Predictive Modeling & Practical Insights from HR Analytics

Analytics - Computer Science and Data Science

In contemporary firms, HR analytics is essential for supporting strategic decision-making processes pertaining to human resource management. With the use of predictive modeling approaches, this article gives a thorough study of HR data and provides corporate leadership with actionable insights. Future attrition rates are forecast and previous attrition trends are analyzed with the use of logistic regression, random forest, and decision tree classifiers. The decision tree classifier is found to be the most accurate model, and the research shows variations in attrition rates over time. All models show potential for improvement in terms of recall and precision, despite this. Implementing staff engagement programs, retention tactics, and routine monitoring are suggested as ways to address attrition in light of these findings. This work adds to the expanding corpus of research on HR analytics.

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