Balancing Innovation & Client Needs With Rajan Sethuraman

Rajan Sethuraman is a highly accomplished professional and an alumnus of IIM Calcutta, where he completed his Master of Business Administration (MBA) in Business Administration, Management, and Operations during 1993-1995. With a strong background in management consulting, Rajan brings extensive expertise to his role as the Chief Executive Officer at LatentView Analytics, a trusted analytics partner to some of the world's most renowned brands. Throughout his career, Rajan has showcased his proficiency in various domains, including Global Delivery, IT Strategy, Management, Business Development, and Business Process Improvement. His leadership skills and strategic acumen have contributed to his success as a CEO, making him a valuable asset in the field. Rajan's track record reflects his dedication to delivering excellence and driving growth in the organizations he serves. In this week’s CDO Insights, we interviewed Rajan Sethuraman to gain insights on balancing innovation and meeting client needs effectively, as his extensive experience and strategic leadership at LatentView Analytics align with the topic's relevance in the analytics industry. AIM: How do you view the relationship between innovation and client needs, and what experiences have shaped your perspective on striking the right balance between these two priorities in your professional career? Rajan Sethuraman: One of the things we notice quite a bit, is that while there is always an interest in trying out new things and being innovative, there is also this need for being grounded in the business reality of our client’s current context. Especially in a situation where budgets are tight and you're operating under a source constraint, there is always the need to make sure that every dollar you spend impacts the P&L. In that context, it becomes crucial that while you are being innovative, you're also doing something that will have a real impact on the bottom line or top line of the company. The decibel levels around generative AI and large language models are at a peak right now, especially because of the democratization that has happened in recent times. Through ChatGPT, everybody is now familiar with it, and there's also a fear of missing out creeping in – “ If I'm not doing something in LLM, am I missing out? ” However, I think in the last two or three months, I'm starting to see some changes, at least in terms of client perception. Instead of just saying, “Let's get something underway and let's get something started,” they're asking questions about how they can make meaningful use of generative AI or large language models or any other emerging technology. In this resource constraint scenario, we were hoping that the second half of this calendar year will be more relaxed from a budgetary standpoint. But that is not panning out. Clients and organizations are still walking a tightrope when it comes to requirements. One of the things we do when it comes to innovation and new ideas, is to try and sit down with the client and help them think through what specific metric they are trying to impact. It could be a financial, process or an operating metric. We peel the onion a bit more to get clarity. We let them know the initiative we are undertaking, while attempting to use generative AI or LLM to improve its performance but focus more on the key metrics we are targeting. We ask them if they are aligned with this, and if these metrics are important in their current context. If yes, we initiate a pilot and the POC. However, most of such initiatives are still in the pilot POC stages; I don't think there are too many full-fledged ones. You will find something in customer experience, customer interaction, and so on. That is where NLP and NLG technologies have also been used in the past, and GenAI is helpful. But when it comes to hard data analysis, generating insights from a ton of available data, people are still figuring out how to marry the hard science, the math, and the modeling with the GenAI capability. AIM: Why, particularly in technology, do clients often seek to implement solutions like Generative AI without a clear problem statement or use case, despite having specific business metrics and objectives in mind? Rajan Sethuraman : My hypothesis is that it is because of the pace at which technology is disrupted. In the last couple of decades, we have observed the life cycle – the introduction of a new technology, the hype cycle, getting to real impact and maturity, and then getting replaced by something else – is getting shortened with every passing quarter. New technologies come up, and you need to be quick in how you understand it, how it can impact your business, and quickly start leveraging it. And obviously, the underlying fear is that if I'm not on it, I'm missing out on competitive advantage. And this could be a real competitive advantage. Whether it is in terms of innovation, products, and services you can come up with and put in front of yo

Balancing Innovation & Client Needs With Rajan Sethuraman

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