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@article{192352,
        author = {Dr. Radhika Nikhil Gandhe},
        title = {Using Big Data to Measure Quality of Work Life in Public Sector Organisations: Opportunities & Concerns},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {1039-1043},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192352},
        abstract = {Public sector organisations across the world are undergoing rapid digital transformation, characterised by the adoption of biometric systems, human resource management platforms, algorithmic scheduling tools, and data analytics dashboards. These technologies generate vast quantities of employee-related data that are increasingly used to inform administrative decisions, performance evaluations, and workforce planning. In recent years, such data-driven systems have also been proposed as tools to assess and monitor the Quality of Work Life (QWL) of employees. This paper critically examines the use of big data to measure QWL in public sector organisations, with particular reference to the Indian context. Drawing on interdisciplinary literature from human resource management, sociology of work, and critical data studies, the paper analyses how digital traces such as attendance logs, workflow metrics, sentiment analysis, and surveillance data are interpreted as indicators of well-being, engagement, and job satisfaction. While big data offers opportunities for enhanced transparency, evidence-based policy formulation, and predictive identification of workplace stress, it also raises serious concerns related to surveillance, privacy, algorithmic bias, consent, and the reduction of complex human experiences to quantifiable metrics. Using a sociotechnical lens, the paper argues that data-driven approaches to QWL risk reinforcing power asymmetries and overlooking the subjective and relational dimensions of work life. The study concludes by proposing a responsible and participatory framework for integrating big data into QWL assessment that balances organisational efficiency with employee dignity, autonomy, and rights.},
        keywords = {Big data, Quality of Work Life, public sector organisations, algorithmic governance, HR analytics, surveillance},
        month = {February},
        }