Use Case | Detection of Turnover Risks

Use Case: Detection of Turnover Risks

Description:
The detection of turnover risks in a municipality helps identify employees who might leave the organization and understand the reasons behind their potential departure. This analysis focuses on preventing the loss of talent, improving job satisfaction, and ensuring continuity in essential services. Using analytical models, the municipality can analyze behavior patterns, satisfaction surveys, and performance metrics to anticipate risks and design retention strategies.

How Does Turnover Risk Detection Work?

1. Data Collection:
   • Historical and current data on employees, such as:
     • Time spent in the organization.
     • Performance evaluations.
     • Participation in training or development programs.
     • Satisfaction survey results.
     • External factors such as workload, internal conflicts, or financial compensation.
2. Risk Indicator Analysis:
   • Low job satisfaction: Negative feedback or low results in internal surveys.
   • Decreased performance: Decline in productivity or efficiency metrics.
   • Frequent absences: Increased absenteeism without clear justification.
   • Lack of recognition: Poor history of promotions or rewards.
   • Misalignment with objectives: Lack of interest in key projects or assuming additional responsibilities.
3. Risk Classification:
   • High risk: Employees with multiple indicators of dissatisfaction.
   • Medium risk: Employees with intermittent signs of turnover.
   • Low risk: Employees who are committed and satisfied with their job.
4. Retention Proposals:
   • Design specific strategies based on risk level, such as:
     • Reviewing workloads.
     • Offering professional development programs.
     • Implementing financial or non-financial incentives.
     • Improving internal communication and recognition mechanisms.

Practical Example
Scenario:
A municipality detects that several key employees in technical areas have left their positions in the past year, affecting the quality of public services.

1. Data Collected:
   • Satisfaction surveys indicate that 30% of technical employees feel undervalued.
   • Employees who have resigned had an average tenure of 5 years.
   • Increased workload after the implementation of new technological systems.
2. Analysis Results:
   • High risk: 10 technical employees with high stress levels and no participation in recognition programs.
   • Medium risk: 15 administrative employees with moderate workloads but lack of financial incentives.
   • Low risk: Citizen service area staff with high satisfaction due to recent training.
3. Model Recommendations:
   • Design a financial incentive program for the technical area.
   • Implement a recognition system to highlight individual and team contributions.
   • Allocate additional resources to reduce workload in critical areas.

Benefits for the Municipality

1. Retention of Key Talent:
   • Prevents the loss of employees with critical skills for municipal operations.
   • Example: Identifying dissatisfaction among urban planning technicians allows retention programs to be implemented before they resign.
2. Reduction of Turnover-Related Costs:
   • Minimizes recruitment, training, and productivity loss costs caused by turnover.
   • Example: Retaining a trained employee is less expensive than hiring and training a new one.
3. Continuity in Public Services:
   • Ensures that critical areas maintain trained staff, avoiding disruptions in essential services.
   • Example: Reducing turnover in urban services ensures that cleaning and maintenance tasks are not affected.
4. Improvement in the Work Environment:
   • Addressing issues such as excessive workloads or lack of recognition increases satisfaction and commitment.
   • Example: A mentorship program for new employees improves integration and reduces dissatisfaction.
5. Strategic Talent Planning:
   • Allows anticipation and planning for future vacancies, creating succession plans for key roles.
   • Example: Detecting that several employees are nearing retirement allows internal replacements to be trained in time.

Specific Applications

1. Identification of Critical Areas:
   • Detect departments or roles with a higher risk of turnover (e.g., technical staff, citizen services).
2. Design of Retention Strategies:
   • Offer professional development opportunities or financial incentives to key employees.
3. Optimization of Workloads:
   • Adjust tasks and schedules in areas with high levels of job stress.
4. Youth Talent Management:
   • Retain young employees by offering clear and attractive career plans.
5. Evaluation of Policy Impact:
   • Analyze how policies like telecommuting, flexible hours, or wellness programs affect turnover risk.

Example of Results Generated
Turnover Risk Detection Report – Technical Department:

• Risk level:
  • High: 15 employees (30% of the department).
  • Medium: 10 employees (20% of the department).
  • Low: 25 employees (50% of the department).
• Main causes:
  • 40% dissatisfaction due to lack of recognition.
  • 30% high workload during critical periods.
  • 20% perception of professional stagnation.
• Recommendations:
  • Introduce a non-financial incentive program, such as public recognition and internal awards.
  • Implement flexible hours to reduce stress.
  • Design a career plan and advanced technical training.

Conclusion
Turnover risk detection in a municipality is essential for preventing the loss of key employees, improving job satisfaction, and ensuring continuity in public services. An analytical model helps identify patterns, predict risks, and design personalized strategies that foster talent retention and optimize human resources. This strategic approach strengthens employee commitment and ensures that the municipality can effectively meet its objectives.