Predict and reduce absenteeism and turnover
Predictive models that identify employees at risk of absence or resignation and recommend preventive retention actions.
Overview
The Absenteeism & Turnover accelerator uses HR data, organizational climate and behavior data to predict which employees are most likely to be absent or resign.
Services
Turnover prediction
Models that identify employees with a high propensity for voluntary resignation within the next 3 to 6 months.
Absenteeism prediction
Algorithms that predict absence patterns by team, role, and period for coverage planning.
People analytics dashboard
Dashboards with engagement indicators, exit risk, and organizational health by area and manager.
Risk factors
Analysis of the main turnover and absenteeism drivers: workload, climate, compensation, distance, and profile.
Recommended action plans
Automated retention action suggestions personalized by risk profile and identified root cause.
Scenario simulation
Simulations of the impact of HR policies (compensation, benefits, flexibility) on turnover and absenteeism.
Where we operate
Where we operate with Absenteeism & Turnover
Large enterprises
Turnover management in operations with thousands of employees, with prediction by unit and role.
Contact center
Absenteeism forecasting for team sizing and turnover reduction in customer service operations.
Retail
Exit prediction for salespeople and store operators with segmented retention actions by profile.
Industry
Absenteeism monitoring on production lines and forecasting shift coverage needs.
Healthcare
Turnover prediction for nurses and doctors with workload and satisfaction analysis.
Technology
Tech talent retention with engagement analysis, market comparison, and career plan development.
How we work
HR Data Integration
Consolidation of payroll, attendance, evaluations, climate surveys, and movement history data.
Feature Engineering
Building predictive variables: tenure, promotions, relative compensation, distance, and engagement.
Modeling & Validation
Training classification models with temporal validation and feature importance analysis.
Dashboard & Alerts
Deploying dashboards with risk scores and automatic alert systems for managers.
Action & Feedback Loop
Implementing action plans, collecting feedback, and retraining the model with new data.
HR Data Integration
Consolidation of payroll, attendance, evaluations, climate surveys, and movement history data.
Feature Engineering
Building predictive variables: tenure, promotions, relative compensation, distance, and engagement.
Modeling & Validation
Training classification models with temporal validation and feature importance analysis.
Dashboard & Alerts
Deploying dashboards with risk scores and automatic alert systems for managers.
Action & Feedback Loop
Implementing action plans, collecting feedback, and retraining the model with new data.
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