S5 E10 | AI-Powered Supply Chains, Data-Driven Decision Making & Differential Leadership with Ajit Narayanan, Licious

Speaker A: Foreign.

Speaker B: Welcome back to the Tech Factor podcast by Purple Quarter. Today we have Ajith in the room. Thank you so much for joining us. Ajit, thanks for coming on a Saturday and we're happy to be at your office.

Speaker A: Yeah, thank you so much for having me here.

Speaker B: Awesome. So just for the crowd or for the audience to know, Ajit, you've actually spent your career with corporates and startups. I think that you spent a very long stint with SAP and then moved on to Myntra. And from Myntra you were a founding member with mfine, took a plunge into a startup, really small startup, and now you're at Licious. So could you tell us in a single word, if you had to define your journey, what would you say?

Speaker A: I'd probably use the word empowering.

Speaker B: Empowering. Okay. Could you tell us a little more?

Speaker A: Yeah, I think, um, so I'll use sort of three or four dimensions to explain, you know, how it's helped me this journey. I think first would be in the direction of innovation. So working in, you know, big established places like in SAP, um, and moving to startups gives you exposure to a lot of new technologies.

Speaker B: Right.

Speaker A: You get to work with great minds. So that's uh, that's a good thing. So you learn a lot. Um, so that's, that's one thing that I, um, I've, um, um, benefited from. The second dimension would be around, um, learning. The business problems are quite diverse in both places. B2B problems tend to be more long term. Um, in a startup you're looking for product market fit and you're looking for immediate results and so on. So they tend to throw up a lot of learning opportunities and that's been good. Um, from that perspective, the third would be around leadership. Um, you have structured leadership styles in big established places and you have flat hierarchies in startups. So the way you do mentorship and coaching of your people tend to be a lot different and that's helped me a lot as well. And the fourth would be in terms of impact, um, um, what you do, um, you see immediate results while in um, an established place, it would probably take you months or years to get there. In a startup, this is going to be extremely quick. So all of this have been learning for me and I think empowerment from these four dimensions has been for me, the big, big thing. Um, having spent my time in both B2B, uh, setups and B2C.

Speaker B: Interesting. So I'm going to double tap on what you just said. Right. And I think I vaguely remember Myntra was 2015 is when you got in.

Speaker A: That's great.

Speaker B: Just one year after, I think they got acquired by Flipkart.

Speaker A: So.

Speaker B: So tell us, how was your journey during that time? Because if I remember it correctly, and for people who are during that period, there was a lot more focus on revenues, wasn't it? So could you talk about how this empowering technology and learning went side by side with Flipkart coming into Myntra? And what did you guys do at Myntra as well?

Speaker A: I think in the first three months they saw sort of the momentum shift from your desktop to mobile.

Speaker B: Okay.

Speaker A: Uh, within. I joined them sometime beginning of April. And uh, By May, almost 80% of our revenues were coming from mobile app.

Speaker B: Okay.

Speaker A: Um, and around 90, 95% of traffic. Right. So I think what we saw that the point was the, the buyers and their preferences moving from websites to mobile. Right. Mobile was a big thing. Um, we had what, 300 to 400 million subscribers on smartphones. So a booming, um, let's say, um, infrastructure. So. And Myntra took, um, I think we took advantage of that. Um, we shut our website as, um, just famously called the App Only Move. Yeah.

Speaker B: Right.

Speaker A: Um, so we focused entirely on building the best fashion experiences for Myntra. Right. And that journey was absolutely, you know, filled with learnings, surprises, all of it. Sure. Right. Um, the mobile platforms were not as robust as they are today. Um, so there was a lot of learnings that we had to do. A, um, lot of, you know, I would say building, learning from mistakes, trial and error, um, all of these things that we did. Um, there was a focus on growth, obviously. And it happened. I think the tailwind was there, um, with us. And us being, um, focused on fashion gave us that, you know, that um, momentum to focus and build customer experiences for fashion, which the horizontals, like an Amazon or Flipkart were not doing. And that gave us the impetus that we needed. Um, revenue grew, um, of course, um, in those days it was a thin margin business. Myntra, um, luckily also had, uh, their own, um, um, private labels. That helped a lot.

Speaker B: Sure.

Speaker A: So, um, a lot of innovations that we did either on processes, um, or on technology sort of helped us grow in that phase.

Speaker B: Right.

Speaker A: Um, yeah, like I said, learning all the time. Right. Some, some, um, innovations worked, some didn't.

Speaker B: Right.

Speaker A: Um, but that was, that was it. I mean, if you look at the private label called Modar Rapido, that was one of the first, um, brands that was fully driven through data and data science. So the brand was Built entirely by algorithms and machines as opposed to, um, you know, human design.

Speaker B: Can you talk about that a bit?

Speaker A: Yeah. So, uh, what happens is when you. When you purchase something online, right. What users tend to leave are signals for you.

Speaker B: Okay.

Speaker A: Uh, on what their preferences are.

Speaker B: Right.

Speaker A: So if you wish list a, uh, product, um, or you add to cart a product, or you check out something, it tells you, um, it tells us that you probably liked some. Some aspects of that product. So if you break that product down into constituent attributes, like, for instance, you know, this shirt would say it's colored blue. It has a color. It has, uh, some print here, which you can't see.

Speaker B: Okay.

Speaker A: Um, and in a kind of weave and all of that. Right. These are attributes that make the shirt the shirt. Um, now if you see a lot of users actually adding this particular product to cart, you can sort of say that it is because of the color blue and the kind of weave and the pockets. Right. For instance, so if you analyze this data over millions of users over several months, what you can end up with is a recipe of a product that actually would be appealing for a consumer.

Speaker B: Wonderful.

Speaker A: Right. And so you sort of backtrack and reverse engineer the recipe that actually would work and that would sell. So essentially what you're doing is you're creating products that would actually sell through the best. Right. So this is fast fashion. Um, and we dabbled around with these little things of little innovations like this.

Speaker B: And this was in which year?

Speaker A: This was 2016-2016-2015-2016. This is a time frame. Now, of course. Uh, this is a thing. You see a lot of companies do

Speaker B: this, talk about it. Yeah.

Speaker A: So fast fashion was something that. And I wouldn't say necessarily we invented it, but I think we played around with it. There were learnings there. Uh, we used AI extensively. So, yeah, those were things that you could experiment, try, fail in that short amount of time. And this is, as a culture that we tend to see in a lot of startups. I carried on with my life at Mfine and now at Licious.

Speaker B: Right. So if I were to think of it, right, you did get to a role of a CTO while you were with Myntra. And, uh, may I call you the poster boy then of Myntra. I mean, I saw you in various form forums and talking about what you were doing with Myntra. How do you take the leap of faith to go and join a startup especially? Completely different field, right? I mean, you went into a health space. This was E commerce. So how did that shift happen? I mean, yeah.

Speaker A: So, you know, I had spent 14, 15 years in B2B, um, with SAP, um, and SAP taught me a lot, uh, in terms of how do you build platforms for scale, platforms for multiple businesses. You are industry agnostic. Um, in a company like SAP, you build for all industries and you build a platform that can be used by everybody. So it gives you ability to think in terms of platforms and abstractions. Um, um. However, the time to market or the speed of innovation is not as much as what I would have personally liked.

Speaker B: Right.

Speaker A: Um, you are always three or four steps away from the consumer.

Speaker B: Sure.

Speaker A: By the time your innovations reach your consumers, it's probably two years ahead. Right. I mean, consumers don't necessarily adopt at the same pace that you're building them.

Speaker B: Correct.

Speaker A: So there is that lag that you didn't generally tend to see. Um, so I wanted to try something which is much more immediate in terms of impact that you can create. And that's why I went to. I said, okay, startups is probably the best place to do this.

Speaker B: Sure.

Speaker A: Um, Myntra luckily happened. Um, the, the shift was quite dramatic, as you can imagine. The, the speed of things, uh, the, the way you do it, the culture of try and fail, and that's okay. Um, is all fundamentally different from what you'd experience at a, you know, in a. In a big setup. So that is, um, um, that was a learning process for me. Um, and that is something that I really enjoyed as well. Because business is fast. Um, um, your environment is changing so rapidly. The businesses have to adapt to that very quickly. So startups sort of live that every day and day out. Um, um, we practically used to say every day is a survival game. And that sort of build gives you a very different kind of, um, you know, energy to, to drive things, think of innovative solutions, you know, drive, um, you know, product, uh, innovations, whatever it might be. That's something that I reveled in. Um, so I continued that journey. Myntra was great. Um, but then I said, you know, maybe starting 0 to 1 would be something even more exciting.

Speaker B: Sure.

Speaker A: Uh, if you could touch a certain set of million users, um, with a company like Myntra, then can I do maybe a 10x of that in healthcare? That was the reason we went and built the startup. Five years didn't necessarily turn out the way we imagined it.

Speaker B: Sure.

Speaker A: But I think there was more than enough learning, um, which now I carry into my life at Licious, so. Yeah.

Speaker B: Yeah. Awesome. So, Ajit, tell us a little more. Right. B2B is a completely different landscape. When you compare the B2C and you've dawned both hats, right. Tech and product both. So tell us your thinking principles. Do they change with respect to these two?

Speaker A: Yes, I think across any aspect of business product engineering, I think they tend to be different. I'll call out a few things which are I think very, very critical. So one is UX and design. I think we should start there. Um B2B platforms tend to focus a lot on efficiency of the user who is using the platform. Um, maybe it's a CRM solution, maybe it is a ah, um, finance controlling solution or whatever else it might be. A marketing technology. You're focused on um, efficiency for that end user. So you're really looking at that. So the interfaces don't necessarily tend to be flashy and flamboyant, but they are purpose built to just fulfill that user's need.

Speaker B: Sure.

Speaker A: It tends to be exactly the opposite um, when it comes to a consumer. Now you're thinking about um, you're not talking about power users, you're not talking about people who know what they're doing. These are people who are browsing and they could be from different target groups within um, uh, the consumer segment. So they all tend to look at your product very differently. They expect a lot of different things and to cater to their needs you have to create your user experiences which are very, very intuitive in nature. Right. So they tend to be extremely different and that's one of the key aspects where you find fundamental uh, differences in the way you approach things. The second would be the way you think of platforms.

Speaker B: Right.

Speaker A: And this is both from a product and engineering perspective. Um, in a B2B. Um, like I said, most setups are industry agnostic. So you are assuming or understanding lot of different use cases across various industries and then creating the abstraction in a way that one product would tend to fit all of these use cases.

Speaker B: Okay.

Speaker A: Right. So the levels of abstractions and platforms have to be that strong for you to create a single product that caters to any industry, whether it is cpg, whether it is retail, whether it is manufacturing, um, it needs to fulfill all of those needs. So the way you build extensions, the way you build, the way you build modularity, all of that tends to be extremely abstract and complicated. Right. While in a uh, B2C setup um, you don't have to abstract to that degree because you're industry specific. Your delicious A's in meet E Commerce or uh, meet B2C.

Speaker B: Yeah.

Speaker A: Um, here the way you think of platforms is, can I build it in a way that if I were to extend and expand my markets, launch um, new business ideas, um, how flexible is the technology to actually empower that?

Speaker B: More horizontal.

Speaker A: Yes. So they tend to be very specific to the domain, but giving you um, agility in terms of new business models that you want to deploy because you are all the time looking for product market fit. So which means that your directions change. So the kind of abstractions you got to build are slightly different. They don't tend to be that complicated as a B2B world. But nevertheless you need to think of it this way. So this is the second aspect. The third is, um, agility and development speed. They tend to be entirely different in these two worlds. Um, since you got to build across industries of all these use cases, your life cycles of developments tend to be a lot longer. So you take six months to build something or a year. Um, and that's okay because you're building it for everybody. Um, while they tend to be extremely short, in B2C you're talking about weeks or you want to launch something in a festive season, you have to hit that date no matter what. Otherwise you miss that and you wait for another year and you don't have the luxury of time. So the way you think of agility is in days and weeks as opposed to weeks and months. In a, uh, B2B setup, the last one would be the way you think of marketing and um, product marketing. Um, your sales channels and marketing in B2B tend to be working with your account executives, um, going into enterprises and doing long term, it's more relationship based return on investment and all of that. While in a B2C setup this is going to be more SEO led, influencer led, you know, uh, specific brand marketing. Um, you don't have a person to talk to.

Speaker B: Correct.

Speaker A: Right. You're talking to everybody.

Speaker B: Right.

Speaker A: As opposed to in this world. So they tend to be entirely different and what you build for each of them also tend to be uh, different because of this. So this, these are some of the key differences I think, um, that exists.

Speaker B: Sure. So you know, uh, let's go to one part which you spoke about. In a B2C it's very important that you look at the design as well because you're interacting with the customer on such a daily basis. And let's just come to today's date and time. Licious. Right. So licious interacts with a lot of customers. How do you go about building technology where you're able to collect customer feedback, you're Able to retain them. So what do you do at Licious?

Speaker A: So again, I think, um, the fact that we are, uh, a B2C online platform means that we have a lot of data with us in the sense that every action that the consumer does, which is an install of an app or he's browsing, um, the homepage, going through the categories, um, making purchases, all of it is giving us valuable information about what is appealing to the user and what is not.

Speaker B: Right.

Speaker A: Um, so this helps us build the right cohorts of customers. Right. Um, consumers who are, um, you know, more, you know, people who eat, um, red meat more or efficiency food more. Right. They tend to behave slightly differently when compared to. To, let's say, somebody who eats chicken and so on. So these.

Speaker B: Is that right?

Speaker A: Um, yeah, I think, um, from, uh, a shopping experience point of view. Let me give you an example.

Speaker B: Right.

Speaker A: Um, chicken, um, that's just one product and you have multiple cuts of it. And therefore it's chicken is chicken. Um, in fish, there are hundreds of kinds of fish varieties. Yeah, Right. And every ethnicity in every region, they tend to like a certain one fish and not the other and so on. So personalization plays a big role in, in the efficiency food journey. While it might not as much got it in. In chicken. Right. I mean you might be used to a certain cut, but that's, that's, that's about it. Right. Limited personalization versus in fish, they tend to be extremely geographically concentrated. Ethnicity concentrated. So all of this matters. Um, two, they tend to be hit by a lot of supply constraints. Not all of this, uh, meat is available at all points in time. They tend to be, um, bans in seafood, um, fishing, um, which affects the supply. Which means that, um, when a certain kind of fish is not there, then people tend to sort of substitute, um, that with something which is similar in taste.

Speaker B: Sure.

Speaker A: Some people do it for taste, some people do it for the kind of dish you're making.

Speaker B: Sure.

Speaker A: So your substitution depends on, on either food backward or texture slash taste backward.

Speaker B: Right.

Speaker A: So these nuances play in that category very deeply. If you look at ready to cook, they tend to be entirely different. Um, in the end. Right. Um, it's more restaurant like, um, you're selling. You're selling almost finished goods. Right. Finished products.

Speaker B: Correct.

Speaker A: Um, yes. There is a little bit of touch that you have to add, which is your own cooking in the end, which is seven to eight minutes. But they tend to be looked at very, very differently. So ratings and reviews that customers leave become an existential part of that category while it is not and so on. So these signals sort of give you a lot of insights about how consumers look at your product. What appeals to them most, uh, why did they come there in the first place, what is causing them to drop off and basis this you are able to build very personalized journeys. Um be it in their shopping or off shopping experiences. Somebody dropped off because probably they found the service time was not good enough. So when we have a better service quality then we need to get them back onto the platform. So there is a process of reactivation of these consumers etc. That we need to do. So um, these are some of the techniques that we ah employ on the consumer side. On the um, supply side it tends to be a lot more complicated. Um because um first of all this is a um, it's a cold chain.

Speaker B: Right.

Speaker A: So right from our processing plants all the way until the consumer's doorstep this is a 0 to 4 degree supply chain.

Speaker B: Oh um. Okay.

Speaker A: Um. And uh there is a process of um taking your raw material and turning them into packaged goods. So we sell packaged food which is not frozen but fresh. So they maintain it 0 to 4 to make sure that you have the longest shelf life scientifically sort of tested and proven and so on. Um, so you operate with three day shelf life for most of the products.

Speaker B: Wow. Right.

Speaker A: Um and three day shelf life across let's say 250 SKUs. Um means that you got. And we distribute this using 100 dark stores in 20 cities. Right. So you have 100 dark stores, you have 250 yard SKUs and you have three day shelf life and then becomes. Now this becomes a mathematical problem. Right? How do I place which sku at what depth in which of these hubs in order to make sure that I don't waste anything. Right. It's a wastage and demand balance that you have to play. Right. You can't overproduce because then you end up wasting. You can't underproduce because then you leave revenue on the table. Right. So this tends to become very very complicated to do this day in and day out. Um add to this um. In order to get my packets produced in m my processing center today I need to have indents placed to my vendors who are supplying the raw material almost four days in advance.

Speaker B: Wow.

Speaker A: So that means on a day basis you are predicting seven days ahead. I'm trying to figure out how many packets of mutton keema is going to sell in Indiranagar. Um. And um, therefore I need how many metric Tons of mutton to arrive at my processing center, um, you know, on a certain day. And imagine doing this math. Right.

Speaker B: So, so you're saying there are patterns. You're able to draw patterns per specific skus?

Speaker A: Yes, you can. Um, um, you know, so the factors of consumption, um, tend to vary based on time of day. It varies, yeah. You see peaks.

Speaker B: Okay.

Speaker A: Um, it varies by day of week. So your Saturday, Sundays tend to be higher. And then of course the weekend, Monday usually dips, Wednesday you see a spike again and so on. And so there's a pattern of that and that pattern itself can vary. The peaks can change depending upon which month of year. Right. Um, and these peaks can shift up and down. Also basis, what is the population density around a certain dark store? M. Right. So in large Hindu festivals for instance, there will be dip in consumption in that population, but there will be you know, the other communities or whatever, you know, eating. Um, so it's pretty hard to get this nailed down precisely. But you can teach a model to learn all of this. And we've um, innovated on some machine learning models that is able to add uh, these aspects of um, religious calendar fed into the model so that it is able to predict to a reasonable degree um, how your product should be placed, how your demand is going to shape. We can do that for those products which tend to move fast because there is enough data for you to actually make the prediction. But when you have products that don't sell as fast, which is your tail, products which you still need to have in your um, you know, your, your selection, then it becomes hard. So your error rates tend to be a little higher. Um, in which case you have to do something called inventory rebalancing, uh, within a city. So if I tend to see that um, a certain packet, which is usually a slow mover, if I have predicted a certain number of packets to be sold in a hub and it doesn't, and if I see demand in any other pocket, move it, then I would move it. Right. So there is that inventory rebalancing that has to happen constantly between my dark stores.

Speaker B: Wow. This super complicated.

Speaker A: Yeah. To, to make this all happen. Right. And sometimes in, in a, in a pure quick commerce world, when you're not dealing with fresh and fresh, these problems don't tend to exist because you have longer shelf life. Therefore you can take bets on um, it selling out at some point and constrain your production in a way that you know, you don't, you don't end up making losses. But in this Category, it tends to be extremely, extremely complicated. And that's also the fun in building all of this in the right way. And there is, I don't think there are many players in the world who do this well. And we hope to be one of those first ones to sort of master this, um, you know, the last mile, mid mile, inventory placement. Um, I think there is a lot of science in this and exciting work to be done.

Speaker B: Great. So, Ajit, while you were speaking about it, right. There's a question that's running in my mind. You spoke about that mutton keema, and that needs to be, you know, um, backward integrated with these guys to say, I would need so much. Right, so much of mutton to get this done. So does technology also help you with the OEMs, I mean, the ones that were actually giving you this meat? Because quality becomes the most important piece for you guys, right, because you have such a short shelf life. Does technology play a role there as well?

Speaker A: Yes. So, um, it's not necessarily technology that we build today, but, um, that we built, but we do deploy technology to make this happen.

Speaker B: Okay.

Speaker A: So, um, at a processing center level, you know, how much of meat by category needs to arrive at a certain day for me to produce a certain number of packets. Okay, great. Um, so the purchase orders or the intents are sent out to vendors who would actually need to provide me this. Right now there are quality checks that are happening at the vendor sites as well, um, using tech, um, in some cases, in some cases it is visual inspection, and in some cases it's biochemistry tests and so on that ensure that the raw material produced there as well is of highest quality.

Speaker B: Wow.

Speaker A: Right. So at the site of production of livestock, this is checked. Right. So let me give you an example of farming. The kind of feed that you give to the, to the chicken, for instance, has an impact on the quality of the end product that reaches the consumer.

Speaker B: Sure.

Speaker A: So therefore, biosecure farms make sure the right feed, um, that they're rightly kept. Um, all of it matters. Right. Um, now we can't say a lot of this, um, in fishing, but fishing generally, what, uh, fishermen do is also that, um, they tend to use chemicals to prolong shelf life.

Speaker B: Oh, Lord.

Speaker A: At the site of fishermen, when they come with trawlers, et cetera, we have testing kits there to make sure that none of those fish actually is procured. We don't pick any of it, even if it means we leave revenue on table. That's fine. Um, but quality remains absolutely, absolutely important for us. So if chemical traces are found, then we don't pick. Right. So we do employ technology at the site of sourcing. We of course do a lot of quality checks at the time of inward into the processing centers. Everything from the right temperature that it's coming in it. So if it is not at 4 degrees, then we will have to then put them into a coal room, get it down to 4 degrees, measure pH, a lot of that and see if it, if um, uh, uh, satisfies our sort of criteria for it to be then sent into a production table for making, making the uh, uh, finished goods. Um, in some cases it is just rejected at the site, I mean during invert. So there are a lot of cases of that as well. Every egg for instance, is tested for float, uh, using candlelight just to make sure there is no cracks, there is no, you know, there is no rotten eggs, etc. When you're taking big consignments from vendors, um, you know, bad actors could ship in a few correct rotten pieces as well. Right. But we just have to make sure all of this is checked. So it is painfully hard to do this business and technology helps in all of this. We have not necessarily gone into this, this world in house to build all of this technology, but hopefully someday we will get there. And I think there's a lot of usage of AI computer vision that I can foresee that where we can, we can employ all of this, uh, in the near term to make this process also extremely, um, streamlined and near perfect.

Speaker B: Oh, okay. So, um, I also thought of something else. Right. So I think meat, when people used to procure meat, it used to be uh, in those black polythene covers. And Luscious was the first one to come with a design even for the packaging. What do you have to say about that? I mean, it's changed the way that at least India looks at how we procure meat 100%.

Speaker A: I think, um, the um, I don't know, shame, whatever it is associated with buying meat. Nobody wants to be seen around a dirty meat store. And that still holds good even today.

Speaker B: Yeah, true.

Speaker A: Um, the company started in 2015, but it is, that statement is so, so valid even to this day. And I think, um, let's just sort of change that game, you know, very fundamentally. Um, and packaging plays a extremely key, key role in that. But not, not just that, um, to preserve our shelf life. Okay, you need this. There is a lot of innovation in that packaging as well.

Speaker B: Okay.

Speaker A: The way, the way the. So it's vacuum sealed, for instance. Right. And we test for vacuum loss. Um, and why is that important? Because then there is bacterial formation that can happen in. It is aerobic. So therefore, presence of air means there is bacterial content that will develop and so on. Right. So the packaging has more than a brand value for us. It is, it is what delivers that meat in that perfect quality that, um, you enjoy, um, in your dinner table or your lunch table and so on. But on the branding side as well, I think people have really, really liked that.

Speaker B: Yeah, true.

Speaker A: So we've had, uh, customers sort of photos, um, on the packaging as well. They love it. Um, every time I meet, um, some folks at, um, some parties or get together, they're always asking, hey, how can I get my photographs onto the brand? Just imagine that. I mean, India, there was a place and time where you wouldn't want to be seen, uh, at a meat store to a time where people are saying, you know what? Get my photo on the box.

Speaker B: Wow.

Speaker A: Because I think you stand for quality, you stand for. And I want to be associated with that.

Speaker B: Sure.

Speaker A: I think, um, that's a big shift that's true for this industry, and hopefully we can carry this forward and we want to make it. So. I mean. I mean, our dream is to actually make it the biggest meat brand of the world.

Speaker B: Right.

Speaker A: Uh, starting with India, of course, first.

Speaker B: Sure.

Speaker A: But, um, yeah, I think.

Speaker B: No, no, I really love the part where you're saying that. Such a huge change of face. Right. I mean, you're thinking of meat as something that you don't want to be associated with, and suddenly you want your face on it. So I think it's a huge thing. Congratulations to all of you for what you've done with the whole thing. So I know it's a little. This is going to be a tricky question, but I'm still going to ask it. I know this is huge, complicated. There's a shelf life for three days, and, uh, you guys are trying to do everything as much as possible. But what is your prediction as a tech and product leader, uh, in this industry? D2C is different. So I want you to tell me, what do you see from a tech perspective that could be a shift?

Speaker A: So I think the first, um, thing, uh, few things that are going to shift, um, in the D2C world. I'll tell you my way of looking at what are the foundation pieces that needs to enable the shift to happen.

Speaker B: Okay.

Speaker A: M. The first and foremost would be, I think, um, omnichannel commerce. Um, it's been talked about for a while, but there are very few players actually who do this. Well probably very, very, very very few. Right. And um, um that is going to be a key lever of the future for D2C. So you have to think of this as a way that DTC brands need to be at the points of consumption where consumers are. Right. So that means that different markets, different channels, um, will mean a lot for D2C brands. Right. So offline will play a big role and it does in meat specifically. But then I need to make sure that the product synergies between online and offline is extremely strong. The consumer journeys are the same and so on. Seamless M is going to be a big area of investment, not just talk in terms of how do you get this done on the ground. That's hard. Um, that would be one, one big change. Um, the second thing that I see is what I call the supply chain. I don't know plus plus okay, supply chain plus plus. There's always a talk about supply chain 3.0, 4.0. I don't know what number it is right now but I'll just say there is a plus plus. Anything that you can imagine. Um, this whole thing about um, real time inventory rebalancing, prediction, demand prediction etc. All of this needs to fit in together. Today demand prediction tends to be a different technology module. Production planning tends to be a different technology module. Um, inventory management tends to be something entirely different. Um, these things need to play together um, and that synergies will start to play out in the next few years and hopefully we can lead some of those thought processes and um, innovations. But this whole dynamic movement of inventory and rebalancing is going to be so critical for D2C brands and especially in the fresh industry like us for this to play out well. So that will be the second one. The third I believe would be um, you know, cx, uh, you know customer support and you know consumer connect. Um, directions will change to be more automated, to be more driven through technology. You've always heard about chatbots coming into play and all of that. I think it's very near to that. If you look at um, some of the recent gen AI models, they can be tuned pretty well to answer very, very specific questions. Um, the day won't be far when you add voice to it, um, even linguistic support to it, make um, robotic um processes for this. Right? So that's going to be a big big thing. Um, and lastly I believe um, you know all of this needs to be held together for D2C. This is it's a consumer plus, um, you know the supply chain. So you know running control towers across this to make sure that what is happening where, etc, full visibility of your business needs to be um, um you know, looked at. So that will be another technological layer that will see a lot of evolution. You'll see a lot of players coming into this field. Um, marketing innovations. I think there were days of uh, you know, TV ad led.

Speaker B: Yeah.

Speaker A: Correct marketing I m think will shift more towards word of mouth influencer. You uh, and I uh, marketing products and so on. So you can see see a lot of shift that will change. It's not a technology thing but I think these are trends that will evolve in the D2C space.

Speaker B: Sure.

Speaker A: And to power all of this it's going to be AI and data. These are going to be our foundations. And I think there's not enough being said about AI. We always talk about AI as a technology innovation but mainstream application of this in all of these you know um, elements that I spoke about is going to get very, very prevalent in the next few um, years.

Speaker B: Interesting.

Speaker A: So this is what I see as shifts.

Speaker B: Interesting. Very interesting. So I think um, I love the part that you've said that AI engine AI. I'm quite excited to see that. If I'm ordering from Licious and then there's a robotic voice which saying that what I can order today. But yeah it'll be fun to see what happens. So just moving along and making this a little more fun conversation. I know I made it like really serious throughout the whole thing. So you've been been a part of a band, you've been a lead guitarist. Am I right Ajit? You've done some gigs even while you were at Myntra. Yeah. So um, do you want to talk to us about what got you into you know, being ah, a guitarist? What led you to. Towards music?

Speaker A: Okay. All right. I thought that was a past life but um. Yeah well I mean picking up guitar is like anybody else in college when you have a lot of free time, you don't know what to do. Um, yeah, uh, music has been passion from my school. So I said okay, not just listen, let me also play. So I picked up guitar to learn a uh, few things in colleges. I used to play with a band in college. Um, I used to play the lead guitar then and um, out of college the same college mates continued from different bands but of course we came together as one band.

Speaker B: Wow.

Speaker A: I switched to playing bass um, in shows but at home I still used to to play my Usual guitar. So, uh, we were together probably close to 15 years playing, uh, as a band, doing gigs. Um, all of that we did, it was for us. All of. For all of us who used to be. Who still are working, um, uh, much like me in other corporations and so on. Um, this was a big sort of let your steam out.

Speaker B: Sure.

Speaker A: Kind of a thing. Right. So get together the weekends, um, play a few songs, then find the next possible gig where all of us were free. Um, do that gig, get back to our, uh, work. So it was a huge, let's say, platform for just letting ourselves be. Ah, it was therapeutic in many ways. So we continued to do that for many years. Then I think all of us got busy with our own lives. And, um, you know, some of us moved out of India and we said, all right, instead of now taking the pain of forming another band, let's just call it a day.

Speaker B: Okay.

Speaker A: Uh, so we stopped playing for the last three, four years. But, um, in our homes, we still continue to play music. We still get together as, uh, band of brothers and still, uh, talk about music and all of that. We do that. So, um, yeah, I think it's important for people to have some. Some passion beyond, um, beyond this work. It helps. Of course. Being in a band teaches you a lot of different dynamics as well. How to work in a group, how to have differences. But still on the day of the show, then you remain tight as, um. Yeah. That nobody sees a mistake that each of you make. And we are making mistakes all the time. Uh, but you tend to cover up mistakes of one another, and that's beautiful.

Speaker B: I think I was going to actually bring that up, Ajit, because, uh, you know, you were a lead guitarist, you were okay to be a bass guitarist, and, you know, it shows. Also, there are few things as a leadership style that emerges, and since we've known each other for a while, I think, um, you are able to play the lead sometimes. You're able to sidestep and let someone take the show. Um, most often or not. I've seen that leaders don't want to take the sidestep. But with you, I've seen that, you know, you've able to push your team forward. You're able to tell them to go forward and do things. I've seen that in your journey in Myntra or even with M, find you're very passionate about what you do, so you keep everything tight, you know, together. So even with Lishes, it's, you know, while you were discussing the whole thing, it sounded like you formed the whole company. Right? If I'm, if I'm allowed to say it, I hope don't get beaten up by Vivekana Bhai. But yeah. So do you look for these traits when you're hiring your senior engineering teams? Do you see some of these? Do you look for them or what, what are your go to items when you're actually hiring people?

Speaker A: Yeah, I think um, yeah it is important for this. I think the first and foremost thing when hiring somebody senior and this is not necessarily in technology, um is um, to see that um, there is solid technical backing and uh, the understanding of the domain that the person is in. Whether it is finance, whether it is technology, whether it is growth, marketing, whatever else it might be. Are you deeply proficient in the core skill that you possess. So that is absolutely, absolutely important. It's almost like table sticks. The second thing is um, a deep understanding of business and consumer. And this is especially true for technology. Okay, right. Um, often technology leaders tend to sort of be either purely technology focused or tend uh, to be product focused but not necessarily business focused. I think this is important. If everybody in the senior leadership team is not looking at the business the same way then uh, a lot of time need to be spent and in bringing minds together and getting them onto the same page as they call it. Right. You have to be in the same page uh, by understanding business, not by because somebody is telling you to do so. Um, so that is an important uh, trait that I look for. How deeply do you understand business and consumers for you to actually see what is the technology pieces or whatever you need to do in finance or wherever else to actually aid that business. This will be a second thing. The third is um, um what I would say adaptability. And this is somewhat in that thing of when do you step forward, when do you step back, etc. I think um, assuming that you will be in the driver's seat at all the times and you have to be the driving, we all like to do it. Of course there is no. You'll be lying if you say uh, we didn't enjoy that. But um, there are times when you have to do. You have to step aside and let somebody else take the wheels and so on. So you got to be adaptable not only just in terms of environment but also that business is changing and therefore you need to change your thinking as well. And associated with this is the ability to learn. Um, as leaders we generally don't like to accept that um, we don't know everything. Right. The reality is we don't know. Um, there's a saying that we often know far less than what we think we know. And it is so true. Um, and accepting that and showing the willingness to sort of learn, um, either from your peers or your team as well, they have a lot of things to teach you. Um, um, or other industry leaders, uh, is an important, important aspect. So these are some of the things that I look for beyond just the ability, core ability itself. This is absolutely, absolutely essential. And of course, if somebody's played sports, somebody has done, you know, something as a team, then that also speaks a lot about that person's, um, leadership abilities or a team being a team player, being able to collaborate because it's so important as a leader, uh, you can't get anything done by yourself. Those. I mean, I think the moment you left your individual contributor realm.

Speaker B: Yeah.

Speaker A: There's practically nothing you can do yourself. Right. So understanding, uh, that is essential. So some of these, you know, I would say evidences sort of give you insights into what that person is. So it's not a, it's not a prerequisite. It's not like, oh, you have to play a team sport for you to be hired. It's not that. But the point is, if somebody's done it, they understand those dynamics and that makes it easier for the person to succeed. Uh, so we look at these, uh, elements.

Speaker B: Excellent. So I'm just going to push the pedal on the last piece that you mentioned. So I'm certain that you saw tough times during COVID Every organization did. There's a lot of uncertainty, ambiguity. And then there is this funding winter that's cropped up. So during this. And everyone's competing not against one another, but I would say that competing for profitability, competing to put themselves out there. So what do you see as, uh, the. What do I call it, the mantra for technologists, technology leaders, to be successful in this era. What would be your thoughts?

Speaker A: For me, there are again, a few elements that, um, are extremely important. The first one would be, um, deep understanding of business. Very deep understanding of business. I think it is, uh, understated. Um, often you hear, uh, things like technology is supposed to drive business and all of that. It almost seems like you have to do business a favor, um, by doing that. But, um, you have to be business backward. And technology, um, leaders need to understand this. Um, all of us love our technology pieces and to build. We are all builders. We are engineers first.

Speaker B: Correct.

Speaker A: Um, while we get all of that, I think it is important to discard that and Start looking at business and say what is important for that to happen. Right? So the way you look at build, buy, don't do, um. Right. It's interesting, but let's not do it right. It's very important for a leader to sort of uh, adapt to that. So this will be one very, very important piece. The second is, um, I think, again, I think we talked about adaptability and learning. Um, business, you know, dynamics change very rapidly.

Speaker B: Correct.

Speaker A: Faster than you can imagine. There is a competitor suddenly who's popped up out of nowhere. They are challenging the existing business models. Um, and they will hit you. Right. And they'll be faster than you because you, at some point you are larger than somebody who's small, I mean who's just starting up. Right. So they have agility that you don't have. So therefore they will be able to move quickly. And um, if you're not watchful of that, then your business is done. So being able to adapt very quickly and change directions is a very, very important thing. I think assuming that here is a roadmap that is going to stay stable for one year, I think is not um, the right way to look at it. I've uh, seen a lot of leaders expecting that and they see rapid changes as a problem as opposed to an opportunity. I think that is um, a second big element. Um, and the third, um, in my view would be um, uh, your ability to learn, uh, unlearn and learn is going to be quite frequent in your life as a technology leader. Um, you know, what, you know, today, um, may not be relevant tomorrow. Absolutely relevant things, um, whatever I picked up in some of my early stages of my career are absolutely useless right now. Absolutely.

Speaker B: Sure.

Speaker A: So if you don't keep um, learning, adapting, um, I think there is a, There is a shelf life that, you know, people, people will hit and that is uh, the, I would say the third big, big um, element of for somebody to be um, extremely successful. So for me these are uh, you know, a few things that people need to keep in mind.

Speaker B: Uh, very nice. I'm going to take that.

Speaker A: One more thing. You've um, got to have extreme amount of grit and resilience. I think this.

Speaker B: Sure.

Speaker A: Um, because business changes so rapidly, failure, uh, is going to be common.

Speaker B: Absolutely.

Speaker A: So if you're going to be hurt by the first failure that you see, then you will not succeed. You've got to keep trying and trying and trying and there will be some point where if your inputs are right, it should work. Right. So not giving up should be probably um, Even a thing to teach in colleges, I don't know. But it is so, um, we have to underline that. I think it is so critical, especially when you start to, um, assume, um, leadership positions or if you're going to be a founder yourself at some point, um, you will feel that you're hitting the road block every day and you know yourself as well being a founder, that those questions are going to come hard at you every single day. Right. Will we exist? Will we not exist? Will we exist?

Speaker B: Absolutely.

Speaker A: And I think, um, going through that, getting through that is so, so critical.

Speaker B: So, yeah, sure, sure. No, thank you so much for that. The point number two, something I'm going to take home. You know where you spoke about there could be competition that'll hit you in your face and you need to be prepared, need to look forward. Right. So I'm going to take that home as a lesson for myself. So before we wind up the show, any parting thoughts? Ajit, uh, would you like to give any piece of advice to young engineers or talk to, you know, groups of technologists who want to be at your level? Anything that you'd like to share?

Speaker A: Yeah, I don't know if there is a mantra or anything of that sort, but okay, I think to engineers, um, um, I think a lot of engineers today are, uh, extremely, extremely smart. Extremely. Um, they're quick on their feet, um, they learn technology. They already come with a lot of understanding of technology. And it's good to see a lot of people who are just, um, you know, fresh after graduation, getting into the depths of, of things, wanting to understand, um, how things work and move ahead.

Speaker B: Correct.

Speaker A: So I would only say one, um, be extremely curious, um, try to figure out how things work, why they work the way it is, challenge some of those assumptions that people are making. Many a times a lot of people are wrong, uh, and they don't know. Right. Um, so being extremely curious is absolutely, absolutely important to understand, um, the business landscape as well. As early as you pick up in your career, I think the more chances of you becoming a solid leader will emerge. Right. So while it might seem boring or it might seem, ah, this is not my domain, etcetera, it is your domain. In the future, the lines between business, product, technology, all of this is going to fade away because it's going to all be solution oriented.

Speaker B: Correct.

Speaker A: Uh, a lot of core technology frameworks are going to take away the pain of building everything yourself. Right now a lot of people use ChatGPT to do basic things like I can do debugging, you know, quite easily, and so on. Um, basic, uh, analysis. I don't need to ask anybody. I can do it myself because, well, it helps you at least 30, 40% of the way. And the rest of it you can do. So own the solution mindset, as opposed to saying, I will only do technology and all of that. So understand the business, think of solutions, be extremely curious. This is it. Uh, it's quite simple.

Speaker B: All right. Thank you so much, Ajit, for this lovely chat. I really am going to take few things back home as well, like I told you, so thank you so much for being on our show.

Speaker A: Oh, thank you so much for having me.

Speaker B: All right.

Speaker A: It was a pleasure.