MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541123135 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy College Of Engineering and Technology; Malla Reddy Vishwavidyapeeth; Malla Reddy University; and Malla Reddy Engineering College For Women, Medchal-Malkajgiri, Telangana, on Dec. 6, 2025, for 'multi-layer behavioral analytics platform for predictive workforce planning.'
Inventor(s) include Dr. S. Narender; Bala Veeravatnam; Mr. Valle Shyam Kumar; Dr. Ekta Maini; Dr. Nalli Vinaya Kumari; and Dr Mustaq Ali.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The current invention reveals a Multi-layer Behavioral Analytics Platform (MBAP), an innovative computational framework that improves the strategic workforce planning process, as it more precisely predicts the future talent needs, predicts the most significant changes in personal behavior (e.g., voluntary turnover), and analyzes the skills gaps on the basis of the non-disruptive, uninterrupted analysis of aggregated and anonymized employee behavioral data. Traditional methods of workforce planning are based on lagged, subjective and old fashioned human resources (HR) data (e.g. previous turnover rates, performance review scores, survey responses) that lacks the captivity of the real-time dynamics of the employee engagement, stress and collaboration patterns. The MBAP solves this inadequacy by creating a direct connection between the behavior of operations and the strategic organizational requirements. The main component of the MBAP is the Behavioral Data Fusion Engine (BDFE). This engine applies a Multi-Mode Time-Series Model (MMTSM) (e.g. special Transformer network) to combine various, aggregated data layers: Operational Metrics (e.g., tool usage frequency, code commit patterns, email communication volume), Collaboration Networks (e.g., inter-team communication frequency, meeting attendance), and Environmental Signals (e.g., remote access patterns, project load metrics). The BDFE is also set to detect non-linear and complex Predictive Signatures which will be associated with certain combinations of these behavioral patterns and future events, i.e., whether an employee will leave voluntarily or whether a team will achieve a high project success. The result of the BDFE is a Workforce State Vector (WSV). This is a continuous and quantified measurement over various dimensions such as Flight Risk Score, Skill Obsolescence Rate, and Team Load Imbalance. This platform then utilizes a Strategic Simulation Module (SSM) that takes into account the WSV to simulate the effect of different scenarios of planning (e.g., introduce a new project, require a compulsory training program) on future talent supply and demand. This modelling would enable the HR and business leaders to experiment and execute resource allocation efforts with predictive accuracy. The MBAP makes workforce planning a strategic capacity that is proactive and continuous rather than reactive and annual by combining real time operational metrics with sophisticated temporal modelling. The result is lower unplanned turnover expenses, greater efficiency in talent investments and greater in line with future business needs."
Disclaimer: Curated by HT Syndication.
