Shylu John

Global Data, AI, and Analytics Transformation Leader with over 25 years of delivering enterprise growth, market leadership, and governance impact across Fortune 500 and multinational corporations. Expert in aligning advanced analytics, AI innovation, and digital transformation with corporate strategy, regulatory compliance, and shareholder value creation. Proven record of shaping $10M–$200M growth trajectories, building and leading global teams of 100–200+ professionals, and sustaining 100% client satisfaction in mission-critical engagements spanning Asia-Pacific, Europe, and North America. Established and scaled data and AI business units, delivering 50+ new use cases and generating €15M+ in measurable client benefits in last three years. Brings to the boardroom deep expertise in data ethics, AI governance, risk management, ESG-linked analytics, and industry diversification, with a history of guiding C-suite executives through technology disruption, market expansion, and complex governance decisions in highly regulated industries.

Career Highlights:

§ Global Analytics Leadership & Revenue Impact: Directed enterprise-wide data and AI transformation initiatives for Fortune 500 clients, leading global teams of 100–200+ professionals. Delivered 2X revenue growth (2021–2023) for an insurance major through new analytics offerings and proactive selling strategies; achieved 4X revenue growth (2015–2020) by building a global delivery practice and CX-focused analytics portfolio.

§ Innovation & Industry Positioning:Developed 100+ analytical solutions by cultivating a culture of innovation and knowledge management; positioned Concentrix Analytics as an industry leader, securing top spots in Everest Group CX Analytics Services Peak Matrix (2019)and NelsonHall NEAT for Advanced Analytics BPS & CMS Transformation (2016).

§ Award-Winning Transformation & High-Value Projects: Led the AI-based solution that earned the BIG Award – Excellence in Customer Service: Transformation of the Year (2020); executed consultancy projects tackling acquisition fraud for a $163B retail consumer finance business for GE Capital.

§ Recognition & Thought Leadership:Published 11 articles, authored 2 intellectual property rights (IPRs), and developed 2 case studies in business analytics and data science; honored with the Ranyard Medal (UK) for global contributions to analytics and named among India’s Top 50 Chiefs for AI-driven enterprise transformation.

Fellow of Royal Statistical Society, UK

● Fellow of Royal Statistical Society, UK.

● Ranyard Medal Winner 2020/21, Issued by The Operational Research Society, UK, Dec 2022. Awarded in recognition of the most outstanding contribution to the philosophy, theory or practice of business analytics published in JBA.

● Top 50 Chiefs 2019-20, Issued by TapChief Community, India.

● Authored 11 publications in leading journals, 2 IPR’s, and 2 case studies in IVEY publishing in business analytics and data science field:

• S. John and B. J. Shah; Concentrix Corporation: Improving Customer Persistency for an Indian Insurance Company, IVEY Publishing, 2022.
• S. John, P. Kartha, R. Graghu and B. J. Shah, Concentrix Corporation: Analytics to Audit Claims in Customer Management Services, IVEY Publishing, 2021.
• S. John, B. J. Shah, V. Dixit and A. Wani, ‘An integrated approach to renew software contract using machine learning., 2021, Vol. 4, No. 1, pp. 14-25.
• S. John, B. J. Shah and P. Kartha, ‘Refund fraud analytics for an online retail purchases', Journal of Business Analytics, 2020, Vol. 3, No. 1, pp. 56-66.
• S. John, S. Vijayan and K.S. Priya, ‘Effect of Macro-economic variables on Healthcare Loan/Lease portfolio delinquency rate', ERM Symposium, Chicago, April 2010.
• S. John, S. Sikdar, P. K. Swamy, S. Das and B. Maity, ‘Hybrid GA-ANN model to predict and optimise flatness value for hot rolled strips', Journal of Materials Processing Technology,2008, Vol. 195, 1-3, pp. 314-320.
• Mukhopadhyay and S. John, On-line property prediction system for hot rolled coil (OPPRESS), ROC No. SW/2460/2005, dt. 24/10/2005.
• Mukhopadhyay and S. John, Mining WARMSS-MP: a data mining-based system for prediction of properties of TMT wire rods in wire rod mill, Application no. 250/05/CAL, dt. 27/11/2005.

Certified Agile Leadership