Achyuta Ghosh — Executive Research Leader, HFS Research[00:06}
Hello and welcome back to the HFS GCC Advantage. This is the HFS Research series, where we speak with GCC and GBS leaders who are shaping the next version of the model. The idea is to go beyond the usual scale and cost narrative and bring out practical stories on leadership, talent, AI, process reinvention, and enterprise impact. Today I have Arvind Shankar from Reckitt. Arvind has actually worked at the intersection of transformation, operations, process ownership, and business outcomes. This makes this a very relevant conversation on what happens when GCCs move beyond functional excellence and start orchestrating work across the enterprise. Arvind, welcome to the show.
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[00:45]
Thank you, Achyuta. Thanks for having me. Looking forward to the discussion.
Achyuta Ghosh — Executive Research Leader, HFS Research[00:49]
Great, Arvind, so before we get into the discussion, can you tell us a little bit about yourself, about your journey and how your thinking around transformation has evolved over the past few years?
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[01:00]
Sure. I’m an operating model transformation professional, and my journey has been shaped by over 25 years of extensive experience in enterprise transformation, both in setting up, scaling, transforming GCCs as well as in transforming GBS capabilities across organizations globally and across multiple industries, including in firms like Prudential, Accenture, Capita, and now with Reckitt.
So, my career journey has been one long argument with process orthodoxy. So, I started my career in operations thinking that if you have a well-defined process and help people do it, transformation would follow. Which is partly true. But through years of transformation experience, I’ve come to realize that process is a necessary condition, it’s not a sufficient one. Right? And so my outlook on transformation has evolved to that transformation at its core is all about change. And to have sustainable change, it’s all really about making sure that you have shift in mindsets. You’re doing shaping the culture and you’re ensuring that it. You know, you help people embrace new ways of working, right? As it evolves.
So, I think today when I think about transformation, I think about it from a human-centered lens and from a business outcome perspective, right? So while productivity, efficiency again are necessary conditions, they are not the only value levers. I think the broader question is how can you enable the enterprise to move faster, grow faster, innovate faster, make better decisions at scale, deliver better experiences for stakeholders while reducing risk for the enterprise. So, I think it’s about delivering 360-degree value across your enterprise and how transformation enables that. So, I think that’s probably been the biggest evolution where the shift to a human-centered business outcome-based transformation it is where my thinking has a lot.
Achyuta Ghosh — Executive Research Leader, HFS Research[03:24]
I think that’s a great start to the discussion, Arvind. And moving on, there’s a lot of discussion today about GenAI tools, Copilot, automation, right? But the bigger question today may be how talent itself is being redefined. And how do you really see the future of talent model evolving? And what does AI fluency as such really mean in practice for GCC, GBS organizations?
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[03:54]
Yeah, I think sometimes we conflate two different things. So, on one end, AI it’s about AI literacy, which I think is table stakes, which is all about knowing what tools exist, broadly knowing how those tools work, and not being afraid of using them, you know, at an individual level or at a collective level. For a knowledge worker, that is table stakes today. It’s similar to computer literacy or spreadsheet literacy in the eighties and nineties, right?
The second part, which is where things get more interesting, is the capability of AI orchestration. And fundamentally, I define that as taking a complex business problem and breaking it down into parts and knowing where to leverage AI agents for which parts and delegating it to AI agents, as well as knowing where to leverage human judgment, and then being able to stitch that together to deliver a reliable consistent outcome for the business, right? Which is a very different and it cog new cognitive skill in itself.
And very few organizations are very intentionally focusing on developing that. There’s a lot of focus on new technology, investing in technology, but I think the future from a is more about talent. And you we need to redefine roles with a view to the future which is, you know, a an AI native future, but it’s also about reimagining operating models that enable that future. So, I think it’s this is the talent model to me is about skills that will be relevant in the future is about orchestrating both effectively as we move forward.
Achyuta Ghosh — Executive Research Leader, HFS Research[05:39]
Thank you, Arvind, for your inputs. What capabilities are becoming more important today? Is domain expertise really enough today in what you do at a GBS or a GCC?
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[05:54]
Sure. Yeah. Absolutely. I think domain expertise continues to be relevant, but again, it’s just a necessary condition and not a sufficient one, right? I think what is missing in the conversation is how we incorporate organizational context, tacit knowledge within the organization, how we bring unique sets of data, not unique data sets, but unique sets of data which is both structured and unstructured data within the organizations together, and how we can orchestrate across all of this to connect people, process, technology, data, et cetera, to deliver outcomes. So, I think that is a developing skill that we need to enable our process organizations, our domain expertise to be able to be effective.
Achyuta Ghosh — Executive Research Leader, HFS Research[06:37]
Great. Arvind, at HFS, we often talk about services as software and generative enterprises, which we feel is what a GCC should really become. So as AI becomes more and more embedded into workflows, how do organizations actually move, say, beyond isolated AI initiatives to build enterprise-wide orchestration capabilities that really create business value? And you could share some examples from your story also.
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[07:02]
I think very. Sure. I think the pilot problem or the pilot issue is a real issue. Every organization that I know of has lots of proof of concepts and pilots. Most of them don’t scale. And the issue usually is not technology. It is about the operating model around the technology.
So I look at AI maturity the same way as the evolution of a GBS across the over the years, right? Where it moves from activity to process to outcomes, right? And in HFS’s own words, to a generative business service, right? So, in AI also I see the same evolution where you automate tasks first, then you move to a process end-to-end process orchestration, and then you move to an autonomous AI agent-based workflow where it it is orchestrating outcomes across the entire organization and across functions.
The in our experience and deploying AI at scale across functions. What we have found is that organizations don’t move straight to an agentic operating model. You first start with a deterministic model where you build governance, you build trust, you build reliability before you move to reusable agents.
The second aspect of this is around data. With LLMs, where it’s not just about structured data. Unstructured data in the form of knowledge artifacts, in the form of conversations, in the form of documents, are also enterprise assets, and we need to figure out how to use them effectively, govern them responsibly to deliver insights and outcomes faster for the organization.
So, if you take a few examples from our context, in R&D and regulatory workflows, activities like medical dossier creation or test protocol creation. Which used to take you know hundreds of hours, we now take a fraction of that time. More importantly, it frees up scientists to focus on more innovation, more newer products, better testing and simulation.
Similarly, in our marketing and AI concept creation, by bringing multiple data sources together, and both structured and unstructured, the speed to insight and the speed to concept creation has drastically reduced. Also, this quality of concept creation has gone towards.
This also frees up our marketers and innovators to focus more on empathy, creativity, as well as meeting our consumer demands, right? And using the needs of the consumers in a more effective manner, which helps us move towards our vision of putting better health in more hands every day.
Achyuta Ghosh — Executive Research Leader, HFS Research[09:53]
Makes sense, Arvind. Also, historically, GCC, GBS organizations have built around process and functional ownership, right? But today, I think the conversation is increasingly about connected enterprise outcomes. And that’s what our model also states, our generative enterprise model states. So how does the operating model need to change when success is measured, not by process KPIs, but by business outcomes? Any examples you want to share would also be useful.
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[10:21]
Sure. I think I just read an article today morning from one of your colleagues, Saurabh, where he spoke about GBS reign BOSS, which translates into business orchestration solutions and services, right?
I think a GBS operating model done well because again you’ll find GBS across the spectrum where people focus only on SLAs, efficiencies, where you get only incremental value. And then you have the leading edge GBS models, which are true. Enterprise value creator, right? Which are really drive outcomes and orchestrate and connect the across the enterprise data, people, process, AI and technology to deliver and end business outcomes. So, I think the GBS, true GBS organizations which aspire to do that, the post and position in the right way and are empowered in the right way can deliver that.
I think there are three or four ingredients to make that happen, right? Which anything you measure improves. If you make sure it’s part of people’s responsibility, and to how you incentivize leaders, right? So, in the GBS context, the GBS leaders need to co-own business outcomes. If you’re only measured on SLA or cost efficiency, that’s all you will get. But if you’re measured on business outcomes and you co-own that, then you will get you know meaningful outcomes and as a true value creator.
Second is I think the end-to-end model or the GPO ownership; process ownership is critical. But many organizations, you know, put a set up that role. And my as my one of my friends, Deborah Kops, to use her term, many organizations, GPOs end up being referees or nannies rather than true value creators. It’s important to empower them and to make decisions and put it at the right level where they are change agents, right? And can orchestrate true end-to-end workflows across the whole organization.
The third element is how you incentivize, right? So, if you’re incentivizing for more efficiency, you’ll get more efficiency. If you’re incentivizing for experience, better insights, your true growth, revenue enablement, then the behaviors align towards that. So, I think these are important aspects to take care of. To enable that operating model. And a GBS operating model, I think, is has the right ingredients to deliver to that outcome.
And I want to take one example that from a Reckitt standpoint, I think if you put data, AI, and GBS together, it’s a very powerful combination rather than you know keeping it in is in its own silos. And in Reckitt, we’ve been very intentional about it, where AI and GBS report into the same executive is part of the same team because we see one together they not only redefine the organizational workflows but also how work gets done in Deliver.
Achyuta Ghosh — Executive Research Leader, HFS Research[13:28]
I think that’s a very good move getting the same person to actually lead both AI and GBS because that ensures that there is perfect synergies explore from there. From an outlook perspective, looking ahead, organizations will need to orchestrate business teams, AI platforms, agents, service providers, external partners. So, what will distinguish organizations that succeed in this environment from those who will struggle in this environment?
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[14:00]
Yeah, so I look at it as three things, right? So, one is architectural clarity. Second is I call for me I term it as enterprise rhythm. And third is adaptive leadership, right? Architectural clarity is all about knowing what to build on your own, what to own yourself, what you leverage the ecosystem and partners for and how you set up the governance and the feedback loops so that all of this you have end-to-end visibility and you know what the left hand is doing and what the right hand is doing. So again, it comes down to both governance, feedback loops, and the orchestration from an end-to-end standpoint across the ecosystem, both internal and external. And being very intentional about what you build and develop versus what you outsource.
The second part is the enterprise rhythm, which is all about governance, it’s all about the feedback loops, it’s all about making sure there’s the process and orchestration governance all sitting together and in squads rather than it, you know, getting mired into bureaucracy.
And the third is means this is an evolving situation. Leadership, it’s about learning agility and being able to adapt quickly. Whereas the situation evolves, people need to be able to progress over perfection and make changes as needed. No one has all the answers. So, I think leadership. Being receptive to have and being agile to take that feedback and make course corrections is important as well. I think that’s what would largely separate organizations that lead versus organizations that lag.
The second thing, as I already mentioned, I think in one of the previous questions, is everyone has access to the same AI fund foundational models and LLMs. The differentiation comes in how we leverage tacit knowledge, organizational context, unique sets of data, and how we stitch all of this together within that organizational context. I think that’s where the competitive difference between organizations will come. And that’s something we have been very intentionally focusing on and you know from day one as a principle within the organization.
Achyuta Ghosh — Executive Research Leader, HFS Research[16:10]
Well, Arvind, thank you for joining us and sharing your perspectives. What I found most useful in the conversation is the focus on orchestration. I think the next phase of GCC/GBS evolution will really need leaders who can connect process, technology, talent, AI outcomes in a more integrated way. You shared great examples in your story also. So, thank you again for being a part of the HFS GCC Advantage.
Arvind Prabhat Shankar — Vice President, Global Business Process Transformation, Reckitt[16:37]
Thank you, Achyuta. Enjoyed the discussion. Thanks for having me here.
