BENGALURU: Infosys’s data and analytics (DNA) practice, which started five years ago, has grown into a nearly $3 billion service line, employing over 20,000 employees. The revenue is almost a quarter of the company’s total business.
Satish HC, EVP and head of global services for DNA, says they realised early on that data had become a new pivot for business transformation. He says the big turning point came when they broke away from the siloed approach to big data, analytics and business intelligence (BI) and brought them under one umbrella. “That proved to be a seminal moment in our journey,” he said.
Satish declined to talk about the revenue of the business. He also declined to talk about customer projects. But sources said DNA created a new set of capabilities and enabled a massive cost takeout for Airbus by working with the aircraft maker’s tier 1 suppliers. Infosys has a long-term engagement with Airbus that started with the Airbus 380 programme, where it was involved in the design and development of structural components.
DNA is now doing work similar to the one it did for Airbus for an auto client and its ecosystem.
“DNA has classic (legacy) and super niches (digital) as part of its portfolio. The latter is growing much faster than legacy. A lot more problems are AI and ML-oriented,” Satish said.
The interdisciplinary team comprises technologists, design thinkers and liberal arts majors. The idea was to create a cross-functional team of problem finders, while machines turned into “indefatigable problem-solvers.” A lot of automation is being employed to solve problems, while people are trying to identify more and more client problems that can be solved. The work involves data consulting, data strategising, cloud data engineering, governance, platforms and operations.
A team of specialists called Tiger supports customers through an advisory-led model, co-creating client specific-solutions. The number of people in the squad depends on the nature and magnitude of the problem.
“We are reimagining the world around us. The one area we are sharpening is our capability to frame the problem,” Satish said.
He said India will be short of data scientists soon. “We are increasingly deploying automation, freeing up the team’s time to focus on framing the problem and modelling the problem rather than cleaning data,” he said.