10 Acquisitions. 10 Legacy Systems. One Year to Transform and Deploy AI

Speaker A: If you as a pet parent can't afford to pay that $5,000 upfront, you might decide to euthanize the pet.

Speaker B: You have been a software engineer, an enterprise architect, and now a global CIO managing multiple countries. That's not a very typical path.

Speaker A: We are going to jettison the, um, entire tech estate, everything, not a single system. In the dual space. 10 different companies is going to come along on the new journey.

Speaker B: How are you choosing your partners for the business and as usual box then how are you choosing your new age partners?

Speaker A: I've worked with tcs, Infosys, wipro, Cognizant. Right. I've worked with all of them in my career and what I learned is it's better to be a big fish in a small pond than a small fish in an ocean.

Speaker B: Most people in your capacity would say, okay, let's stabilize first. But you didn't just do that. You did AI along with stabilization.

Speaker A: We don't want to be like lemonade. We want to leapfrog lemonade. And to do that.

Speaker B: Hey everyone, welcome to CX Spotlight. I'm your show host Chira Khanijo and today I'm going to talk about one of my favorite topic. Why? Because it is super relevant to what's happening today. The most feedback that we ever get on is how many AI conversations we are doing with enterprise tech leaders. But what's the most asked question from most enterprise technology leaders is that yes, we want to do AI, yes we want to build automate and yes we want to do AI Everything. Automation, everything. But. But tell me how to do it with my legacy systems. Do I do legacy transformation first and then AI, Should I do AI bolt on to legacy system? Can I do both together? Because that will be the nirvana scenario. So we found someone who's actually done it not once, twice but is doing it actively right now. Today's guest is Munir M. Hafiz. He has been a hands on software developer to begin with. Somebody who has touched the system with his own hands and then spent 30 years in technology with Siemens, PwC, Deloitte, EVI, working on autonomous cars at Aptiv and then SVP and CIO at TransUnion. Now working as CTO at Independence Pet Holdings. And while he's doing it, he's doing it with 10 acquisition in four years and modernizing 10 legacy systems while doing AI with it. So let's talk about how he's doing that and learn from it. Hey Munir, welcome to the show.

Speaker A: Thank you so much for having me.

Speaker B: Awesome.

Speaker A: Munir.

Speaker B: Uh, most interesting thing, as I said, is your career arc. How about we start there, we start through this, walk me through this career arc because you have been a software engineer, an enterprise architect and now a global CIO managing multiple countries. Uh, that's not a very typical path. What does all that look like from where you're sitting now?

Speaker A: Yeah, I think there's always a difficulty sometimes for very technical individuals to be able to connect with the business and be able to speak the businesses language, which I think is super important, whether a CIO or cto so that you're able to deliver business value as opposed to technology. Right. It's, it's, it's not about the technology, it's about the business value that you're delivering at the end of the day. And I was a very hardcore software developer. I worked on telephone switches. Caller ID was my first project at Siemens, not to date myself. And I worked in telecom industry doing hardcore software network monitoring for a decade before I went into architecture and development management, et cetera. When I went into the big four starting with PwC, there started to get to uh, a change in my arc and trajectory. I started as an architect, then leading development teams, delivering projects for customers globally, implementing SAP in 100 plus countries as an example. And I started to slowly cross that barrier. From a technologist that is very focused on delivering a technical outcome to starting to understand the business language and focusing from a, uh, from a business perspective. That was a difficult arc for me. I'm very much in the engineer's mind and fortunately for me I've had some good coaches and mentors at uh, PwC, at Deloitte and EY that took pity on me and helped me along that journey and gave me some good advice that was very helpful in making that trajectory change from technologist to someone that enables the business with technology. Right. And that seems like a subtle difference but it, it's, it's a very critical one because what I've seen is that technologists focus on technology a lot of times for technology's sake as opposed to what is specifically the business outcome and technology's enabler for competitive advantage. It's not technology for technology's sake. So that's, that's been a little bit of my arc from a pure technologist to one that's more focused on business outcomes and technology. Uh, I don't want to say secondary but certainly as an enabler, but focusing on, on the business outcomes first.

Speaker B: Super. So you join, then you join Independence Pet holdings and what do you actually Find like what's the honest version of what the technology environment looked like when you walked in?

Speaker A: So just to give a little bit of background, so a private equity firm out of the UK called jab holdings had acquired about 15, uh, different brands in the pet space. Anything from pet insurance to shelter management software, pet microchipping. Right. And creating an ecosystem around that experience. JAB has a number of different retail consumer goods. So they own Hugo Boss, they have restaurants, Panera Bread, Pret, Krispy Kreme, are old, are all, are all managed and owned by jab. They've got started to get into the pet space because it's a huge addressable market in the US. 70% of US households have pets, 150 million pets, less than 5% have insurance. So it's a huge addressable market. And, and the growth rate has been in the double digit 20 plus percent for the last five years. So they've invested and created one of the largest pet, uh, insurance companies in the US and in Europe. And as part of that acquisition phase and part of the reason I was brought in, those acquisitions were running as independent companies. And now we needed to create a true operating enterprise as opposed to a number of individual companies. Not to draw a parallel, but when I was at TransUnion and I joined TransUnion as their global CIO, very similar journey, they had acquired a number of companies, 26 companies in 10 years in 30 countries. And the integration work across that landscape was very similar to here where each one of those organizations come with a different culture, different talent, uh, and a different set of technologies. Right. So we have 10 plus different policy administration systems. Right. In different phases of maturity. And managing an estate like that proves very difficult when you're trying to modernize and trying to enable the business to move faster because you're having to do everything 10 different times and that slows the pace at which the business can operate. Right. So, so a lot of our focus has been how do we take the strength of those tools but get to a point where we can consolidate and transform them and then be able to start to accelerate some of the business value. Like how long does it take to roll out new rates as an example. Right. The quicker you're able to roll out new rates, the quicker you're able to start to reap the benefits from the, from our customers. Right. So that's, that's been a lot of the focus and looking at that estate has been obviously a challenge. But fortunately we were able to convince the board that continuing to maintain different systems was not cost effective one, but also not going to help with the growth trajectory that were and the arc that the business was looking for. Um, not the least of which, of course can't have any of these conversations without AI, the introduction of more AI, claims, automation, et cetera, uh, all of that is much more difficult to do when you're talking about doing that in 10 different operating companies than when you're talking about sort of truly shared services. Right. And centralizing all of the technology and data assets in one organization that is then able to look for opportunities of how to move forward in a much more effective way on a new platform.

Speaker B: Give me your kind of genuine first reaction when you saw the sprawl of the systems. I'm thinking, because I've worked with this industry, there is actuary work, there is claims, there is pricing and there is policy and there is so many things. Right. And there are, I mean it could be anywhere from a, uh, build system versus a bought system versus a self managed or somebody else managed system. How did the sprawl look like? Could you talk a little bit in more detail about this so that people can relate to the sprawl that they see in front of today? How complicated was this?

Speaker A: The sprawl was, let's say, not surprising given the number of acquisitions. Right. I've been in many M and A activities on both sides of those being acquired and acquiring. Right. So it was not surprising to me necessarily how many different systems there were. Right. I expected that coming in. I saw that when I did something similar. TransUnion. TransUnion had 50 data centers. They had. TransUnion is about a four and a half billion dollar revenue. Their tech spend was $1 billion with a B on an annual basis. Right. 60 to 70% of the 20,000 employees

Speaker B: working at uh, TransUnion or at.

Speaker A: I know a TransUnion. Trans. Right. So I, I've, I've seen this before. Right. So that experience kind of prepared me for what I was about to see here. Right. The, the challenges that we faced was TransUnion is a larger established organization. Right. So for example, they already had a GCC in India as an example. Right. TransUnion had. So as you're looking to consolidate, looking for more labor arbitrage, cost control, there's already a vehicle of how to do that because they already had a GCC established in India, South Africa and Costa Rica. Right. So as I came in, I had a lot of maturity in an organization that I could leverage to be able to start to make change. Whereas here you're talking about buying 10 plus companies with 15 brands that are 300 million here, 400 million here, 800 million here. Right. So a lot of smaller organizations, which then means the uh, level of technology isn't always maybe at the level of sophistication that you would expect. Right. So again not to draw parallels by TransUnion, the companies that they would acquire were much larger companies, so they had much more established technology organization, much larger formal processes, et cetera. Whereas here when you start to acquire lots of small companies, the level of maturity isn't quite where it needs to be as a, as a foundation. Right. So a lot of what we are looking to do is to essentially start from a new foundation. And in a way it's easier at uh, transunion when you're talking about a lot of large established mature tech organizations that you're bringing together. There's a lot of expectation that there's the building blocks there. When you're starting from an environment where there's lots of smaller organizations, there was already an expectation by the investors that there was an investment needed to be able to grow to the levels that, that we're looking for. So in a way, even though it's smaller than TransUnion, it's, it was simpler and easier to convince the board that an investment was needed because there was almost an expectation during the acquisition process that some of these organizations perhaps under, invested in technology over a period of time, creating tech debt that we had to deal with. Right. So my job in a way was easier because there was already some of that expectation built that we're going to have to invest maybe not to the extent that they expected. Right. So had lots of conversations with the board around the magnitude of the changes that are necessary. Right. But that, that's been part of the journey and that, that my work in prior organizations, particularly at TransUnion before I came here, really prepared me for how of the expectation of how, let's say messy the environment might be. We had six different platforms for how we build 12 different mobile applications as an example, right across the stack, 10 different policy administration systems, most of them custom built, right. Bespoke custom development, right. Some third party solutions, but for the most part they were custom built. Right.

Speaker B: So and the logic was hidden in them.

Speaker A: Business logic, as you can imagine, over 20 years hard coded into, into, into the, the applications and that made it right. So a lot of things like single points of failure, having only one person that knows things, these were things pain points that the business was already feeling right. So I just had to surface them in more cohesive messaging. Right. But fortunately for me, the, the business has already been experiencing that pain. Right. And they understood some of the limitations of their systems. That again made my job a little bit easier to try and come up with a uh, transformation story of what we needed to do and why we needed to do it to enable the growth trajectory, the very aggressive choice trajectory that we have for our business.

Speaker B: Yeah, we will talk more about this, we'll double click on this because that's the story. But I think I want to say something which is came up in my research and I want to inform everybody about it, which I find fascinating about Independence Pet holding, which is that I think it's just five year old entity in a way. It was formed in 2021. But the Crazy thing about it is that all these companies that came together were existing since a long time. So the systems are still long time legacy. It's not like it was just five year old problem that you were solving. It was actually 15, 20 years old problem. But at the same time it's not small at all. It has around 800,000 pets insured within just US and Canada. The last numbers I saw. Is that true?

Speaker A: Yeah. So our gross written premium is around 3 billion. That's, that's just North America. Right. And you've got another billion, billion and a half in Europe. Right. So between the two organizations, about four and a half billion and overall I think we have a million and a half pets. The 800 million that you probably saw, that was just our pet's best brand. That's at around uh, 8, 800,000 customers. We're reaching, getting close to a million customers just in that brand.

Speaker B: Yeah. And that's why I found it so relevant for this conversation because 20 year old tech debt, 15 year old tech debt, super new company that needs to figure it out and then growing so fast that you can't just say I'm just going to fix stuff. You have to, you know, capture that revenue as well. What fascinated me is that you even acquired recently a cat pet brand then, um, um. And that means, you know, so much innovation expectation and revenue expectation on you. So that's where I think I want to go next into this section is that most people in your capacity would say okay, let's stabilize first, get the house in order to, then we'll think about AI. That's what I hear most common. It's like a knee jerk reaction or a uh, or a mature, obvious expected reaction. But you didn't just do that. You did AI along with stabilization. Before we go down that path, tell me your reasoning behind that and the risk that you accepted with that.

Speaker A: So there's sort of that proverbial example of building the plane in mid air. Right. And I, uh, know a lot of my peers certainly experience that same, same feeling right. Where you can't stand and you have to do multiple things concurrently. Right. So in the space that we were in, the growth is so explosive, which is good news from a business perspective. Right. But the demands on the systems are so great that standing still to clean up some of that tech debt first and then being able to start to do a transformation on a new platform that is agentic first, et cetera, was just not an option. So from a timing perspective. Right. That would take too long. So what I've decided to do and what we've agreed to on a business perspective is that we're going to bifurcate and basically look at the organization as two separate organizations and um, not just on the tech side, but also on the business side. So one, we looked at the talent that we had and if you look at the talent there, they've built a lot of these systems over the course of the last 15 to 20 years. We, we needed to be able to keep them engaged, support those systems. But they also knew that we're in the process of replacing them and that had, they have a dying skill set. Right. So it was a big risk because in many cases we had single points of failure. It was one person that knew how uh, things worked. So the, the approach that I opted for is instead of bringing in a third party that can take over the application space and let the team go or dangle uh, the team along for the next two to three years while we do the transformation, then let them go. Right. I didn't feel good about that. As, you know, just as a leader taking care of their employees, I was looking for a win win for the business and um, the employees at the same time that's sometimes at odds, but opted to actually re badge the employees to one of our third party partners. And what that allowed us to do is to give them a career path and certainty of their job trajectory long term. They're no longer worried, well, what's going to happen to my job two years from now when my system shut down? Right. And now they are with a third party that once they're off of our account, they have growth opportunity on other accounts. Right. So, so that enabled us to not only reduce cost of the legacy systems, but also to secure that talent longer term while at the same time also being able to uh, quite frankly look myself better in the morning that I did the right thing not just for the business by lowering cost and securing the legacy systems, but at the same time also doing the right thing for the employees and not laying them off and giving them a job, job growth and, and, and a career long term. So we essentially what I look to do is have two entirely parallel stacks, right? So all of the existing systems will continue supported by a third party. We've also did a managed service for all of the infrastructure. So putting a neat box around all of the legacy systems and being able to have the right talent that can continue to work with the business because we can't slow down on. Right, that's, that's the plain and midair analogy, right? I can't build a new system and not continue to maintain and freeze the changes in the existing systems, right? So I needed to create an entire separate ecosystem that would continue to work with the business on the growth trajectory. But now having that be managed by a third party, right, where, where they take a lot of the burden of the documentation and the processes and the testing and et cetera and securing the resources because now they have long term career growth they're no longer worried about. I'm going to lose my job in two years. So that's one, one bubble. Now the, the new, the new is where we're hiring and in some cases also using some of the existing talent to build an entirely parallel team that's going to work. Focus on the new. And I think the key to transformations and our uh, you know, we've all been through many transformations. Usually it is, you're touching bits and pieces of the technology. You, you're touching your erp, you're touching your CRM, right? You, it's usually an ecosystem of technologies and you're touching maybe a core anchor application or you are limited by existing business processes, right? So what, what we've convinced the board is if you start to bring AI into the picture, right? Think of latest data I saw only about 11% of projects have CFOs actually show a benefit to the bottom line, right? So the vast majority of AI projects are focused on blue money, right? This is uh, a Gartner term as they like to come up with all these cool terms, right? Blue money versus green money. Blue money is productivity, NPS scores, kind of soft benefits, right? That are benefits, but they're not like hard dollars, right? And green money is flows to the bottom line, to your P and L. So productivity improvements certainly a great thing, but that doesn't necessarily translate into dollars. Right.

Speaker B: So.

Speaker A: And if you look at why a lot of the programs out there don't deliver hard cash is because there's not a fundamental change in the business process. If you add AI to an existing process and you don't optimize that process, then you're introducing productivity incremental change, not transformative change. So what we looked at and what we've said is, look, we are going to jettison the entire tech estate, everything. Not a single System in those 10 different companies is going to come along on the new journey. And not a single one of the business processes are going to come along either.

Speaker B: Wow.

Speaker A: So what, what we've been able to have the board understand is that if you want the best benefit from AI, if you take a lot of your business process baggage with you, you're going to have a lot of the same problems just in a fancy tool, in a nice new stack, you're going to have some of the same legacy problems and you're not going to get the full benefit. That transformative benefit that AI can get you if you don't rethink your processes from scratch with Agentic and AI as the foundation of those processes. Right. So we're essentially creating two parallel companies. One company that's working with legacy and continuing to focus on business growth and one company that's going to work build the future, both from a tech landscape and as well as from a business process perspective that's going to have, then at some point those two are going to come together two to three years from now. Right. And at, uh, that intersection point is where we do the migration. Right. And then after the migration, we shut down the entire new stack. Now that is going to mean major, major, major change management on the business side side. Right. But again, I think there was a general recognition that incremental change changes on, on the periphery, on the edges. Um, can I introduce an AI chatbot to increase my digital channel versus people calling in? Sure. Can I have an outbound agent calling out versus a salesperson calling out? Sure, you can do those things, but those are not transformative. Those are incremental improvements. And what we're looking to do is to entirely transform how the business operate to have zero touch claims processing, zero touch policy administration. Right. That is a, that is a far cry. And if you look at, in the us, the, if you think about kind of the pet healthcare system is different from the Human health, obviously, but in the pet, if you think yourself as a pet parent, you go to the vet, your dog is sick, your dog swallowed something, let's say, right? It's probably $5,000 later of X rays and surgery, et cetera. And what happens today is as a pet parent, you go in, you get that bill, you have to pay that upfront, and then if you have insurance, be able to go get free, right? So if you as a pet parent can't afford to pay that $5,000 upfront, or you're putting it on a credit card at 24% interest, you might decide to euthanize the pet and that you can't afford to do it. Right? And, uh, we've seen that. So what, what we're aiming to be able to do is that at the vet, at the practice management software at the vet, that the vet is able to live, put in a claim, say there's this, uh, that has insurance with us, be able to put a claim in, and for us to be able to, within milliseconds, to be able to come back and say, yep, claim approved. We'll pay you $4,500. We'll pay the vet clinic directly. All that the pet parent has to pay is their deductible, $500. So you can say, okay, your insurance has already approved that, they've paid us. You only have to pay your deductible so you can take care of your pet the way you need to, rather than having financials be the dictating factor. Right. So we're looking to transform how the pet experience for the pet parent is right at the point of service at the vet clinics, of which I believe there's about 26,000 vet clinics in the U.S. right. So that's part of the transformation that we're looking to be able to do. To do that, we need full claims automation within milliseconds, right. Um, where we need adjudication, OCR for all of the medical records, right? There's a lot that goes into making something that's, you know, you could describe in a minute actually work from a technology perspective, especially given where we are today. So I think the uniqueness that I saw in the journey here and that we were able to push through is be able to essentially bifurcate into two parallel threads. This work. Now, that's not always possible. Uh, it doesn't. It's costly, but it is also the fastest way to do it. Right? So the conversation is always, what's more important to you? Is it more Important to do it fast or is it more important for you to do it cheap? Right. If you need to do it cheap, you're going to go slower, right. And then you can't essentially bifurcate your organization both on the tech and the business side. But if you want to go fast because you're growing at 20 plus percent a year, you don't have time to take five years for a transformation. You need to do a transformation to the 2, 3 years. If you have to do it at that pace, you have to take a different approach that's totally different. And that's where that bifurcation becomes super important. So that you have dedicated people that are working on both versus people that are working across. Right. And are limited by, you know, the bau. And BAU is what's paying for everything. So it's always going to tend towards the BAU capacity, right. If there's, if there's an issue, it's always going to tend and you're going to pull from the new and then the new slows down. You don't meet your targets, takes longer, costs more, right. So that, that's the thinking that's gone through of how do we transform with what's there in the legacy perspective and, and be able to get the maximum benefit from an AI perspective in the shortest period of time.

Speaker B: So this is one of the best playbook. I will play it back to you because I heard that I'll play it back to you, but I don't want to lose the thread because we are, we are onto something super interesting. You exactly gave out how you did it, right? Can we further double click and say what's the thing that actually breaks the most often when people try to do what you're trying to do, which is live with the old, but build new in a separate box, what breaks the most, what happens.

Speaker A: So, and I, and I lived at a transunion, right? Uh, doing almost the exact same thing at a little bit larger scale. But you usually run into a few things. One is culture, right. I believe the saying is culture eats strategy for breakfast. Right. And if you're, if you're trying to get a lot of existing, whether it's on the tech, on the business side, people to train incrementally, that is very painful. You almost have to start fresh, right? So that's, that's, that's one of the lessons that I learned trying to get them to change over a period of time incrementally is, is super painful. Um, because of culture sets in especially if the organization's been around for a while. The other challenge you usually usually uh, run into is that when you're using sort of common resources or common teams, the revenue generating side, which is the legacy side, it will always take precedence. And if you have teams that are, you know, the same infrastructure team, the same security team, et cetera, then the priority is always going to go back to well, this is revenue generating so this is what the priority needs to be, right? So when you're trying to commit to timelines where you're going to achieve certain things, it becomes very difficult because you always get pulled, right? So not bifurcating has that challenge of the cultural change becomes incremental and it becomes a death uh, by a thousand paper cuts. The lesson learned for me is you got to rip off the band aid and you got to start fresh and then sharing m the resources uh, will slow you down because you always are going to give preferential treatment, understandably so to the revenue generating side, right. You've got the cash cow that's paying for the transformation, right. You got to make sure it's still, it's still moving forward. Right. And then the third part really is around the reimagining of the business process and you start talking about AI. Obviously AI is, it's, you know, it's entire own conversation. But when you are, when you're taking existing processes and you trying to change them, you're looking at incremental change, not transformative change. So that's the other big challenge that I see. When you're doing a transformation, either you're doing it in the margins or you're focusing on a ah, new tech solution. But you're carrying over some of the legacy debts, right? If I learned anything, doing a lot of SAP, SAP implementations is the biggest challenge and I can tell you looking from, from outside in whether the program will be successful or not. There's a few key criteria. One of it is are you making SAP conform to your process? Are you conforming to SAP's process? If you, if you're making SAP confirmed to your process, even if it's a five year program, I could tell you right from the beginning it's going to fail, right? Or it's going to be super, super, super painful. So those are kind of the three things. The, the cultural changes, the, the, the, the difficulty being able to balance and the prioritization across old and new. And uh, then of course the business process being optimized from the ground up for geni, not limited by the art, by by today, but by the art of the possible. Right. That's what you really want to focus on.

Speaker B: Yeah. So for a lot of people, if I could try and reiterate what I heard so that we can bind it into a playbook that anybody should be able to take value from. Here's what I heard is that from your experience of these at TransUnion, having you know, 30 different companies, 35 countries and all those systems plus here, what you're observing is to the North Star first is to identify what's your business as usual versus what, what's your new objective, what's the dream state or the North Star that you're driving towards. And then first step was to get the buy in and be very honest about conversation up to the leadership that this is what it's going to take if we really need to bring innovation, true innovation, not incremental, not patchwork, not like a band aid innovation, which I think gets mentioned so many times that I am bound by so many things that I cannot innovate. So probably the most revealing thing is to bite the bullet early in the game and say this thing that here is what's going to take. The second amazing thing that I learned was that tribal knowledge is the most important thing and culture is such important thing. If you address it in an inhuman way then it's not going to help you. So I think you did right and did good at the same time by rebadging the same employees who get to have a career trajectory and protecting your tribal knowledge at the same time. The second thing I really think was valuable was that which uh, is brilliant in a way that for you as a leader and your leadership team to build this new aspirational AI zero touch system that you're talking about, you need to have your brand brain cells available and not going in day to day work. So you found a partner to black box it uh, or to kind of box it and protect your bau. So the revenue is dependent and somebody else is responsible for the SLAs and things like that and taking care of your employees as well while you have energy to build new. Right. The final thing which I think so many people get wrong is amazing which is let's conform our new AI to our old standards and build incrementally. I just love that analogy so well that every workflow that you're designing, if that has a confirmation bias of what you used to do earlier. Then I had somebody, some CIO come on the podcast and talk about how in their biggest AI initiative The maximum time they spent was build the integration for the old system. That took 95% of the time. And I think that's what I realized here was the separate part of doing the new. So all fantastic learnings and really a playbook of doing that. My thought goes to that while you're doing this, all these 10 companies had their own culture as well. Right? How did you. And their own way of working per se. Culture defined as their way of working. What did you find harder? Was it to manage the technology or solve it for the people that came along with it?

Speaker A: People's always the harder part, Right. The technology. I've never met the technology problem that I could, that you can't solve one way or another. Right. It might not be elegant, but there's almost always a solution one way or another, especially if you throw enough money at it. But culture, it doesn't matter how much money you throw at culture. Right. You could throw enough money at uh, a place problem with tech that you can solve. But culture is super, super difficult. So I think the, the key to me was a few things. One is understanding the skillset of the teams, understanding who had the right aptitude to work on the new versus the old. Right. So I spent a lot of time in my first four months and I, uh, building relationships with the tech teams as well as the business of course, but certainly focusing on the tech teams and understanding the skillset, the mindset of people. Right. And then being very clear about what the North Star is. People can get behind a North Star even If they don't 100% agree with it, if they understand what it is. Right. I think a lot of times the vision is not clear. It's, you know, a 20 page detailed presentation. If you can't describe your North Star on one page. I learned that when I was@deloitte ey. If you can't show a strategy on a page, then it's too long. Right. So I think being able to have them understand what the future holds and their role in it was super important. But reality is, and you know, and I was very frank with the team, there's going to be people that are going to opt out. Right. There are people that liked working for small companies, small startups. Right. And there's nothing wrong with that. I have full respect for that. Sometimes people that work for startups are not going to work for large enterprises and vice versa. So this is where certain people opted out. Right. A lot of the CTOs of those companies are no longer with the organization or have taken on different roles. Right. Because the, the, the m, the skill set and the mindset was not going to match the future. So I think the really hard part is figuring out what is the mindset of people. Skill set. People can pick up new skill sets, but when you talk about the mindset, that is a much more difficult thing. And you know, whether it is sort of quiet quitting or whether it is agreeing in public but then undermining in private or any, any of uh, the kind of cultural issues that start happening with the team. But I think this is where I really found that if I can build a team from scratch while the existing team operated as is, I would have a much larger degree of control of um, the culture. Now I think the obvious question is where do you get the money? Right? I mean I'm, it's, it's uh, if, if you have a good supply of money, you can, you can do something like that. Right. But so for, for me I self funded on the, on the tech side this transformation to a large extent because as I've re badged employees, we're also able to lower the cost of the support of the systems as we brought in resources from offshore. Right.

Speaker B: So spend got repurposed. Oh, nice. Okay.

Speaker A: Right. So the spend came down. Right. So that I can self fund a lot of the roles that I needed to hire. Right. So that's not always an option. But in this particular case rebadging solved a whole slew of problems including how do I fund this. Right. Because going to the board and saying hey, I need X dollars and it was a difficult sell for the board. Right. And for the business leaders to, to say, okay, we get it, we're going to have to throw everything that we're doing to start from scratch. That is a super difficult argument to make.

Speaker B: Yes.

Speaker A: Part of, part of the path to that of saying we got to build separate and new is we have an entirely functional stack. Even if it is not ideal and suboptimal, it's an entirely functional stack. Yep. Yep. So if I'm building new, new is always risky. Right. Uh, and if anything goes wrong, timelines extend, which Almost, you know, 80 plus percent of tech projects go longer than expected. Right. Then I have an ex entirely existing stack that's functional. Right. I'm not putting the business at risk by taking out a piece and putting a new piece in and um, doing open heart surgery. Right. And then the heart failing and then the business fails. Essentially instead of doing heart surgery, I'm bringing an entirely new body essentially.

Speaker B: BAU is protected there.

Speaker A: The BAU is protected, the business is protected. And that was one of the key things that the board bought into. Right? You're protecting the business, right. There's always skepticism of major transformation programs for good reason. Right. So the fact that we can put a bubble around and protect the business and if there is challenges with the implementation timelines, uh, with the implementations, you're not risking ongoing operations or ongoing.

Speaker B: Awesome. So you're one, one year into this. How much time are you into this? Two years into this transformation.

Speaker A: Next year will be, uh, next week will be one year.

Speaker B: Okay, next week, almost one year. One year into this, the bet was AI automation zero touch first. So what's actually working and what has come out of it so far?

Speaker A: So I think one of the important thing is you, you can't entirely, I don't say abandon the existing stack, right? You still have to make enhancements. And we have introduced AIs in there, outbound, outbound calling, inbound calling chatbots. So, so we have introduced AI capabilities, right. But again, I would say they're not transformative, they're incremental. In, in many cases, you know, an AI chatbot for customer service is not really, you know, radical these days, right. It's. Everybody does it. So I think where we can, we're still investing in the legacy systems, but clearly we're putting most of the investment and most of the focus on the new stack, right. And it's, and it's a daily conversations I have with CEOs of different business units, right. Of do you really want to invest this money and this dollars in your existing system that you're going to know in two years that's going to go away. Or do you want to focus on building the new? And sometimes the answer is, you know, even if it takes, uh, us six months to build it, we still have a year and a half of benefit and that's, there's a lot of dollars associated with that and we have to go for it, right? But again, if I'm bifurcating and I have separate team, right, A separate, totally separate development team out of the two, then I'm not worried about, oh, if I continue to enhance that and I'm taking away capacity from the new, right. So I have totally separate development teams, totally separate leadership on the tech side and we're advocating for the same on the business side that are totally taken out of their day job. Right. And this is the other mistake I see a lot of times is that the business participants, this is A side job, right. They have their day job and then they're working on the side on, on requirements and figuring out what the new system is going to do. But that was the insistence that you have to pull them out. It's a full time job, it's a full time business process owner job to be able to define these things. It's not a side of desk. Right. So it's not just on the tech side, it's also on the business side that we've had to advocate for that. But what we ended up doing is being able to come in with what are the business benefits overall if we do this transformation from rate loss to how quickly we could implement new rates to customer service costs, cost per claim, etc. Right. And we project it across all of these different areas. What the business impact would be, whether revenue increase or cost savings and lowering our admin ratios so that we can justify the cost of the actual transformation because they do cost a lot of money. So I couldn't, certainly couldn't self fund all of that, but I could certainly fund seeding the new tech team. Right. And the rest of it will come from the business case. So that, that's been the, the journey that we've focused on the last year. And you know, for being there for a year, I think we've made a lot of progress in, in one year. But we still have a lot of work over the next two, three years. We always joke internally because we're, you know, a pet company, that it's dog years, right? That if you're here, you know, it's like one year, seven dog years, right? That's it, you know, you've been here. But it's uh, a, it's a dog year. Not a, not a normal over here,

Speaker B: you know, on dog. I'll tell you a dog story which relates to. Do you. I was at my, I was meeting a good dear friend of mine in Chicago. I was going to speak at a place and I went and met one of my friends and they, they're pet parents and they have two, two dogs, Ollie and Bozo. And, and then I asked so which breed they are and they pulled one of your guys. Figo. Figo, yeah, you know, Figo. And they, they pull it as a shih Tzu, this Maltese, uh, and a mix of that and it was phenomenal for me and I asked who's that? And then I looked up Figo and I started realizing that you're going to come on the show and this belongs to that. So that was a Great story and example of. And then they started showing me about some, there's some pet health thing as.

Speaker A: Wellness. Wellness, yeah. So you can take them for vaccinations and things like that. Yeah.

Speaker B: So those are, those were phenomenal. I didn't realize that uh, the like your landscape is so modern and digital sort of forward. I was thinking of it like an archaic insurance, insurance expectation when I saw that it was very good. Did that come out of any of the initiative that you all were doing?

Speaker A: No. I mean uh, just because they're legacy doesn't mean they're not good. Right. So the technology that was there and the capabilities of the systems were good. What they weren't ready for is the AI transformation and leapfrogging our competition. Right. Lemonade is one of our main competitors, right. They're digital first, mobile first, AI first. Now, uh, use all of your, you know, and that's what, what, what I've said to the board is we don't want to be like Lemonade, we want to leapfrog Lemonade. And, and to do that we, we have to leapfrog in technology. So we have a well functioning technology set. Of course you have, we have 10 of them. Right. But we have a good technology set but we need to leapfrog competition. And as uh, such we have to take drastic measures and look at how we operate totally differently, being touchless, automation, et cetera.

Speaker B: Awesome. Now I'm going to talk about something more tactical like a quick takeaways that we can do. I think one thing I found very interesting was that one page strategy that you mentioned. I know what you're talking about, but I would love to say what is on that one page strategy that you show to the board or to anyone in your team.

Speaker A: So the one page strategy to the tech team was a little bit different than to the business team. Right. So for the tech team it was really around how do we structure ourselves. Right. And a lot of that when you're Talking about bringing 10 different tech teams together, how do we structure ourselves in an end state to support legacy and future. Right. So it had a organizational construct of how do we show what's the benefit and who would focus on what, et cetera. For the business it was, we actually partnered with PwC and we brought in what, what is sort of a user story, right. A customer takes a picture of a dog. We look at the picture and use AI to um, how old is the dog, how healthy is the dog based on the posture, what breed is the dog? We pre populate that and we showed what a journey could look like totally devoid of technology in the background. Right. They upload, the policy gets bound all electronically, no human touch billing, no human touch claims processing or medical records processing, all of that. No human touch. Right. So that we could show what that journey would look like and what are the benefits to our customers? Right. Before, so you show the customer journey, then you start to peel the onion and say, okay, what's the business benefit in terms of KPIs and metrics. Right. Loss ratio, et cetera. Right. And then the next layer down was, okay, how do we organize ourselves and what's the cost? Right. So the strategy on the page was really articulating a uh, vision for the future of what is the experience we want our customers to have that would allow us to provide the best possible experience to our pet parents and allow them to enjoy their time with some pet parents. Look at the pets as core part of the family. Right. At least culturally in a lot of countries in the West. Right. And then um, how are we able to support that in the most cost effective way and be able to have the best return from a business perspective, but then also from a customer experience. Experience perspective.

Speaker B: Very cool. It's sort of a day in the life, right? Like the day in the life of a pet parent. Yeah. Interesting. And for the tech teams, what was the, what was the configuration of that one page was like?

Speaker A: So a lot of it had about the consolidation of the teams, right. The companies, when they were bought, they were told that they were going to operate individually and separately, uh, very much the same journey as I experienced in my last employer, where they bought them, left them alone for years. Right. And then coming in and creating a shared service essentially is, is a, is a big leap. Right? So the concept of a shared service, concepts of roles that are, I, I would say are industry best practices like architecture and a, uh, cybersecurity team and a data analytics team. Concepts like leveraging a gcc. These are, I would say are fairly industry cited. They're not really earth shattering. But being able to present like, hey, here's how we operate today, right? Here's, here's how you are today with 10 different teams. Everything's duplicated at uh, different levels of maturity in cyber security, data analytics, et cetera, different maturities across them and here's how we could look like tomorrow and here's how that enables us to be able to provide a better quality of service to our customers and to our business at a lower cost. And at the same time Provide career opportunities for our employees. Right. It was really painting a picture. Right. I mean obviously we shared with them um, the day in life of what, like here's what we want from a business perspective. But as a technologist, they want to understand where do they fit in the journey to get to that. Right. You use that with the board to sell the business case and get the money. Right. But, but to the tech team it's like, well, we operate here like this today. Here's how we're going to operate and here's what the benefit is. Especially since a lot of the employees had never been in that type of a setup in the shed Services worked with offshore. Right. Many of them worked in smaller organizations. Right. And most of the career were there. Right. So while again I would say it's, it's not any earth, uh, shattering concepts, it's visualizing what their future looks like from where they are to where they need to be. Especially for people who've never gone through that journey. That was really the profound change in messaging for the, for the tech team. Here's what we need to do for the business, here's the challenges that we have today and then here's how you fit from how we operate today and why we need to operate in a different way to be able to support that vision.

Speaker B: Super. I have last three questions. We are towards the end and this is now I'm going to step and make it a well rounded conversation because so far it's about internally what you're doing and everything inside the four walls that you have. But that's not how world works. There is partners and there are people and there are skills and there are people who want to work for you. Right. So let's step out a little bit and talk about partners, IT companies, tech providers that you have. Right. You had to make two different kind of decisions. I would wonder that there would be two different sort of choices or criteria. You would have. One, how are you choosing your partners for the business as usual box that you mentioned? Then how are you choosing your new age sort of these uh, partners because those are very different skills. I have come from that world and now in this world and I see enterprise, you know, kind of timelines and the AI native timelines and AI native culture. It's entirely different. So I would love to get your point of view on what goes on in Munir's mind and how do you decide when you are sitting at this side of the table which is your business as usual, legacy systems or even modern systems. But Running in business as usual versus your native build that you're doing.

Speaker A: Um, and as you pointed out, right, those are very different characteristics in the organization. There's few organizations can do both, but not many that can do it well. Right. And so on the legacy I opted for one of the Indian outsourcers. Right. I also opted not to go with one of the large ones. Right. So I've worked with tcs, Infosys, wipro, cognizant, Right. I've worked with all of them in my career. And what I learned is it's better to be a big fish in a small pond than a small fish in an ocean. Right. So we, we picked a provider that is more medium size, that had the right experience and the right presence in North America and nearshore as well as in India. Right. So that we, the nearshore component was super important for us. Right. They have peasants in Mexico that allows us to get lower rates, but same time zone. Right. And that we were large enough of a client that we had a direct line to the leadership. To the leadership, Right. Because I've never done a, ah, tech project that doesn't have problems and never worked with a provider where things don't get dicey. And what, what differentiates one provider and partnership from another is how do they respond to, to when those challenges happen. Right. There's ones that say well, uh, cr. Right. And like get legal out and look at every word of the srw, right. And it starts to get hairy or they fess up to what the issue is and they try and go fix it. Right. So how you as a provider respond to when issues occur is super important to me. The differentiation is a partner, especially a strategic partner versus a vendor. Right. So that's, that's how we went about selecting a outsourced provider that is able to help us mid size with the right thinking, onshore, offshore, nearshore presence. And you know, in Chicago they literally are uh, across the street. It happened by accident, but literally across the street from our offices. So you can see if I can see from my office, I can look into their office. Uh, we were joking that we were, we're going to do like one of those, you know, old style Taro.

Speaker B: Yeah.

Speaker A: Cups right across. But that totally happened by, by accident. Uh, they were there and we were looking for bigger offices and we just happened to be picking us in the Chicago Loop, an office that was across the street. But it also is representation of how close we work together. Right. So they, their employees work in our office. Right. So it's a super tight relationship. So that's on kind of the legacy part. Um, when we're talking about the, the new, the innovative. Right. That's where you know, and having worked for three of the big four, I tend to gravitate. Right. And each one of the big four has capabilities in most spaces. The question is which one is stronger? Like in our case in the insurance space. Right. Every one of the big four has an insurance practice. Right. We felt he had one of the strongest insurance practices. So that's what we've partnered with and that's where a lot of the new work is coming in. They're helping us thinking through what is the art of the possible of the new end state processes. What are the technologies we need to be able to do that and to help us with the implementation the key driver change that I'm trying to institute in the organization. Before I came, vendors were driving the organization. Right. There is a view, there was a view of well, we'll just write the check to PwC or Deloitte and they'll just come in and do it. Right. And that never ends well. You need the brain power and the strategy and the direction be internal. You can consult from the outside. Right. And augment. But you can't have your direction, North Star be driven by a third party no matter how good they are. So one of the first things that I did is start to build requirements capability and architecture capability so that we have that capability internally and are able to drive with a partner like a PwC towards the future state so that we are able to control where things go gain from their experiences as we're driving to towards that future state. Um, but that's how we've kind of looked at compartmentalizing those two different relationships that require two different types of partners.

Speaker B: Awesome. I want to ask this, that moving away from vendors a little bit. I think that was really well answered and candidly thank you for that. That how you decided? Let's come to the most impacted and the most important part of the people, which is humans and people that work with us. There are a lot of talented people who would love to work for you over your teams. Right. And there's a lot of uncertainty out there. Everybody wants to work in this AI, but AI is taking tremendous amount of jobs as well. At the same time, right in your seat, you have a privilege of knowing where you're going. Right. Or deciding where you're going. What advice would you give to thousands of people in enterprise tech, right. Who want to know, who wish they could sit in my place and ask you that. Muneeb, what would you advise us to focus on? Where should we spend our skills and build our skills on?

Speaker A: I would say I'll take a Paul

Speaker B: because lot of things you said. We are building agentic, we are building native first, we are building automation, we are not building bolt on. It's the exact thing people want to work on but they're not very certain where should I build my skill skills with, where should I go, should I transition? So if you can help a little bit with that.

Speaker A: Yeah, I mean it's undoubtedly. So I'll answer kind of from a, you know I uh, have a soft spot for developers given that I was a developer for a long time. Right. I think the predictions that uh, we're not going to need developers in the very near future are perhaps over optimistic. I do think how many developers and the productivity of the developers and how quickly can roll out changes is absolutely changing. Right. Very fast. So I think whether you are uh, let's say you're a software developer learning Claude, which is you know, one of the large best out there in terms of software development or GitHub, uh, copilot, which is probably a couple tiers down but still very very good. Right. So I think if you're, if you're a software developer, understanding and learning those and how can it make you more productive so you can do things more quickly. But also how do you move up the value chain? Right. Versus sitting being a developer just pumping out code to how can I partner with the business to help them understand the art of the possible and take that to the next level. Right. So that's kind of as a developer, if you're a data scientist or data data analyst it might be learning GENIE and databricks. Right. Uh, so I think depending on what skillset you have, you need to find the right tool set that is really focused on that space that can help you be more productive and getting things done faster. But I'm biased having made that transition from sort of a pure technologist to somebody that translates technology in a business context that I see the value of what AI can do in those spaces and is not just allow it to pump up more code. Yeah, I think, I think if all, if all you do is pump out more code faster and more features faster, that's certainly a benefit. I'm not discounting that but I think if you don't use that as an opportunity to move up the stack of a value chain. Right. And going from just sitting, writing code and pumping out new features to somebody who's working with the business to suggest what features, what capabilities, then I think it's a missed opportunity in terms of how far you can take your career. So I think that that's, that's what I would advise folks to do when it comes to how do they best possession position themselves to take advantage and propel their careers. It's certainly going to have an impact in terms of how many we need of each one of those roles. There's no, no question about it. So again, everybody's going to learn it, right? Everybody's going to learn it. So how do you differentiate yourselves from a hundred other developers that are learning cloud at the same time? And this is where I think what I've seen in my career, the people who did the best in technology are the ones that are able to speak to the business in a way that helps the business get a competitive advantage out of the technology, not just purely becoming the best developer in the world or the best data scientist in the world. If you don't add that business angle, then I think you miss out. Awesome.

Speaker B: Yeah, I had a last question that I always ask, but I'm going to mix it up a little bit. You can answer whatever you choose. Part of the question. First, first, I think you're a pet parent, so do you want to share their name? And I think we want to see the human side of our leaders and C suite executive as well. Second thing is that in next two to three years, our industry is getting, I mean, you know, 10 years in, uh, lifetime is one years in AI, right. What excites you the most about the change? So those are my last questions.

Speaker A: Yeah, so we have a, uh, Bellanese cat. He's two years old, he's running around here somewhere. I'm surprised he hasn't jumped on my desk yet and walked across the camera. He usually likes to do that and sit on the keyboard and type of way. So, yeah, I've always been a pet lover. I'm originally from Germany. My family always had dogs growing up. But I did, you know, having worked in consulting for many years, I did a lot of travel so I didn't feel good about having a dog and not having the attention required. So a cat is usually a little bit less sensitive to you being gone. So had a cat for 22 years when she passed away, uh, a few years ago. And then we, we got a cat called Miso. He's a Bellanese, beautiful white chocolate point that my daughter loves dearly. So he's been a joy to have. The personality of that breed is very nice. Um, in terms of what I'm most excited about over the next couple of years, look, in my 30 plus years in technology, technology, there's always a new technology, always, right? Whether it's languages, whether it's packages, whether it's software. AI is a little bit different in that there's uh, an element of self learning and being able to work on things that we didn't teach it to do. Right. That's part of the scary part. And what does that mean for society and what jobs are going to be there in the future. But what, what does excite me in a positive way is how does that help me enable the business to be more competitive faster. Right. So my lens is always, yes, I love technology, I'm an engineer. My heart and soul is as an engineer. Understanding technology is core to that. But my lens is always how do I help the business propel forward and be able to help them every time I go into a new industry? I've worked in professional services, financial services, telecom manufacturing, automotive, credit bureaus. Right. I've worked in many, many, many, uh, different industries. And what has been common across those is that when I went into a new industry, I would always spend time to learn the business. When I went into manufacturing, I went to China and went into the plants to understand what was going on on the floor. You know, as we were talking about how we can use automation in plants. Right. Did the same thing here with insurance. I'm um, new to insurance, so I spent a good part of my M year learning the business and that's where I'm excited to be able to marry that knowledge of understanding of the business with what AI is going to evolve to over the next few years to continue to help the business move faster and faster in a, uh, super competitive landscape.

Speaker B: Yeah, that is brilliant. That's all I had. I want to just say two things. One is thank you so much for sharing openly, freely what is can be the most valuable thing. Some other C suite executive or a technical person or enterprise technology leader. Second thing is I wish you the best, I wish Iph the best on this amazing journey that you're on with innovation in AI. And thank you for being on the show.

Speaker A: Thank you so much for having me as I enjoyed the conversation.

Speaker B: Thank you.