Building a Data-Driven Organization: Leadership Lessons from Srikanth Velamakanni, Co-Founder & Group CEO of Fractal Analytics

In the rapidly evolving field of artificial intelligence and data analytics, few individuals have been as influential and prescient as Srikanth Velamakanni. As the Group CEO, Co-founder, and Vice Chairman of Fractal Analytics, one of India‘s largest AI companies, Velamakanni has been at the forefront of the data revolution for over two decades. From starting Fractal in 2000 when analytics was still a niche domain, to now overseeing an AI powerhouse with 2000+ employees across 16 global locations, Velamakanni has expertly navigated the shifting technological landscape and established himself as a visionary leader.

Over the years, Velamakanni has amassed a wealth of experience and wisdom on what it takes to build and scale a successful data-driven organization. As more and more companies seek to harness the power of AI, his insights have become increasingly valuable and sought-after. In this article, we‘ll take a deep dive into Velamakanni‘s leadership philosophy and the lessons he‘s learned on his remarkable entrepreneurial journey with Fractal. Whether you‘re a startup founder, a seasoned executive, or a budding data scientist, there is much to glean from his story.

The Evolution of AI & Fractal‘s Transformation

To understand Velamakanni‘s approach to building data-driven organizations, it‘s important to first examine the broader context of how artificial intelligence has progressed over time. When Velamakanni co-founded Fractal in 2000, AI was still very much in its nascent stages. "The fascinating thing about our journey is that it has mirrored the journey of the progress of AI," he notes. In those early days, much of Fractal‘s work revolved around analytics and structured data, utilizing techniques like logistic regression, decision trees, and random forests to help clients make better data-informed decisions.

But as the field of AI began to evolve, so too did Fractal. In the early 2010s, breakthroughs in neural networks and deep learning began to emerge from the research labs of tech giants like Google, Microsoft and IBM. Velamakanni recognized that this new wave of AI technologies was going to transform business and society in profound ways. "2012 was a big turning point," he recalls. "I read the book Superintelligence by Nick Bostrom and met with leading researchers like Li Deng from Microsoft. That‘s when it hit me that I was already late to start, but I did start almost immediately."

Under Velamakanni‘s leadership, Fractal began to invest heavily in AI research and development. In 2012, the company established Fractal Sciences to explore cutting-edge problems in the field and incubate new product ideas. This paved the way for the creation of several successful AI startups within the Fractal ecosystem, including Cure.ai for healthcare, Eugenie.ai for sustainability, Asper.ai for revenue management, and Senseforth.ai for conversational AI.

By 2015, Fortune 500 companies around the world had started to wake up to the disruptive potential of AI, with many CEOs being asked by their boards to present comprehensive data strategies. Fractal was well-positioned to capitalize on this rising enterprise demand, having already developed deep expertise in applying AI and machine learning to real-world business problems. Today, the company is at the forefront of implementing advanced technologies like transformer language models and diffusion models to solve an ever-expanding range of challenges for its clients.

Velamakanni‘s foresight and willingness to continually reinvent Fractal in line with the latest technological advancements have been key to the company‘s enduring success. "My advice to everyone in the industry is to get deeper – do your research and keep upskilling," he stresses. "Your relevance now is a function of how much you have read or evolved in the last week, not just the last 10 years."

Lessons in Building Data-Driven Organizations

So what does it take to build a truly data-driven organization? According to Velamakanni, there are several critical ingredients:

1. Invest in technical talent from top to bottom

One of Velamakanni‘s core beliefs is that strong technical capabilities are essential for any company seeking to harness the power of data and AI. At Fractal, this starts with having a deep bench of top AI researchers, data scientists and engineers at all levels of the organization. "From junior to middle to senior management, I would say do not lose the tech edge," Velamakanni advises. "Spend some time every day to read research papers and stay abreast of this tech because a lot is changing rapidly."

This focus on technical excellence extends all the way up to the C-suite. Despite his demanding schedule as CEO, Velamakanni still carves out time to stay on top of the latest developments in AI and engage with the scientific community. "I still manage to stay technically sound and updated to keep going and stay relevant," he says. By leading by example, Velamakanni has instilled a culture of continuous learning and improvement at Fractal.

2. Bring together multi-disciplinary teams

While having strong technical chops is crucial, Velamakanni also emphasizes the importance of assembling multi-disciplinary teams to tackle data and AI challenges. He discovered this himself several years into Fractal‘s journey, when he realized that some of the company‘s projects were stalling either due to lack of engineering capabilities or failure to properly frame the problem.

"We learned never to take the client‘s problem for granted," he explains. "They might come to us with a downstream issue, but we have to go upstream from there and trace it back to the root cause. That‘s the actual problem to solve." To do this effectively requires bringing together people with diverse skill sets, ranging from data scientists and machine learning engineers to sociologists, anthropologists, and UX designers.

At Fractal, these cross-functional teams collaborate closely to reframe client problems, design human-centric solutions, and build end-to-end systems to drive real impact. "About 6-7 years ago, we brought in people from different disciplines and built a team where they could all work together and create magic," Velamakanni shares.

3. Democratize data and insights across the organization

Another key pillar of being data-driven is ensuring that relevant data and insights are readily accessible to stakeholders across the business. Too often, valuable data remains siloed within technical teams and fails to inform decision-making in other functions. Fractal takes a democratized approach, building self-serve tools and platforms to give employees at all levels the ability to ask questions of data and derive actionable intelligence.

One notable example is Crux Intelligence, an AI-powered business intelligence startup incubated within the Fractal ecosystem. Crux‘s mission is to enable anyone in an organization to get answers from their data using natural language, without needing technical expertise. By putting insights at everyone‘s fingertips, Fractal empowers its people to be curious, test hypotheses, and make data-driven decisions in their day-to-day work.

4. Prepare for a changing workforce

Looking ahead, Velamakanni anticipates that AI will fundamentally reshape the nature of work and organizations in the coming years. He predicts a major shift from the industrial-era paradigm of time-based work to a knowledge-based model. "In 10 to 15 years, people will end up working because they want to, not because they have to," he envisions. "Companies will resemble artists‘ studios more than factories."

To thrive in this new reality, organizations will need to rethink long-held assumptions about management practices, performance evaluation, and what it means to be productive. They will also need to ensure that gains from AI-driven productivity are distributed equitably. "AI is the most impressive productivity growth technology we have ever come across," Velamakanni declares. His hope is that in time, society can leverage these productivity gains to guarantee basic needs for all, freeing people to pursue work that aligns with their passions and purpose.

The Power of Education

Beyond his work at Fractal, perhaps the most striking thing about Velamakanni is his deep commitment to education. Despite his hectic schedule, he makes time to teach courses on machine learning and data science at universities, as well as internally at Fractal. In 2021, he co-founded Plaksha University, a new institute in India dedicated to bridging the gap between technology and the liberal arts. He also recently launched the Fractal Data Science Professional Certificate on Coursera to help upskill the next generation of data science talent.

When asked what drives him to invest so much energy into teaching, Velamakanni points to the profound impact that education can have on society. "If you take a very long-term view of the economy, education and entrepreneurship are the two vectors that will lead to better outcomes," he explains. "Better-educated people to solve problems, and entrepreneurs willing to take risks to solve those problems. Together they can make the world a better place."

For Velamakanni, teaching is not only a way to give back, but also an opportunity for continuous learning and growth. "The hidden benefit of teaching is that it keeps me young," he shares. "You realize your own level of ignorance when you try to teach a topic. So it pushes me to stay updated."

Conclusion

Srikanth Velamakanni‘s story offers a compelling blueprint for what it takes to build a successful data-driven organization in today‘s fast-moving AI landscape. Through his work at Fractal Analytics, he has demonstrated the importance of continuously evolving with technology, investing in top talent, driving cross-functional collaboration, democratizing data, and preparing for the future of work. At the same time, his deep passion for education underscores the vital role that knowledge-sharing and continuous learning play in nurturing the next generation of AI leaders.

As more and more companies seek to harness the power of data and AI, Velamakanni‘s insights and experiences will only become more relevant and valuable. By studying his journey and the hard-won lessons he‘s learned along the way, aspiring entrepreneurs and executives can position themselves to build thriving, impactful data-driven organizations for the future. With visionary leaders like Velamakanni lighting the path, the potential for AI to improve business and society is boundless.