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Predictive HR analytics is another aspect of strategic workforce planning that this research paper focuses on as complemented by machine learning. Employing the two large datasets obtained from Kaggle, the paper undertakes an analysis of primary selected employee attributes to make Workforce forecasts with the intention of fostering better choices within corporations. These findings show that machine learning models can predict employee turnover, job satisfaction and many other important factors of HRM enabling managers to allocate organizational resources in the most efficient manner. It indicates that this approach of employing available data leads to better strategies so that businesses stay relevant and proactive in an increasingly competitive environment. The study also opens up path for future studies and suggest that one can explore newer and more sophisticated machine learning algorithms and can also integrate real time data in order to enhance prediction accuracy and cover wider area of businesses.

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This page is a summary of: Strategic Workforce Planning with Predictive HR Analytics: Machine Learning Insights and Techniques, November 2024, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/icaccm61117.2024.11059099.
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