In this Leading with Data episode, Rajan Sethuraman, CEO of LatentView Analytics, discusses his journey from Accenture to leading a fast-growing analytics firm. He highlights challenges in transforming LatentView, stressing generative AI, talent acquisition, and geographic expansion. Rajan shares insights for those starting careers in data analytics.
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Now, let’s look at the questions asked by Ranjan Sethuraman in the session and how he responded!
I joined LatentView Analytics in June 2016 after over two decades at Accenture and a year at KPMG. LatentView appealed to me, combining my background in management consulting, extensive analysis, and later expertise in talent acquisition and predictive modeling for hiring and attrition. This blend of business consulting and analytics is what attracted me to LatentView, where we address complex business problems through data analytics.
Moving from Accenture to LatentView was a significant change, given the size difference between the two companies. I was attracted to the potential impact I could have in a smaller, dynamic company like LatentView. The culture at LatentView was vibrant, with intelligent people working on challenging problems. My role evolved from Chief People Officer to CEO, and my focus has been on transforming LatentView from an execution partner to a strategic thought partner for our clients.
My primary goal has been to pivot LatentView from being an execution partner to becoming a strategic consulting partner. This involves helping organizations think through their analytics strategy and how it ties to their business goals. To achieve this, we’ve been building deep industry and domain expertise, developing domain-specific solutions, enhancing our consultative problem-solving skills, and leveraging external advisors’ expertise. Additionally, geographic expansion and exploring inorganic growth opportunities have been key priorities.
We’ve always focused on hiring a mix of technical, mathematical, and business domain skills from top-tier campuses and through lateral hiring. With the IPO, our visibility in the talent market has increased, allowing us to attract high-caliber candidates. We emphasize a culture of learning and agility, where employees are encouraged to take on new challenges and continuously upskill themselves.
We prioritize hiring for fundamental skills and providing an environment for continuous learning. Our culture encourages tackling tough problems confidently and learning on the job. We have institutionalized mechanisms like internal hackathons and client-related innovation exercises to foster a culture of learning and staying at the forefront of analytics.
Preparing for the IPO didn’t require significant changes, as we already had a culture of discipline and governance. Our focus was on profitable growth and strategizing for the future, including identifying key sectors and geographies for expansion, and considering inorganic growth to enhance our capabilities and market presence.
Generative AI has created a buzz, with clients eager to explore its potential. It has democratized the understanding of what’s possible with analytics, leading to a surge in demand. We’re taking a three-pronged approach: developing core generative AI-based solutions, creating generative AI wrappers for existing solutions, and using generative AI to enhance our internal productivity.
We’re committed to expanding in Europe and exploring opportunities in India and Asia Pacific, focusing on Fortune 500 companies and leveraging advisors’ expertise. For inorganic growth, we’re looking at acquisitions that can help us leapfrog in key sectors and capabilities, with a focus on companies that bring additional IP and non-linearity to our services.
The data analytics market is expected to grow significantly, and we aim to quadruple our revenue in the next four years. The shift from systems of record to systems of decision-making presents immense potential for data analytics. We’ll also explore adjacencies in industries, geographies, and types of work that align with our current offerings.
Be resourceful, agile, and willing to learn continuously. The ability to seek help, move quickly, and adapt to new skills is crucial in the dynamic field of data analytics. Keep learning and reinventing yourself to stay relevant and ahead in your career.
Rajan Sethuraman’s journey exemplifies the evolving dynamics of the analytics industry. From talent strategies to embracing generative AI, LatentView’s transformation into a strategic partner underscores the industry’s shift toward decision-making systems. As they eye geographic expansion and inorganic growth, Rajan envisions quadrupling revenue in the next four years. Strategic evolution, talent agility, and adapting to emerging trends—serve as a compass for navigating a career in data analytics.
For more engaging sessions on AI, data science, and GenAI, stay tuned with us on Leading with Data.
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