International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Leveraging HR Analytics for Talent Forecasting: A Strategic Approach for Organizational Success

Author(s) Aditi Poonia, Dr. Rakhi Kumari
Country India
Abstract In today's dynamic business environment, effective talent management is crucial for organizational success. HR analytics offers a data-driven approach to anticipate future talent needs, identify skill gaps, and optimize recruitment and retention strategies. This dissertation explores the strategic utilization of HR analytics for talent forecasting, aiming to enhance organizational performance and agility. Through a comprehensive review of literature, case studies, and empirical analysis, this research investigates the implementation of HR analytics for talent forecasting in organizations across various industries. The study identifies key methodologies, tools, and best practices for leveraging HR data to forecast talent demand and supply, assess workforce readiness, and support strategic decision-making. Findings highlight the significant impact of HR analytics on improving workforce planning, enhancing employee engagement, and driving business outcomes. Practical insights and recommendations are provided for organizations seeking to harness the power of HR analytics for sustainable growth and success.
Keywords HR Analytics, Talent Forecasting, Strategic Human Resource Management, Organizational Performance, Predictive Modeling, Data-driven Decision Making, Workforce Planning, Talent Management Strategies, HR Metrics, Human Capital Analytics, Predictive Analytics, Employee Retention Strategies
Field Business Administration
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-06-08
Cite This Leveraging HR Analytics for Talent Forecasting: A Strategic Approach for Organizational Success - Aditi Poonia, Dr. Rakhi Kumari - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.22403
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.22403
Short DOI https://doi.org/gtzjjv
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