Employee Attrition Risk Summary
This result appears above the form after submission, as requested.
Interpretation
Top drivers
Calculator Inputs
Use the fields below to estimate individual attrition exposure from multiple workforce conditions.
Example Data Table
| Employee | Tenure | Engagement | Stress | Months Since Promotion | Risk Score | Band |
|---|---|---|---|---|---|---|
| A. Khan | 1.4 years | 4/10 | 8/10 | 22 months | 71.6% | High |
| S. Iqbal | 5.8 years | 7/10 | 5/10 | 10 months | 38.9% | Moderate |
| M. Ali | 9.2 years | 9/10 | 3/10 | 6 months | 19.4% | Low |
Formula Used
This calculator converts each input into a normalized risk value from 0 to 100, then applies weighted importance. The final result is a weighted risk score on a 0 to 100 scale.
- Weighted Contribution = Factor Risk × Weight ÷ 100
- Total Attrition Risk (%) = Sum of all weighted contributions
- Engagement Risk = ((10 − Engagement) ÷ 9) × 100
- Satisfaction Risk = ((10 − Satisfaction) ÷ 9) × 100
- Manager Support Risk = ((10 − Manager Support) ÷ 9) × 100
- Workload Stress Risk = ((Stress − 1) ÷ 9) × 100
- Compensation Risk increases when pay falls below market competitiveness.
- Promotion Risk increases as months since promotion rise.
- Absence, Overtime, Commute, and Team Turnover Risks increase with their values.
Risk Bands
- 0% to 34.99% = Low
- 35% to 59.99% = Moderate
- 60% to 79.99% = High
- 80% to 100% = Critical
Model Weights
The current version uses these fixed weights:
Engagement 12, Satisfaction 10, Manager Support 10, Stress 10, Compensation 8, Promotion Gap 7, Tenure 7, Team Turnover 7, Absenteeism 6, Overtime 6, Commute 5, Mobility 4, Training 3, Performance 3, Flexibility 2.
How to Use This Calculator
- Enter the employee’s current workforce, engagement, and job experience values.
- Use market-aligned compensation competitiveness, where 100 means benchmark pay.
- Click Calculate Attrition Risk to display the result above the form.
- Review the score, risk band, interpretation, and top weighted drivers.
- Use the charts to understand which factors push risk upward.
- Download the result as CSV or PDF for reporting and planning.
- Adjust a few variables and recalculate to compare retention scenarios.
Frequently Asked Questions
What does this calculator estimate?
It estimates the likelihood that an employee may voluntarily leave, using weighted workforce, engagement, workload, and retention factors. It is a planning tool, not a final employment decision tool.
Is the score a guaranteed prediction?
No. The result is an evidence-based estimate from the selected inputs. It highlights risk patterns and retention priorities, but it cannot guarantee whether someone will stay or leave.
What score range is considered high risk?
Scores from 60% to 79% are treated as high risk. Scores of 80% or more are critical risk and usually justify urgent retention review and manager action.
Why can strong performers still show high attrition risk?
High performers may still face poor manager support, low pay competitiveness, weak flexibility, stalled promotions, or heavy workload. Attrition risk depends on multiple conditions, not performance alone.
Can HR teams change the model weights?
Yes. This version uses fixed weights for simplicity and consistency. You can edit the JavaScript configuration to align the score with your internal retention model or historical data.
Should this score be used alone for HR action?
No. Use it with interviews, engagement data, manager feedback, market context, and policy review. Combining quantitative and qualitative evidence leads to better retention decisions.
What inputs usually influence the score most?
Engagement, job satisfaction, manager support, workload stress, compensation competitiveness, promotion delay, and team turnover often produce the strongest weighted effect on the final risk score.
Can this help compare retention scenarios?
Yes. Change one or two fields, recalculate, and compare results. That makes it useful for testing the impact of pay changes, promotions, workload relief, or flexibility improvements.