MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202511124874 A) filed by Megha Bhatia; Nisha Agarwal; Himanshu Gupta; Swati Rai; Aarti Garg; and Nikhil Gupta, Moradabad, Uttar Pradesh, on Dec. 10, 2025, for 'integrated data-driven human resource retention system using digital literacy and leadership-enabled decision framework.'
Inventor(s) include Megha Bhatia; Nisha Agarwal; Himanshu Gupta; Swati Rai; Aarti Garg; and Nikhil Gupta.
The application for the patent was published on Jan. 23, under issue no. 04/2026.
According to the abstract released by the Intellectual Property India: "This invention presents an integrated system for improving workforce retention by combining human resource analytics with assessments of employee digital literacy and leadership commitment. The system gathers data from multiple HR functions-recruitment, training, performance, rewards, career development, and digital usage-and processes this information to identify indicators of employee disengagement or turnover risk. A predictive module quantifies attrition probability, while a digital literacy component assesses technological capability gaps that may influence job performance or organisational participation. A leadership evaluation feature examines managerial readiness for digital transformation, commitment to employee development, and consistency in HR decision-making. Both digital literacy and leadership commitment serve as moderating elements within the system's analytical logic, enhancing the fidelity of retention predictions and clarifying the sources of workforce instability. The system then generates recommendations tailored to organisational and individual needs, including training initiatives, revised managerial practices, or strategic HR interventions. A reporting dashboard presents retention forecasts, readiness assessments, and recommended actions in an accessible format. The invention addresses a critical deficiency in existing HR technologies by integrating organisational context into predictive retention modelling. This makes it particularly effective for environments undergoing digital change or those facing resource limitations. The system provides a comprehensive, evidence-based framework for understanding and improving employee retention."
Disclaimer: Curated by HT Syndication.
