Employee Turnover Prediction

Overview

Turnover prediction uses classification models (logistic regression, random forest, XGBoost) to estimate the probability an employee will leave within a defined period (typically 6-12 months). Features include tenure, compensation, performance, promotion history, and engagement signals.

When to Use

Trigger conditions:

• Identifying employees at high risk of voluntary departure
• Quantifying which factors drive turnover for targeted interventions
• Prioritizing retention budgets toward highest-impact employees

When NOT to use:

• For involuntary termination planning (different process and ethics)
• When headcount is < 200 (insufficient data for reliable modeling)

Algorithm