Fractal Analytics’ COO Ajoy Singh tells us that Fractal’s approach to digital transformation is human-centric and decision-driven. In this story, he takes us through a deep dive into how the company uses AI technologies to help companies make better decisions in the new normal

Fractal Analytics is a global AI solutions company founded in 2000 by Srikanth Velamakanni and Pranay Agarwal. It has 3500+ employees across India, the U.S, the U.K, Ukraine, Singapore and Australia. It services large companies like Reckitt Benkiser and Wells Fargo, and offers its customers a suite of AI solutions for revenue growth, operational efficiency and medical imaging, to name a few. 

In this interview with the Smart CEO, Fractal Analytics COO, Ajoy Singh, takes us through the key strides the company has taken in the last three years, and how it is aiding customers in their digital transformation journeys, one data set at a time. 

Tell us about Fractal Analytics’ journey since the pandemic started. 

It has been a tough but energizing journey for us. Having faced many ups and downs, we’re now able to see the impact we were able to create towards the society, our employees and our customers. 

When Covid hit us in the early part of 2020, we had no idea what’s going to happen. We didn’t know how to progress, or how the pandemic was going to affect lives. We started out by thinking about what we can do to help the Government in India and other countries track the infection spread, create health infrastructure, aid in lockdown-related decision-making and so on.

On the business front, we saw a sudden rise in demand for digital transformation. In a chaotic world of broken supply chains and talent crunch, we helped our clients reimagine their business and digitize their processes. We helped them automate their businesses using AI so that they could serve their own end customers better in a different, more volatile world.

From an employee perspective, one of the key things we did was to ensure a continuous stream of communication between every employee in the company. We had daily town halls with our employees globally, just to keep them on the same page on what Fractal is doing through this period, and to seek their inputs on how we can do these initiatives better. In the last couple of years, we conducted nearly 130 town halls and this has really helped us retain employees and maintain our culture. 

How did you help your customers transition into the digital world during the pandemic? 

The word digital transformation is full of buzzwords like IoT, big data, AI, cloud and such. At Fractal, we believe that digital transformation is not a suite of tech words. Rather, it encompasses five very specific things;

• Helping our customers engage seamlessly with their customers
• Improving the operational effectiveness of our customers 
• Helping our customers build better products, faster
• Helping them drive better executive decisions 
• Transforming their business in a sustainable way and re-imagining their work

To elaborate, when it comes to helping our customers engage seamlessly with their customers, removing digital friction was one of the key things we focussed on. For example, the entire retail industry got transformed during the pandemic. There were no shoppers coming to the store. So, how could we help our retail customers improve their curbside pickups? How could we help retailers imagine their supply chain? How could we improve their operational efficiency? These were some of the aspects we worked with them on. At the core of all this was AI. 

Tell us about challenges you faced when taking your customers through digital transformation.

Digital transformation has always been there, but the pandemic accelerated it by leaps and bounds.

The big challenge which we see in many situations is how people think about digital acceleration. A lot of error takes place when people think of digital transformation as data forward and technology-centric. But, we say digital transformation is a user-centric and vision backwards way of doing anything. So, for example, we don’t believe in starting with building huge data sets. We believe in first looking at what vision and decisions our customers want to drive. And then we work backwards to look at what data, engineering and algorithm is required to drive those decisions. The key is to be decision-driven and human-centric in approach.

Is this where data engineering comes in? How does Fractal approach data engineering? 

It ties in very closely with how we design career tracks at Fractal. We have six career tracks in total. Three are around AI. engineering and design thinking behavioral sciences, and the rest are around decision sciences. In the latter, we have people who are very good at AI and who also understand domain and design very well. They not only understand what is the business case and what is the vision requirement, but they’re also adept at converting data nuances into business language and business models. Similarly, we have people who are called information architects. These people are very strong in engineering and understand how to do storytelling from data. Not only are they able to understand massive data sets, but they are able to convert the outcomes of AI into business use cases or business stories that people understand.

Ultimately, our effort is not just to rely on people with one set of career tracks, but to rely on a combination of these career tracks in every engagement. This ensures that we get not only technical expertise, but also domain expertise.

While on the subject of career tracks, tell us about initiatives Fractal is taking to skill its employees in an ever changing tech world. 

We believe the shelf life of knowledge, especially in our industry, is less than three years. So, first of all, there’s a huge focus on learning initiatives. For example, we have our internal training academy called Fractal Analytics Academy, which focuses on each of these six career tracks I mentioned earlier. Each career track has a well-defined career plan and curriculum which depends on how many years an employee has been at the company. To get a certification, every employee is expected to complete a certain number of credits, just like they do in college.

Secondly, we also train our employees to adopt a problem-solving method at work. 

We have recently invested in a company called Analytics Vidhya. With this investment, we hope to become a net creator of talent not just within our company, but also for the global industry at large.

What are your target markets for growth?

Our vision is to create at least a billion dollars in value for each of our customers. To achieve this vision, we have to be very selective in terms of which customers we want to work with. We want to work with a very selected list of customers, perhaps less than 500 globally. And they should meet the criteria we have set in place; they should have US $10 billion in revenues, should have a valuation of US $20 billion and above, or should be serving 13 million customers. We are keeping this criteria in place because if we have to create a large impact, the company we are servicing has to be large enough.

Keeping this in mind, we have our focus on companies in the U.S, the U.K, Europe and Australia.