Use Case | Optimization of Public Recruitment Processes

Use Case: Optimization of Public Recruitment Processes

Description:
Optimizing public recruitment processes in a municipality aims to streamline and enhance the selection of personnel to fill vacancies in the municipal administration. This approach includes the use of advanced models to filter and prioritize candidates, automate administrative tasks, and ensure transparency and objectivity in decision-making. This reduces selection times, optimizes resources, and ensures that the chosen candidates are the most suitable for each position.

How Does Public Recruitment Optimization Work?

1. Candidate Data Collection:

• Relevant information is gathered, such as:
  • Resumes and professional experience.
  • Academic qualifications and required certifications.
  • Results from selection tests (e.g., written exams, psychometric tests).
  • Scores on merits and specific criteria.
  • Data from previous calls, if applicable.

2. Evaluation Criteria:

• Job fit: Comparison of the candidate’s profile with the specific requirements of the position.
• Regulatory compliance: Verification that candidates meet current public hiring regulations.
• Experience and skills: Assessment of relevant work experience and competencies.
• Test performance: Analysis of scores obtained during the selection process.

3. Automated Analysis:

• The model analyzes the collected information, prioritizing candidates who best meet the established requirements.
• It automatically filters profiles that do not meet basic criteria, such as minimum education or specific experience.

4. Report and Ranking Generation:

• The system generates a ranking of candidates based on overall scores.
• It offers suggestions to optimize the process, such as adjustments to selection criteria or identification of potential biases.

Practical Example

Scenario:
A municipality needs to fill three vacancies for administrative technicians. Five hundred candidates apply, and the process must be completed within two months.

Process with the Model:

1. Data Collected:

• Education: Degree in administration or related fields.
• Experience: Minimum of 3 years in public administration or similar.
• Tests: Technical exam and merit evaluation.
• Languages: Intermediate level of English, valued as a merit.

2. Analysis Results:

• Top Candidates:
  • Ana López: Meets all requirements and achieves the highest scores in the tests.
  • Juan García: High scores in merits and relevant experience.
• Discarded Candidates:
  • María Pérez: Does not meet the required education level.
  • Pedro Ruiz: Insufficient experience in the public sector.

3. Generated Report:

• Ranking of the top 20 candidates.
• Details on areas for process improvement (e.g., adjusting criteria for future calls).

Benefits for the Municipality

1. Reduced Selection Times:

• Automates administrative tasks such as reviewing resumes and merits, reducing the time needed to evaluate a large volume of candidates.
  • Example: Instead of manually reviewing 500 applications, the model automatically preselects the 50 most qualified candidates.

2. Transparency and Regulatory Compliance:

• Ensures that recruitment is based on objective criteria and complies with public hiring laws.
  • Example: A detailed report shows how scores were assigned and decisions made, eliminating doubts about potential favoritism.

3. Identification of the Most Suitable Talent:

• Prioritizes candidates with the skills and experience most aligned with the position and municipal needs.
  • Example: Identifying a candidate with prior digitalization experience for an administrative services position.

4. Human Resource Optimization:

• Reduces the workload of staff in charge of the selection process, freeing them up for more strategic tasks.
  • Example: The model performs the initial analysis, and managers only evaluate the top-ranked candidates.

5. Adaptability for Future Calls:

• Provides insights to adjust criteria in future calls, ensuring continuous improvement of the process.
  • Example: Identifying that few candidates meet a specific requirement, such as a high level of English, may lead to reevaluating its importance for the position.

Specific Applications

1. Mass Recruitment Processes:

• When the municipality needs to fill a large number of vacancies in a short time.

2. Specialized Calls:

• For technical roles requiring specific skills, such as urban engineers or sustainability experts.

3. Reserve List Management:

• Creating and maintaining lists of preselected candidates to efficiently fill future vacancies.

4. Merit and Scoring Validation:

• Automated validation of scores based on experience, education, and tests.

5. Equality Policy Compliance:

• Analyzing diversity in recruitment to ensure equal opportunities.

Example of Generated Results

Recruitment Process Report – Administrative Technicians:

• Preselected Candidates: 20.
• Average Scores:
  • Education: 8/10.
  • Experience: 7/10.
  • Selection Tests: 9/10.
• Recommendations:
  • Adjust experience criteria to attract more candidates.
  • Include an interview phase for top-ranked candidates.

Conclusion

Optimizing public recruitment processes in a municipality ensures that selected candidates are the most suitable for the positions, reducing time, costs, and associated risks. It also promotes transparency and regulatory compliance, reinforcing public trust in municipal management. Implementing advanced models enables a more efficient, fair, and strategic approach to managing public talent.