People analytics has brought a paradigm shift in the processes, technologies and systems of organizations. Success is driven here through data-driven methodologies. The primary objective of this research is to identify, rank and interrelate challenges affecting the adoption of people analytics in India. The interpretative structural modelling (ISM) approach is applied to rank and interrelate these challenges in the Indian context. MICMAC analysis is conducted to reveal the driving power and dependence of these challenges of people analytics. The MICMAC analysis also indicates the relative importance and interdependence between these challenges in the Indian context. During the first phase of the research, 12 challenges are identified from the literature, and these people analytics challenges are validated based on expert opinions. During the second phase, ISM identifies ‘Leveraging existing enterprise resources’ as the most important challenge in the Indian context among the 11 validated challenges. MICMAC analysis identifies all 11 challenges as ‘linkage challenges’ with high dependence and driving power. For researchers, this methodology facilitates further carrying out exploratory studies and focusing their interactions through hierarchical structures. The study investigates the core issue among many issues faced by people analytics professionals. Second, it has methodological novelty in the context. Finally, it points to multidimensional implications for various stakeholders in people analytics in the Indian context.