Who's Likely to Quit - Employee Turnover Prediction Analytics
Using predictive analytics to identify at-risk employees for proactive retention strategies
📊 Key Performance Metrics
87%
Prediction Model Accuracy
€45K
Average Turnover Cost
3.2 Years
Average Employee Tenure
💡 Strategic Insights
1
High Prediction Accuracy
Machine learning model achieves 87% accuracy in predicting employee turnover risk 6 months in advance
2
Significant Cost Impact
Each employee turnover costs approximately €45K in recruitment, training, and lost productivity expenses
3
Critical Risk Periods
Employees show highest turnover risk during years 1-2 (adjustment period) and after 5+ years (career plateau)
📈 Data Visualization Summary
⚠️ High Risk: Years 1-2 & 5+ | Cost per loss: €45K | Prediction accuracy: 87% | Avg tenure: 3.2 years
🎯 Strategic Action Plan
🚀 Primary Focus: Leverage the key insights from this comprehensive analysis to drive strategic decision-making and optimize business performance across all identified areas.
📈 Implementation Priority: Focus resources on the highest-impact metrics and findings identified in this dashboard to maximize return on investment and accelerate growth.
📊 Performance Monitoring: Establish robust KPI tracking systems based on these analytical findings to ensure continuous improvement and maintain competitive advantage.
🔄 Continuous Optimization: Regularly review and update strategies based on ongoing data collection to maintain relevance and effectiveness of implemented solutions.