here. (gentle music)