A Study on Public Grievance Redressal System (PGRS) With Reference to National Informatic Center, Anantapur

Abstract

Effective governance serves as the backbone of a thriving society, ensuring that public services operate with transparency, accountability, and efficiency. One of the essential pillars of good governance is a responsive grievance redressal system that addresses public complaints promptly and effectively. The Public Grievance Redressal System (PGRS) plays a crucial role in empowering citizens by enabling them to raise grievances and track their resolution status. However, with the increasing volume of grievances and the growing complexity of issues, traditional manual approaches are proving insufficient. This study introduces a data-driven framework that leverages advanced data analytics and machine learning techniques to enhance the efficiency of grievance resolution. By analyzing grievance data from Anantapur District spanning the periods 2023-24 and 2024-25, the study identifies key patterns, predicts resolution timelines, and provides actionable insights to optimize redressal mechanisms. The predictive models, validated through rigorous cross-validation techniques, offer a robust foundation for improving grievance management processes. In conclusion, integrating technology with public grievance systems has the potential to revolutionize governance by fostering trust, transparency, and accountability, ultimately enhancing the citizen experience in an evolving digital landscape.