Pranav Dar — January 10, 2022
Beginner Interviews

“My experience is that for every dollar of AI spend, you need $10 of engineering spend to make it work.”

How about that for an eye-opener? While the world is laser-focused on data science, there is a HUGE opportunity to upskill and invest in the data engineering aspect. This is just one excerpt from our exclusive interview with Srikanth Velamakanni, Group Chief Executive & Vice-Chairman at Fractal.

In this wide-ranging interview, we discussed multiple topics, including:

  • Fractal becoming a unicorn with the latest investment round
  • The role of data engineering at large in the data science ecosystem
  • Fractal’s plans for the data science community

Srikanth co-founded Fractal Analytics in 2000, well before analytics and AI were entire industries. He served as CEO of Fractal Analytics from 2006 to 2016. In his current role as Group Chief Executive, Srikanth leads the Fractal group of companies and is also responsible for the inorganic growth and long-term future of the business.

fractal_interview_srikanth

You might have come across Fractal in the news recently – they announced a huge US$ 360 million (~ INR 2700 crores) investment from TPG, a leading global alternative asset firm. This makes Fractal just the second unicorn of 2022 – incredible! You can read more about this announcement in our article here.

There is a lot to think about and learn from Srikanth and hence we are publishing this interview for our community. Happy learning!

 

On Fractal Becoming a Unicorn

Analytics Vidhya (AV): Srikanth, welcome to the call and a huge congrats on Fractal becoming a unicorn! Can you give us an insight into how this investment accelerates Fractal in its journey?

Srikanth Velamakanni: Thanks a lot. It’s been quite a journey and there’s a lot more to look forward to.

Let me break down my answer into two parts. These are the two key features about what Fractal is building:

  1. Extreme orientation towards clients and people, and
  2. Orientation for the very long term

That’s what really characterizes Fractal’s approach and strategy. And this fundraise actually helps us in both. It helps us in investing in more products. We spend about 15 to 20% of our revenue in R&D and creating products so it will help us in accelerating that further. And secondly, it will help us in doing meaningful investments and acquisitions that bring greater client value overall.

“We think true client-centricity is about inventing on behalf of the client.”

From a long-term standpoint, we also have been looking at investors who have a longer-term orientation. Longer-term we would like to be a public company and I think building Fractal for the very long term is accelerated by getting investors who are long-term oriented and getting Fractal to scale and size that can be public. This is also one of the reasons for the investment.

 

AV: You mentioned Fractal wants to invest and scale up in a lot of new areas. What are some of those growth areas that you see?

Srikanth: I see opportunities everywhere! We just have to be focused on what we can address. But AI is such a large and nascent space that there are many victories to be had. Many things to do.

We focus on what do our clients need the most. Everything is client-centric. So we work backward from what does the industry or the client need, and then work backward from there. We only serve Fortune 500 size clients.

So looking at that, what we see is one is end-to-end problem solving for clients.

“It means that not only do we bring smart algorithms, but we bring in great engineering and a great human centered behavioral sciences and design.”

We see great opportunities in areas such as healthcare and supply chain, to name a few. We see opportunities in a number of places geographically as well. It comes down to where we can be really good and how we can serve our clients better.

 

AV: That’s super interesting and we’ll circle back to the engineering aspect in a moment. Before that, we were curious – Fractal started as an Analytics Consulting/services company but has built and invested in several products in the last few years. What does the roadmap look like from here?

Srikanth: Our goal, when we incubate any product or a business, is that eventually, they should be able to raise a lot of the capital on their own and potentially be public on their own merits. So our goal is to incubate many of these products or invest in some of the products and then let them discover their journey as part of Fractal. We can bring a certain set of skills and capabilities and resources to their success, but eventually, we want them to be on their own and be very successful.

“So we will continue investing about 15 to 20% of our revenue in building out products and R&D.”

Quantum computing is an area of research for us. If you look at the AI world, I see it as three phases :

  • 2010 – Google and Microsoft got interested in AI and started investing heavily
  • 2015 –  Big global companies started investing in AI, and
  • 2020 – Everybody and their cousin started investing in AI!

We want to invest today because we know that in seven or ten years everybody will be investing, and in fact even in five years we’ll see some great use cases. So that’s one area of investment. Similarly, we’re investing in computational neuroscience as an area.

As I said, we see opportunities in a number of different places and we aim to build products across each of these areas of interest.

 

The Key Role of Data Engineering

Data Engineering

AV: You mentioned earlier that engineering also plays a big part in your thought process in this investment. And we’ve seen in the last decade that data science is everywhere. As you said, everybody wants to invest in data science. But recently, we have started to see a huge spike in interest in the data engineering side of things from organizations. How does the engineering side of things factor into your thinking at Fractal?

Srikanth:

“My experience is that for every dollar of AI spend, you need $10 of engineering spend to make it work.”

There’s obviously the complexity of data that we have to handle, and the complexity of the systems that we have to handle. Eventually, you’ll have to procure the data and create those pipelines, which is one aspect of it. And the second aspect of it is deploying them.

“Deploying these AI models at scale and making sure that they’re deployed in the real world and we are managing and maintaining and scaling them and actually making sure that they’re continuing to work.”

And at this point in time, Fractal is not over-indexed in these areas and we would like to be.

 

Srikanth on Fractal’s Role in the Data Science Community & Entrepreneurship

AV: We’ll switch focus here and look at it from the community angle. Fractal has done a strategic investment in Analytics Vidhya. What does the investment mean for the Community and the data science ecosystem at large?

Srikanth: I feel very passionately about the community. I have personally been involved with the data science community for a long time.

India is a highly math-oriented country and we produce a ton of engineers every year. We have extremely smart people across the country.

“India is going to contribute 91 million to the global workforce in the next 8-10 years. India is the only major country in the world that actually has a net addition of labor workforce in the next 7-8 years. So think about that for a minute!”

One of the things that we have done is to create what we call a crossover program, which is to look at the top decile of the tech talent in India.

Think of the IT industry. India employs four and a half million people. Very, very smart and capable people. A third or quarter of them are very interested in careers in data science. And we’re trying to see how we can enable them to access AI and really learn the basics of AI and problem solving.

“It’s not just good to be a tool operator, or know how to run a tool or write some code, but you have to actually be able to solve problems.”

Fractal knows how to do that, so our intention is to use some of the money there. Also to create this ecosystem in India and I think contribute to the nation overall because of that.

 

AV: You mentioned that India has everything to be the AI destination for the world and upskilling is obviously one of the areas. Any other areas which need to take shape for India to progress forward in that journey?

Srikanth: Absolutely! Another two areas that come to mind are risk capital and risk taking. Something that has been covered a lot in the media recently as well is entrepreneurship. It has taken off in a very big way in India in the last few years.

I do still think that relative to the rest of the world, we are quite under-indexed on overall entrepreneurship. And most of all, entrepreneurship in India is low-risk entrepreneurship. The boldness of vision and the willingness to commit a higher degree of capital would also be useful. It’s a matter of time these things will happen.

At an individual level, I facilitate courses on entrepreneurship and encourage others to do the same – to leverage their experience and help the talented young people of this country to broaden their horizons.

 

AV: Can you recommend a couple of top books on entrepreneurship for anyone who wants to get started?

Srikanth: That’s a tough one! One I would mention is a book called the Breakthrough Company. It’s about building a company from let’s say $5 million to a $200 million scale. It’s what I did. When Fractal was $4-5 million in revenue and I thought it was very useful, so I will recommend that.

Another is called Invent and Wander by Jeff Bezos and Walter Isaacson.

And finally, I would say generically read books about entrepreneurs and their stories. You realize no one had a straight path to success. There’s no such thing as an overnight sensation.

 

Disclaimer: Fractal is a strategic investor in Analytics Vidhya.

About the Author

Pranav Dar
Pranav Dar

Senior Editor at Analytics Vidhya. Data visualization practitioner who loves reading and delving deeper into the data science and machine learning arts. Always looking for new ways to improve processes using ML and AI.

Our Top Authors

Download Analytics Vidhya App for the Latest blog/Article

Leave a Reply Your email address will not be published. Required fields are marked *