Operational Efficiency of Large-Cap Indian Information Technology Companies: A Three-Year Comparative Study Using Data Envelopment Analysis

This study evaluates the operational efficiency of five large-cap Indian Information Technology (IT) companies using Data Envelopment Analysis (DEA) over three consecutive financial years (FY2023–24 to FY2025–26). A quantitative longitudinal research design was adopted using secondary data collected from the audited consolidated financial statements of Tata Consultancy Services (TCS), Infosys, HCL Technologies, Tech Mahindra, and Wipro. An input-oriented Charnes–Cooper–Rhodes (CCR) DEA model was employed to assess relative technical efficiency by considering total assets as the input variable and revenue from operations and net profit as output variables. Pearson correlation analysis was further conducted to examine the relationship between DEA efficiency scores and selected financial performance indicators. The findings reveal that Tata Consultancy Services consistently remained on the efficiency frontier throughout the study period, demonstrating sustained operational excellence, while HCL Technologies exhibited continuous improvement in efficiency. In contrast, Tech Mahindra experienced a significant decline in efficiency during FY2025–26 following rapid asset expansion, and Wipro consistently recorded the lowest efficiency scores among the sampled firms. The analysis further indicates that asset turnover exhibited a stronger positive association with operational efficiency than net profit margin during the study period. The study provides valuable insights for corporate managers, investors, and policymakers by offering a benchmarking framework for evaluating operational efficiency and resource utilization in the Indian IT sector. It also contributes to the existing literature by presenting a recent three-year comparative DEA assessment of large-cap Indian IT companies.

Data Envelopment Analysis (DEA), Operational Efficiency, Indian Information Technology Companies, CCR Model

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