Kshitij Jain, head of UK/Europe analytics and global chief strategy officer, EXL Analytics
Describe your career to date
I joined EXL in 2006 as a founding member of the data and analytics practice. EXL is a NASDAQ listed firm, which provides data, analytics and digital operations services to its clients globally. The organisation has an annual revenue of approximately $1.4bn (2022 guidance) and a market cap of $5.5-$6bn.
Since joining the organisation, we have managed to grow the data and analytics business from scratch to what is now a $500 million-plus and 7,000 professionals strong entity. I have had the privilege of taking on different roles throughout, and have worked with clients in the US, UK, Europe, South Africa and Asian markets.
In my current capacity, I lead the data and analytics business for UK and Europe; a team of 600-plus professionals solving complex business problems for our clients across banking, insurance, utilities, retail, media and hi-tech industries. I am also the chief strategy officer for the business globally and am responsible for charting the future course to ensure a high growth and high impact trajectory.
Before EXL, I worked with Bank of America within M&A banking. I was also an early stage member of a research and analytics firm, where I focused on financial services analytics.
From an education perspective, I am a chemical engineer from the Indian Institute of Technology (IIT), Delhi, and completed my MBA from the University of Cambridge, where I had the privilege of appearing on the director’s list for exceptional achievement.
What key skills or attributes do you consider have contributed to your success in this role?
I feel my most important attributes have been intellectual curiosity and getting a thrill out of creative business problem solving. Over two decades in the industry, the one thing I have thrived on is the constantly evolving and expanding canvas available to us in the world of data and analytics.
What level of data maturity do you typically encounter across your client base and what tends to hold this back?
Data maturity varies vastly across industries, functions and clients, depending on their context and environment. Digital natives in less regulated industries such as retail and media tend to have more maturity in terms of use cases and ability to leverage data at scale for near real-time decisioning. On the other end of the spectrum - legacy organisations in regulated industries (eg commercial and speciality insurance) and especially those that have grown inorganically, struggle with even basic data quality, trust and availability. Of course, this is somewhat of a generalisation as there are leaders and laggards in every industry.
In general, the biggest challenge with moving up the data maturity curve is the articulation of business value of data initiatives to attract strong leadership buy-in and funding. Linked to this aspect is the lack of ongoing engagement on data programmes with the business stakeholders.
Other challenges include lack of talent availability – especially those that cut across data and relevant industry knowledge; inadequate data governance or just on paper and via committees but failing to deliver improvement in quality; sub-optimal operating models (eg centralized vs. federated) and below-par allowance for change management in data initiatives.
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