Reckitt's Varun Kakaria On the New Expectations for CIOs

Transformation inside large organizations almost never happens at once. Instead, it's usually thanks to steady shifts, whether that's in leadership mindset, data strategy, or how tech teams partner with the business to drive impact. In this episode of Tech Transformation, I'm speaking with Varun Kakaria, North American CIO at Rekit, about what it takes to lead transformation inside a global company, from building stronger data foundations to scaling revenue growth management.

We're talking about deploying AI in practical ways, helping teams adapt to new ways of working, and the new expectations for CIOs. Stay tuned for that and more on this episode of Tech Transformation. Welcome to Tech Transformation with CGT, where we take a look at some of the trends and innovations that are impacting consumer goods and retail. I'm Lisa Johnson, VP of Content at CGT, and today I'm excited to be speaking with Varun Karkaria, North American CIO of Rekit.

Varun's been with Rekit for about 12 years in a range of roles and through a lot of change. So he's here to talk about what it's like leading through that change and some of the things they're focused on right now. Varun, welcome. Thank you, Lisa.

It's been an honor to be here. So it's really great to have you here. I know some background. I know we've been trying to get this on the calendar for quite some time.

So I'm thrilled we were able to make it work. Very excited that you're going to be at Analytics Unite. But for now, let's start off by talking a little bit about your background. So you have spent, as I mentioned, you've spent over a decade in RECIT.

You've been in both global and regional roles. So we'd love to talk about that, what you've done in the past, how it's shaping what you're doing today, and what it's like leading regionally and globally. That's a great question, Lisa. And I've been fortunate enough to go and understand both sides of these coins.

In fact, three sides, because I've been into some commercial roles as well in my early career. And what it has given me is a bit of a diverse perspective, because we, in a lot of companies, struggle to bridge this gap, because global seems to be focused in their own priorities, which are central and more headquarters in nature, and markets have a business to run. And when you see both the sites, we are all working for the same purpose. And that's where the most important thing that came out in that journey was, how do you develop a shared success mindset?

And that's a twofold question. One is for people, because the teams are working and they have to collaborate together. And what we have done in the recent years is invested that a lot. And that's part of our operating model.

But also then you need to have the right integrations, as we call joint business planning. And these help a lot. So I really value these things. That one, how can we kind of unite the planning aspect?

But in the year when things happen, when things shape up, if the teams are working collaboratively, they end up delivering a common purpose. And sometimes you have to understand each other. There are priorities from both ends. So that's one big area, I think, which has influenced my thinking and my leadership style.

also. And then for me, learning across the globe, being fortunate to work across the globe, we also realize one size doesn't fit all. You have cohorts like Europe and North America might function differently. ASEAN markets might function differently.

So you need to start thinking on archetypes and try to tailor things for that. One size, as we said, it does not fit all even in real life. So that's a new approach that we have tried to take and address the standardization question versus what is required for solving the business problems at hand. And last but not the least, we cannot undervalue the importance of change management and value.

Every program, whether it's a region or whether it's a globe, everybody's looking for adoption of these programs, how they can deliver value for me. So you need to heavily invest in change management and making sure people are well trained, the programs are well received, and ultimately deliver value through these programs, whether it's productivity or growth, and a strong mechanism to sustainably measure the success and value of these programs. So broadly, these are my learnings.

And this has also influenced my leadership style, just to end it. Because I think working with diverse set of people, I almost kind if I say it's a human first leadership style, where if the right people are motivated and working with you, it's almost like the third pillar. If you call innovation and operational excellence as the main two pillars, people are the third pillar. So I think diverse teams, motivated teams are a key to deliver success, whether you are in regions or globe.

So that's my answer. Yeah, no, and that, you know, you're really hitting on people process technology. You hit on all of them. You have talked in the past about how the CIO role is evolving.

It's evolving fairly rapidly. So what are you seeing? What are some of the shifts that you're seeing and how technology leaders need to show up today? So CIO traditionally has been called the chief information officer.

And I think now, I mean, if I take a pun, it is becoming like a chief impact officer. That's the transition that I see. All right. That's convenient.

It's important because I think if we don't have impact, any of the roles, then it becomes pointless, right? So in my view, again, what I have seen when I started my career in the very beginning, technology was technology and business people was IT and business were two different animals, right? And what has started happening, not very recently, but fairly recently is there are lines between technology and business that have started to blur. I mean, it's either ways.

Business people cannot do without being technology savvy. And similarly, the roles of a CIO or any technology leader cannot do without learning business, right? So it has to be both ways. Because for me, we are not all about systems delivery.

While traditional technology is important to kind of give us the right foundations of cyber, infra, but you have to quickly evolve to be business partners with your teams, understand business problems, solve them together with them, and in fact, help them enable better business growth through technology. So I always tell my teams that let's not do something which is not solving a business problem or which is not giving a business benefit because you are not here to deliver tech solutions for the sake of justifying technology.

So that's an important thing which I see all CIOs or all tech leaders must appreciate and I think they are now and what I think as we go along as AI comes along as you know e-commerce and other businesses come along we need to be really business advisors for them because sometimes our business leaders who are doing fantastic work earning for the company are so involved in delivering that the next big change the advice we need from people like us or technology leaders to tell them what can technology help you with.

With AI coming in, a lot of us do not even understand what AI can deliver for us. A lot of us have fear on what we can do. So I think that role from a systems delivery partner has already evolved to a business partner or a technology-based enabler to becoming a role of an advisor is my view around this. Right.

No, I mean, that makes sense. It seems like a lot of this groundwork was already being laid and then the rapid use of AI is just accelerating its need. So that focus that you've talked about, becoming a business partner, that focus on the commercial impact for your role, I mean, that really sets the stage for one of the most powerful growth enablers, and that's revenue growth management. So it's a core component of your role.

Many CPGs today are eager to deploy RGM solutions. So in your experience, what are some of the best ways that you believe are, what are some of the best ways to approach this journey and some of the paths that organizations should take? So you rightly said revenue growth management is a key pillar now. And revenue growth management entails not just tech solutions, but a combination of business processes and tech solutions.

But broadly, if I talk about the RGM, the way we call it RGM in Racket, the way it shapes up is around areas around customer planning. When I say customer planning is the decisions we take around promos that we give or pricing or trade spends that we do with our customers. So kind of formulating those strategies from a logical and, you know, kind of data-driven decision perspective have become very important. No longer the times where you want to decide on pricing, on what impact will have when I increase my price, will my consumers take more volume of it, less volume of it, will I be negatively impacted?

Those decisions used to be humans. And we obviously did not have the power of years of data or other trends that we see in the market. Revenue growth management tools give you that power of making those, still have that human element of decision making, but give you a lot of aid around how to take those decisions. Now, if I talk about the journey specifically that we have taken in Rekit, and there are other companies who are going through that journey, but I think we took it, I think, on an accelerated path.

We thought of RGM not as a one-off capability. We thought of it as a strategic capability that has to be sustained from a long-term perspective for the company. So we did not take the approach of, hey, let's do a small pilot and then we'll see what happens. We thought this was a strategic capability.

Let's take the step forward because we have realized these decisions are very important. So we invested in building this capability in-house. We definitely involved a strategic partner because we needed to ourselves learn on both the technology element of it and how to embed it in the operating model, as I said before. So we did take one of the key partners and they are very good at this.

But we, in the very beginning, also told them that our intent is to run it ourselves, right? So we invested in two kinds of capabilities. One is the post-facto analysis, which we call the core RGM, where you have data driven ROIs on promo, your pricing techniques and your, you know, kind of trade spends analysis. But then we realized that some of our markets are so advanced that they're ready for predictive or, kind of AI-based predictive models around this as well.

So for example, in US, we are able to use advanced tools where we can take pricing decisions based on what-if scenarios, on what impact we will have in our future business. And we co-developed those tools with the partner that we had. But importantly, what we did was slowly we transitioned and trained our internal teams to build this capability in-house. And as of now, we run this capability from Rekit itself, from a technology perspective.

So yes, we took a hybrid approach and that worked for us because if you just take a build approach, or sorry, a buy approach, which is basically your licensing, you cannot really customize it to your own needs in the future because your segments and categories might change. Then from a capability perspective, we kind of married both the processes, as I said, with the tools. So we did heavily invest in tools as well, which are technology tools. But what we have done is every market that we have gone to, we have first set the processes right.

We have done trainings, which are black belt certifications, and then kind of sustained the momentum by with people kind of making sure the tools are being used for at least season one, let's as we say it properly, and then we hand it over to the market. and last but not the least RGM it was not without challenges that's what I would like to say that some people who implement it and I've done a lot of reference calls with other companies as well who are looking forward to implementing it the biggest challenge is how do you get your data right and I think we should heavily invest before even beginning this program because a lot of data needs to be harmonized they need to be refreshed in the right way So that's the last part I would say.

Could you, yeah, could you build on that last part? Because we know that data is the, it's the bedrock of all transformations, right? Having a solid data foundation. So what are some of the key steps that you took to really enable, to get your data where it needed to be?

So we have invested in a data lake already, which was the foundation set. But as we went into RGM, we realized we needed a heavy focus on customer data. and we needed, the worst thing we found was when you take external data specifically around market share and or customers, they are coming in very different fashions. So for me, the biggest learning we have done is how do you win data harmonization and the recency of data, invest in the recency of data because your RGM tools are as important as you have the latest data in them, right?

So what we did was, again, We invested in a data layer. We invested in a harmonization capability of data. We have focused on reusability of data by centralizing it and making it reusable for many countries. And what we are already doing in the process is kind of centralizing some of that differential data that we have across markets into hopefully a single stream that can make it usable for other programs as well, as we think of joining marketing, for example, and sales RGM data as well.

So you've led sales execution across 48 countries, which is huge. So how does working at that scale influence the way you think about actually operationalizing transformation inside a big, complex organization like Racket? So sales execution is an important part globally for us. And hence it looks like we were able to do something standard around 48 countries but it was a journey in itself right So it has really transformed the mindset of how do I even approach generally any technology solution because it was a challenging journey first of all We applied all of that, what we had spoken about in the beginning on archetyping, what we had to do, and just to elaborate on what we did so that it's clear on what I'm talking about.

So sales execution means for us, when we go out into the stores to sell, how can we kind of perform better and not just do growth for us, but how do we grow the category as well? And what it entails is if you talk about, for example, emerging markets like India or Brazil, we have a distributed environment where we kind of send our reps to the stores to sell products or merchandise products. So if you can put solutions which can help increase the efficiency of our distributors or our reps to perform better, that's the solutions which I'm talking about.

the second bit is we have a pharmacy or an otc business where we have education to do in some of the medical spaces some of the pharma spaces and then we have to obviously sell products as well and then markets like europe and north america we need to really make sure our products are visible on the shelf uh you know we help the categories kind of be uh available to our customers. So we have solutions which we can get there as well. But since you asked, I think your question was more about how do you operationalize and manage?

Yeah, at more of a local level. More of a local. So we started with the approach of global working with local closely to understand what are the nuances in the business, because otherwise we could have not tailored the solution. But we still kind of took that capability mindset to take the baton in the global team's hand.

And at that time, I was leading that global team to develop the solution with vendors who are reliable and who are capable to develop these archetype based solutions. Because if you start developing solutions locally, then at the end, the whole data journey and the inside journey also gets impacted because then you, again, are increasing your problems of multiple solutions, multiple management of solutions and data. So we took that approach of centrally developing, but listening to the markets, developing for the markets and their benefits.

what we did was since we hired experts on how to kind of deploy these solutions the initial kind of onboarding and piloting of these solutions and we i would say co-piloting of these solutions with the markets we did with us being very very heavily almost like a high touch versus a low touch but in the process we focused a lot on training and change management to the markets where they became the local heroes to really scale and sustain these solutions. So that's the common approach we took with all of these three solutions.

You know, as you're looking ahead in your North American role, what are some of the key priorities that you're most focused on right now or just in the near future? We have deployed, in fact, almost most of our markets, which are distributor-based, a handle-based solution for our reps and for our CRM, for our distributors. in markets like North America, we have merchandising solutions in place which help influence self-availability and better self-execution. So coming to what are my other priorities in North America, from a North America perspective, when I joined in, this is one of our most data-rich markets that we have in Rekit.

And it's a very evolved market where people want to look at the right insights before they want to take a decision. And that was a challenge also, by the way, because when people want that, your business teams are nice enough to want to use data to make their decisions. You need to give them that as well, right? So what is an opportunity is also a challenge.

These words are interchangeably used. So for me, I think the biggest priority that we have achieved, I think, and we are still kind of in the midst of it is solving the data challenge, which availability of data, bringing it together the right way was a big challenge, right? So that's the fund. And I try to learn from my past to first set the foundations right.

But then we invested heavily in some of the mistakes that we do. We end up making, I mean, when we say, when I see my ecosystem, there might be 30,000 reports sitting in the whole record ecosystem. When I go to North America, there were 500 reports that we had initially, right how do you streamline insights which are more relevant which are more usable that was the first journey we took and by the way I've been lucky that my business counterparts have been very very supportive and savvy around this intent so we partnered with a leader in my business team to streamline what are our forums what kind of reports and cockpits we should use what kind of Decisions, though, should be coming out of the report.

And we designed that whole ecosystem first. And then from a technology perspective, we did a very innovative thing. We definitely developed these insights, which was a big journey in itself. But we said, when you have this, it's almost like you ask in your home, right?

Where is this book lying? And you start finding the hole in the room or something you have lost versus something telling you, hey, go there and fetch that, right? So we tried to make a place, one single place, where you can access all of these insights. Imagine if you are the CEO of the company, you don't have the time to look for these things.

So we launched a project called Atlas. We called it Atlas because it helps you navigate the right insights. And it's like one URL, which is atlas.recq.

com. My CEO doesn't have the time to know anything. He will just go to atlas.recq.

com. There is a guided thing on where you need to find whatever and you just use it. And to the extent now, I mean, just speaking on a lighter note, my CCO and CEO are amongst the top 10 users of reports themselves. That must be great to see.

Exactly. I mean, you would have typically analysts kind of sending reports to them, but they use it themselves. So it's a great achievement on their part as well. I guess the only follow-up question I might have is if you're able to talk about, you had mentioned some of the obstacles you've encountered during this.

anything you could talk about what you've learned any missteps that and learnings you've had yeah so I think we I mean I we had a lot of missteps we took in terms of as I said setting the foundations right right we have to make sure the insights are relevant and this is in fact more relevant when I because I think I mentioned one of the journeys we took but if I talk about data as a holistic learnings that we had in North America, we are actually into two more important things which I can give you these learnings about.

One is the Gen AI piece, which is very important. A lot of people talk about Gen AI, but what we have done is try to kind of scale it to become usable. And then the next thing is how our retailer landscape is changing because of some of these data elements. So what we started was how do we kind of use Gen AI more from productivity And when you say productivity it also is how do you make people smarter and make their lives simpler That's what my philosophy is about Gen.

AI. So we started with marketing and we thought, how could we give marketers our brand insights and brand planning easier? When we started that journey, we thought we know it all, right? We had interviewed people.

We knew from, as we say, external references. And we brought a central solution, which we thought marketers will be delighted and they will use it in their daily lives. When we launched that solution, great response. They saw the power.

And then you see slowly the buzz started going away. Right. You did not see that being used in daily lives. They were occasionally being used.

And the shine wore off. Exactly. You know, like shiny new shiny object, not giving the shine anymore. So I think we had to literally do a deep dive.

While Atlas, which I talked about, became a success because of the simplicity and the learnings we had done with this part, this was a big deep dive and a learning experience. So we realized a couple of things. One, when we get smarter, even the people who we are working with also are leveraging AI in their own daily lives. So if there is a Nielsen data coming, they're already putting co-pilots on top of it and getting those insights.

So we had to be smarter. The commentaries had to be better. The second thing is the whole thing which I talked about operating model. What the insights they are getting through that Genesis tool, we call it Genesis as the program.

Are they relevant to their business reviews? Are the managers going to ask those same questions to them? So that becomes very important. And last but not the least, who is the driver of this?

The VPs of our categories, if they are asking those questions and if the thinking on their reviews is embedded, only then the junior managers or the brand managers will start using the tool because I, as a head of the function, I'm asking those questions based on my thinking and the tool is giving me those insights. So we used to call it, we are calling it business tacit knowledge, right? So we did some deep dive. I think there were elements that we needed to add in terms of data sets.

We needed to bring some of this top-down way of thinking into the tool and we had to make the commentaries more sharper and more user-friendly to operate, right? Because if you start dumping, If you see all the chat GPTs and, you know, co-pilots, they just have one prompt. You ask anything, they bring insights to you. So, I mean, I'm not going into details, but some of these learnings we have incorporated and we are about to launch the version two of that.

And hopefully that should really, really drive. And we've got really, really positive response on those things. And so that's the learning. and last but not the least we are applying the same learnings on the retailer landscape some of the people who are in north america if they are hearing there are retail giants like walmart and target tying up with chat gpt and i think we are not just thinking past we are thinking ahead on how do you kind of become their partners in evolving generative engine optimization or how do you kind of become partners in using that technology to help grow your categories?

And I think this is a new thinking that all of us will have to do at some point in time. So I'll stop at that because I can speak on and on on these topics. But that's the three priority areas for us. Perfect.

No, thank you. Okay, so we can start wrapping up a little bit as we start to wrap up a little bit. When you're talking about learnings, we'd love to kind of go back to talking about your learnings as a leader. So if hindsight is 20-20, right?

It's always 2020. What's one hill you thought you needed to die on in your career? And now you look back and you think, yeah, I probably handled that a little differently. That makes me think.

I think probably I'll hit beyond the work aspect, right? Because I think we've talked a lot about projects and programs and capabilities. As a leader, I think when you're growing up as a leader, you take a lot on you, right? because you want to be seen as a person who knows everything, who does everything.

But then as you grow, you become also a people leader. And I think it's important that you make everyone grow and not just be that person who's trying to control everything. So the one learning I have is how to give up micromanagement and start entrusting your teams with doing the job. And I have a different wording for it.

a lot of, you know, HR wordings talk about freedom to succeed. I talk about a thing called freedom to fail. Because if you give that opportunity for your teams to learn and perform and give them the safe space to sometimes fail with the right intent, I think that's the journey I would, I would take the learning and improve upon. Because initially, I used to do a lot of things myself, you know, kind of just make sure everybody follows that path.

But now I've, as I've grown as a leader, I try to more delegate. I give this freedom to fail and freedom in a box. And let others do the problem solving as well. So that it gives me, by the way, it gives me an advantage of giving more time to think of strategic priorities, next steps, engaging with the leadership.

So it's a win for both the aspects. And I think it's a leadership style I would advise everybody to think about. Yeah, for sure. Great vision.

Certainly not easy to learn over time. Yeah. Okay. So final question.

And love to talk a little bit about what you're going to talk about at Analytics Unite. We don't want to give the whole thing away. But Analytics Unite, just again, it'll be April 7th through 9th in Chicago. We are back at the Drake.

So if you want to, you know, for anyone who's going to be there, you're going to be kicking us off on that first day. So can you just talk a little bit about what you're going to share while you're there? Yeah, it's one of my favorite areas that I've done a major part of my career in, as we say, sales execution as well, being part of both business and IT. So I'm going to talk about how, and I'm not going to give it away too much, but how do we transform the way we do our in-store execution as I spoke to you about.

This is very important obviously for making sure our commercial growth is happening. And we have practically used AI to kind of how do we drive interactions with our stores through our people and how we have transformed the way we do it. And we are naming it as smart execution. So I'll stop at that.

But it's really interesting. And it's not something that I've done before. And this can really help change the way we execute in our stores. Well, we're very excited to have you there.

For anyone who's listening, would like to learn how they can join us, they can go to analyticsunite.com. But for now, Varun, thank you so much for joining Tech Transformation. Very excited to have you speaking again at Analytics Unite.

Thank you, Lisa. It was a pleasure speaking to you.