S2E1: #ONTrigger with Shanker Selvadurai, VP & CTO of IBM Technology Asia Pacific

Reading Time: 20 minutes

Catch Shanker Selvadurai, Vice President and CTO of IBM Technology Asia Pacific, in an exclusive conversation with Sanchit Vir Gogia, Chief Analyst and CEO of Greyhound Research, on GreyhoundTV ONTrigger, our peer-to-peer dialogue series. In this exchange, Sanchit (SVG) spoke with Shanker about the Client Engineering team formed by IBM to enable experiential selling and help clients co-create solutions in a true MVP fashion. Here’s a glimpse of the topics the duo chatted about:

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SVG: Hi, everyone. Thank you for joining yet another episode of GreyhoundTV ONTrigger. First of all, my apologies. I know it’s been a while since we brought you some new content on this platform, but trust me, we’ve been swamped for the proper purpose, thanks to Generative AI. Our maximum time in the last quarter or so has been spent on CIO advisory on Generative AI. So that’s what’s kept us busy. But be rest assured—in the coming quarter, you’ll see some amazing content on Greyhound TV ONTrigger again. I’ve got a wonderful gentleman with me to kick off this new season. He’s Shanker Selvadurai, the vice president and CTO for IBM in Asia. Shanker, welcome to the show.

Shanker: Hi, Sanchit, thank you for having me.

SVG: Since you’re the first guest in this new season, you’re truly special for the session. So, I’m going to make it easy for you. I’m not known to make this easy for people, but I’ll keep it easy out of respect and thankfulness. Before we talk about IBM or your role at IBM and, of course, the topic of client engineering, which is what this is all about, let’s first talk about you as a professional. I know you’ve spent north of 30 years in the industry. You have experience in Europe, Asia, the Americas, and worldwide. You started your career at AT&T, NCR, and Fujitsu. You have done the ropes. After 18 years at IBM, I would say that’s not just one IBM; there are many flavours of IBM, right? Now, if you were to characterize these 18 years in, let’s say, a few folds, what would that be from your eyes?

Shanker: when I joined IBM in 2006, the tech industry started embracing the cloud computing revolution. Since then, we’ve seen numerous transformations, from the rise of mobile devices and big data analytics to the emergence of AI and quantum computing. I believe continuous learning is essential to keep pace with these challenges or changes. This means staying informed about the latest technology trends and, of course, IBM’s offerings.

I do this by reading industry publications and podcasts and networking with folks like yourself, peers and thought leaders to broaden my perspective. The key to this is being open-minded, adaptable and flexible. I think it’s crucial to keep pace with change right now.

For instance, when we started exploring Generative AI with clients a few years ago, some were sceptical about their potential impact. But by keeping an open mind and embracing emerging technology, I think we’ve been able to help our clients transform their business in ways that would not have seemed unimaginable just a few years or short years ago.

Another source of inspiration for me while working here is the opportunity to work with talented and innovative individuals at IBM. Even our team consists of some of the brightest minds in technology.

SVG: Yeah, I must compliment IBM—I do that on every other analyst call with IBM. The fact that you guys kept investing in forward-looking technology, even when the company was bearing losses, is a commendable stand, especially for a public limited company that constantly has an onslaught of stakeholders and shareholders. So, a big thumbs up to IBM for that. However, you mentioned clients, and you have a very important position within IBM, the CTO’s office.

Now, when you sort of step into client situations, I’m sure you see the spectrum, from traditional mainframe to Cobol class clients, and then there are the cutting-edge GenAI clients, right? Now, from that spectrum, where do you think client expectations lie? One is that. Second of all, how do you think client expectations have changed overall? Because where the conversations were a few years ago were all about tech outcomes per se. Today it’s changed multifold. So, please provide us with the spectrum of clients you work with and their expectations from you, your office, and IBM.

Shanker: I might provide context from an Asia Pacific perspective because that’s where I’ve spent most of my time in the last few years. I’ve worked with clients from various industries across the region during this period. Over the years, I’ve seen fundamental changes in technology, business, and financial models that have impacted the industry, especially client expectations.

• First, the shift towards cloud computing has been one of the most significant trends in recent times. With the increasing adoption of cloud services, I think this is no longer tied to traditional on-premise IT infrastructure, that’s for sure. Trends like SaaS, PaaS, and infrastructure as a service have become essential for businesses looking to modernize their IT infrastructure.

• Another trend that has had a real impact, especially in the last five years, is the rise of artificial intelligence and machine learning technologies. AI and machine learning transform industries by enabling businesses to gain deeper insight into customer behaviour, predict future trends, and automate complex processes. This has led to a greater focus on data analytics and data-driven decision-making because the basis of all of this is data, driving demand for more advanced analytics tools and services.

• Another thing I’ve seen is a shift towards more flexible business and financial models. For instance, subscription-based pricing models have become increasingly popular, particularly in the software industry. Now, businesses can pay for software on a recurring basis rather than making a large upfront investment.

• Another trend is the emergence of fintech companies, particularly in the financial sector, that are disrupting the services these large traditional financial institutions provide by offering more flexible and agile solutions to their customers.

• And the last thing I would say is that there’s been a tremendous focus on digital transformation, which is essential for businesses to remain competitive in today’s evolving marketplace. Digital transformation using technology fundamentally changes how businesses operate, from streamlining processes and improving customer engagement to creating new revenue streams and driving innovation.

SVG: Before we go on to a specific topic of the team you lead, I want to have a small counter. As IBM transforms from a mainframe services company to a hybrid cloud AI company, many clients do have a fair bit of cynicism. I hear a ton of pushback sometimes. Maybe it’s just a notional pushback, or maybe it’s a lack of education. But how do you work with these clients who probably haven’t fully understood what the new IBM stands for?

Shanker: Yeah, it’s interesting you say that. One thing that probably we could have done better, I think, is that when companies were looking at the technologies, I would say the more contemporary technologies at the moment, I think what’s happened is that I think IBM may not be as obvious to them because a lot of these companies, like I know some of the companies have been aware of hyperscalers, had a lot of influence over the consumer type of customers. That created a lot of momentum for them, even in the enterprise space.

We invested a lot at IBM in newer technology like hybrid cloud and AI. But I think it was not that obvious to some of the enterprise clients because, at the end of the day, if you’re a consumer, when you go to work, you become an enterprise user. But I think the experience you had the consumer bring into the enterprise is where the other technology providers had a leg up.

But having said that, it’s important to see how we have shifted. One way to look at it is the kind of research and work we do in different spaces. For example, you can look up the most recent patent on Generative AI. IBM has the greatest number of patents on Generative AI. I think it’s about almost three times the closest in terms of patents from another technology provider. So we continue to invest in R&D, but maybe we are not as obvious as the other technology providers here.

SVG: Well, that’s nothing new with IBM. IBM has been the top patent provider for the longest time. I think filing patents has never been a problem for IBM. I think that’s been the forte. Right?

Shanker: You know, that’s interesting. But about five years ago, we took a different decision because, you know, we moved into open source and acquired Red Hat. We decided that, you know, we’re not going to pursue that patent just for the sake of acquiring patents. We made a conscious decision, and I think you would have seen in the last five years that IBM has dropped from an overall technology patent perspective. So, we desire to invest in areas that we think are critical only. So, for example, GenAI is one space that we think is going to be, you know, important and will make fundamental shifts in the future for the organization enterprises. So, we shifted our focus to where we will do more research versus generally trying to file as many patents as possible. 

SVG: It correlates well with IBM’s move to become more ecosystem-centric because it was all about eating all it could. Now, let’s share and eat it all together. So, I think the attitude and outlook toward patents also align with the ecosystem strategy. So I think it’s a good one there. But you spoke about changing client needs and expectations regarding financial outcomes. At the same time, we spoke about changing IBM. Is the client engineering team a natural outcome of these two changes, or what’s the genesis? Please give us a sense of where the idea all started.

Shanker: I think you’re spot on. In terms of change, the whole idea behind client generation comes from the changing landscape of client expectations. It’s been a critical factor in terms of forming this team or organization. The rationale was to shift more from traditional sales techniques towards a more experiential selling model where clients can co-create and experience the value that IBM technology brings to their business. 

To make this happen, we staff the client engineering team, or what we call internally CE, with a diverse set of skills. For instance, designers drive aspiration and create engaging visualizations of potential solutions. We also have business technology leaders who demonstrate the business value of IBM technology and help clients understand how they can be applied to specific use cases. And, of course, we also have other technical roles within that team that deliver the actual proof of experience which grounds the technology with real-world business scenarios, giving clients real confidence in selecting IBM solutions.

The goal here is to achieve user and financial buying from our clients through this co-creation process and to build trust and deepen our relationship with them. In the last six months, right, with a focus on Generative AI, we ran a campaign; we’ve done 125 GenAI pilots.

SVG: I wrote down skills and co-create in bold in my notes. I’m going to double-click on that. But you know, let me, let me wear the cynical analyst hat here and ask you, is it just old wine in a new bottle, Shanker? Because IBM has had these rows of customer success managers for a while, it’s done pre-sales very well. And I’m assuming client engineering sits in the pre-sales bucket. What’s new that the clients can talk about and expect is that in the tech world, we’re known to put old wine in a new bottle every few years.

Shanker: The key difference here is the approach itself. So, for example, when you want to look at a particular solution, such as automation, you would have an automation specialist come and talk to you about the solution and try to put things together. But in reality, in the customer environment, if you want to take that forward, you have to integrate with the client’s environment, which may have other types of technology, to visualize the true capability of the technology you’re positioning.

But with this team, it’s a little different. It’s a squad approach where you have people skills in different disciplines coming together. So you have folks like the designers, the business technology leaders, the AI engineers, the cloud engineers, the developers. They all come together in a squad form. And engage the client in understanding the user problem, the problem, or the use case. Then, formulate a solution and rapidly prototype something to demonstrate to the client what this will look like, not just using IBM technology but also the client’s environment and data, and show them the possibilities quickly.

SVG: So true MVP in that fashion. Okay, interesting. And you know, even before we talk about the team skills mix, because it’s a topic, I’d love to sort of go a little deeper. I’m more keen to talk about where you start from, i.e., with co-create. So what’s the sort of normal process? What does it look like for a client? Are there key steps on the way that you take? Are there key measurables? Ultimately, you know, the funding has to come from the CFO’s office, and ultimately, what gets measured gets done, and that’s where the funding comes from. So, if you can break it down for our readers, what are some key metrics or steps you take in creating an MVP for a client?

Shanker: We have a method that goes along with this. Maybe you’re familiar with the IBM garage methodology. The IBM garage methodology accelerates digital transformation through an end-to-end model, including co-creation, co-execution, and cooperation. 

In IBM client engineering, we’ve taken the best practices from the co-creation phase and focused on solving a specific client problem or use case to achieve clear business value. We call this method, within CE, the value engineering method, which is an offshoot of garage methodology.

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But let me walk you through some key stages in this co-create space.

• So, the first thing we normally do is call it business framing. In this space, we establish the business objectives and desired outcomes for the engagement.

• Next, we conduct a design thinking workshop. We work with the client to explore potential solutions and identify user needs.

• Then, we go into prototyping. We create, in a very iterative way, and test prototypes to validate ideas and gather feedback from clients or even the client’s users as well.

• Then, we build an architectural blueprint. In this phase, we define the solution’s technical architecture, taking into account the client’s unique requirements and constraints.

• Then, we go into the MVP build, where we build and deliver a minimum viable product for the client for testing and feedback.

• Once all of that is done, we do a value assessment. We assess the value delivered by the engagement from both a quantitative and a qualitative perspective.

And all of this is done within three to five weeks.

But here, I would say the client’s involvement is crucial to the success of the engagement. To ensure their dedication and focus, we work closely with the client stakeholders ahead of time to identify any critical success factors or maybe even create a preparation checklist for each party, both for the client and us.

While unforeseen situations always arise during an engagement, we always try to be flexible and accommodate reasonable requests to ensure that both parties are fully invested in achieving the desired outcomes.

SVG: And the key sponsor at the client end would be, would it be the CIO’s office, or does it often also include the offices of other business leaders, if you may?

Shanker: Interestingly, most of the engagement we’ve done so far is mostly from the business side. I think the business is always trying to do something, and they want to do it quickly, and in that kind of scenario, they find that helping them visualize what it will look like is critical for them before they take the next step. Because this is a prototype or MVP and not a production type, it’s proof that what you’re asking can be done. And this is what it would look like.

SVG: Do you have any examples for us that you can share? Because I think to contextualize all the wonderful things you’ve said, are there any client situations you can share with us just to better understand and get a handle on, let’s say, what sort of organizations you have worked with here in Asia from a client engineering perspective, and what sort of outcomes have they experienced so far?

Shanker: Maybe I’ll share some recent stories or success stories from our region. I think the ones I’ll probably share will demonstrate how we collaborate with clients to identify challenges and deliver successful outcomes.

Maybe I’ll start with this one close to home in Southeast Asia, with a tier-one telecommunication service provider. The client was looking to build a next-generation data platform capable of processing large volumes of data and generating insights for new product offerings. Our CE team worked closely with the C-suite-appointed stakeholders, building a foundation using IBM technology, including our core analytics and integration solutions and the WatsonX data platform on the AWS cloud. This was a high-stakes project with unique challenges, and we partnered with other vested parties to address them. Then, the clients saw the value of the output of the client engineering team and now intend to turn the foundation into a data marketplace to monetize insights with their partners. So that’s one example.

Another example comes from a global F&B consumer brand in the region, which relied on its distribution network for its business and wanted to increase efficiency to be more responsive to its distributors. We created a WatsonX GenAI-powered solution that allowed the distributors to access data related to the supply chain process quickly and more efficiently. So we eliminated several human steps, and now the client stands with the outcome and plans to expand capability across the global distribution network. 

We’ve also worked with other ecosystem players, like an ISV in India. They had built an AI-powered contact center solution but wanted to upgrade it with new functionalities. We co-created a refreshed architecture using WatsonX, providing new capabilities to handle complex scenarios and reduce the cost of operations.

One last example I use that is closer to you is one of the latest projects we’ve done with a financial institution in Australia that wanted to create what I would say is a first-pass legal document review process using the WatsonX platform. This solution can identify deviations from any pre-approved standards terms within moments, taking advantage of GenAI to understand context, finding deviations and then redlining those deviations. In the past, the legal department probably took several days to turn around. Now, within minutes, it’s done, and productivity has increased a lot.

SVG: These are excellent examples, of course. And I have a few questions about them. So, let’s say an engagement like this becomes successful. Does it get handed over to an account engagement team, or does the CE team continue to be a part of the overall engagement?

Shanker: No. So the way we work is that once we’ve completed the engagement, we either hand it across to what we have, which is a technology expert labs organization, a services organization within the IBM technology arm, or we hand it to our IBM consulting colleagues, or in many cases now we are handing it over to ecosystem partners. They also take forward the actual implementation of the solution or the productization of the MVP or pilot.

SVG: So I’m assuming this MVP is done at no cost to the client, right? How do you qualify a client or a use case that you think fits wonderfully well for a CE team? Is it the existing IBM clients? Is it the length of the relationship? Is it the depth of the relationship? Give us a sense.

Shanker: First, before we begin engagement, we work with the clients to identify preconditions for the project’s success. These might include things like data availability, infrastructure access, and access to stakeholders. Some of these requirements may be the client’s responsibility, while others may be IBM’s. We also ask the client to fulfil preconditions before we start the formal engagement.

In terms of outcomes, we lay them out front and provide regular and frequent visibility to stakeholders throughout the project. This is critical. It helps make course corrections towards the intended outcome and achieve sponsor buy-in without any, what you say, unwelcome surprises.

It’s important to note that this is a co-creation process. So, both IBM client engineering and the client have a shared responsibility for achieving the outcome. Again, it’s probably based on trust and holding ourselves accountable for the commitment, for the joint commitment.

One thing to keep in mind is that our engagement, as I shared earlier, focuses on non-production environments, and we respect clients’ privacy and confidentiality requirements. So, if a project requires taking a proven concept to production, it would go to, like I said, technology expert labs, consulting, or other partners.

SVG: You mentioned transferring a lot of these MVPs to the ecosystem partners as well. Now, that intrigues me. How do you ensure that the ecosystem partners have the knowledge, the know-how, and, let’s say, the kind of resources that they would need to ensure consistency of the MVP from a scale and security and other perspectives?

Shanker: Let me provide some context first before I get to the details of how we do it. Our CE team works closely with both direct accounts and what we call indirect accounts or partner-led accounts.

In the case of direct accounts, we work directly alongside the IBM account team. We develop the roadmaps, deliver the proof of experiences, and create value assessments.

When it comes to partner-led clients, we take a similar approach but collaborate closely with partners instead. So, our CE team not only brings the necessary skills and experience but also, during the co-creation process, transfers knowledge to the partner resources. This helps ensure they are well-equipped for future engagements and continue delivering value to clients. So it’s like on-the-job training, which we did last year or maybe at the beginning of last year. 

To expand our reach even further and cover a larger portion of the addressable market, we have dedicated ecosystem engineering teams in place. These teams can focus on collaborating with GSIs or regional system integrators, RSI hyperscalers, and ISVs. With this combination, we can effectively engage with a wide range of clients and ecosystem players, ensuring our team stays informed and up to date on the latest trends and developers in the market.

SVG: When you produce these MVPs, be it for direct clients or indirect clients, is this client IP, or is it IBM IP? 

Shanker: So when we create the technology, we have a document of understanding. In the document, we clearly articulate what actually belongs to the client. If it’s the client’s idea or data, it all belongs to the client; we don’t hold it. But what we do is harvest the knowledge in terms of how we created and transfer skills in terms of the knowledge of the prototype or MVP we did.

SVG: I’m asking this question because of your example of the data marketplace you helped build. Now, that’s a very interesting example. Now, there can be another client in, let’s say, North America who probably also needs that kind of knowledge sharing. Now, are you able to share the specifics of a marketplace and the platform for another client? Or does that concept and the idea become proprietary to one specific client? Ultimately, the only way you can scale this is when one MVP starts to help build multiple other products for multiple clients.

Shanker: From a business model perspective, the client’s business model is the client’s IP. We don’t share that. But in terms of technology, how you apply technology to what you need to do, I think those are the transferable skills, which we also take to other clients, as well as knowledge and experience.

SVG: Thank you, Shanker. That’s a wonderful answer. The thing is, the CE team is a rather globalized team. There are different resources where you pull different skills at different points in time. So, how do you ensure that learning from these various use cases and MVPs that you have on the go doesn’t fall through the cracks and that other peers from other parts of the world have access to that information?

Shanker: So we can drive that in a couple of ways. 

When we complete a project, we codify whatever MVP or pilots we do as technology patterns. Technology patterns are what we call combines things like architecture, design and assets that people use to create the MVP. This is put into a shared knowledge base that any of our team members worldwide can access. They are categorized differently by industry, use-case type, and technology use. So it’s pretty easy for them to take something and apply it.

I’ll just give you a simple, interesting factoid. When we started with the client engineering team, our typical pilot would take about eight to ten weeks. Today, we’re doing two to five weeks. That’s primarily because we harvest these assets or technology patterns and apply them to other types of use cases as well. So that’s how we have actually shortened it to three to five weeks now.

We also have what we call community calls, where we bring together. We have a concept of guilds here, where guild champions drive certain topics, such as GenAI, automation, intelligent automation, or sustainability. I think they drive conversations, and the team members interested or keen in these areas will join those calls and participate. I would say that we also have Slack channels for this one.

Because the client engineering community is a young community, members are very excited to share what they’ve done and are quite happy and excited about sharing with other people what they’re actually able to do.

SVG: Maybe you should convert this into a platform and monetize it at some point. Because there is so much property and intellectual wealth in this platform, monetizing it at some point makes perfect sense. I mean, just giving access to the ecosystem partners to have access to this on-the-tap wealth of knowledge. I think it should be monetized at some point, right?

Shanker: You made an excellent point. I think it’s an idea for me, for us now.

SVG: Before we close this conversation, I am very keen to sort of go back to where we started, which is the team and the skills you have in the context of all that we’ve spoken about. Could you give me a sense of the team dynamic, or are there these permanent sets of hands that you have in the CE team? One is that. Second, what sort of roles do they play in each engagement? Is there an engagement holder? Is there a technical architect? Is it a client expert? Is there an SME that joins the team on an as-needed basis? Please give us a sense of the team’s structure and skill mix.

Shanker: Let me first define the roles. I think the CE team consists of several key roles. 

I think I shared the first one earlier, so let me talk a little bit more about it. There are designers. Our designers play a crucial role in helping clients envision their future state. They create visualizations of potential solutions and work collaboratively with the client to define the desired outcome.

And then we’ve got the business technology leaders who have deep business consulting skills and focus on ensuring that we can cover both the people and process angles with clients, hypothesize, and calculate the business value of the outcome we are aiming for.

And then we got a number of technical roles, everything from solution architects to cloud engineers to developers, who are really the core people who deliver clients’ proof of experience, like pilots and power, proof of concepts.

These team members bring solution and product skills based on what the client’s use case or problem is solving. And then we just introduced a new role last year, AI engineers. And this is, I would say, actually the evolution of data scientists, who are now more focused on AI versus data science type of projects. So, based on the client’s use-case problem-solving, a mixture or combination of these different roles come together.

Typically, in every engagement, you would have a designer who kicks off the ideation process and a business technology leader. However, the other roles depend on the use case itself, and they come together in a squad formation. So, the combination of these roles works with the client’s team to create this outcome. I think you also mentioned it, as this is an IBM investment. We do not charge our clients for it.

Today in APAC, we have about 200 staff across the five markets, around 13 countries.

SVG: So, how do you measure the success of this team? It cannot currently be financial since it’s free, of course. How do you measure the success? And more importantly, are there times when you don’t get a client to be happy with an MVP, and you have to walk away?

Shanker: Yeah, that’s an interesting question because we are also constantly thinking about this. This is a big investment on IBM’s part, and we need to make sure that we’re getting the return on our investment internally. And this has evolved. 

Today, we have moved from how we measure this team from a utilization perspective to a more outcome-based measurement, where if they work on a specific proof of experience, what percentage of that converts to a deal that closes for us. And today, we’re looking at a ratio for every two we close one.

SVG: Okay, that’s good. 50% closure is a good rate. And, you know, I think in the closure, I’d love to get two things from you. One is that since big companies have big agendas, agendas sometimes change overnight, and radical decisions are made to close and shut teams. So, what is IBM’s commitment to the client engineering team in the long term? In today’s terms, the long term is not seven to ten years. It’s three to five. So moderate, moderately long. One is that. And if you are committed, per se, what additional changes can clients expect in the coming year?

Shanker: Okay, so let me ask the first question, I think easily.

You can quantify, you know, the commitment based on the continuing investment. So, we started the client team around two or three years ago. We started with about 50 people in the Asia Pacific, and today, we are about 200 in size. And we continue to see that.

This is where clients begin to see value because they experience the technology. They see a difference in the way IBM engages because the clients are experiencing what they want to see versus showing, basically, just talking about it.

So, in terms of changes and moving forward in 2024 and beyond, I think we’re making some exciting things from a structural and organizational perspective. With IBM’s go-to-market evolving, maybe I will share a few key highlights.

• First, we have aligned our team more closely with each market’s unique needs, reflecting the distribution of direct and ecosystem clients. Based on that, we are adjusting our investment. This will enable us to be more responsive and effective in addressing the specific requirements of different markets or regions.

• Second, I think we’re bringing together the client and ecosystem engineering teams under the same global management structure to facilitate better collaboration and synergy. One is focused more on partners, and one is focused more on direct clients. So, we are bringing it under the team. So we try to harvest and, you know, bring synergy. I think this will also work more closely together and provide even more value to our clients.

• The last bit, I would say, is to meet the growing demand for GenAI. As you mentioned, as you kicked off your session, we have continuously strengthened our teams with new skills and additional capacity for AI engineers who bring deep knowledge and expertise in this area. Many of these folks are researchers with PhDs. All this, I think, is hoping to enable us to deliver more innovative solutions to meet the evolving needs of our clients.

SVG: So net-net, IBM is committed to CE. Wonderful. On that note, Shanker, thank you for your time. It’s been a wonderful conversation. Thanks, everybody, for reading/watching. I hope the content in this conversation has been helpful. If you have any hard questions, send them over, and I’ll ping Shanker and have them answered for you. Thanks once again.

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