HR Analytic Project
My Project
Project Title: HR Analytic project
Status : Completed
Structured data , Qualitative and Quantitative data
This project provides a comprehensive analysis of Puma’s employee attrition rate, incorporating a performance tracker to identify trends, patterns, and correlations between employee performance and turnover. By leveraging data analytics, we aim to offer actionable insights to improve employee retention and optimize workforce management strategies.
Objectives
Analyze Attrition Rate: Determine the factors contributing to employee attrition and identify high-risk groups within the organization.
Track Employee Performance: Monitor and evaluate employee performance metrics to understand their impact on retention.
Provide Insights: Generate actionable insights to inform HR policies and improve employee retention strategies.
Data-Driven Decisions: Enable data-driven decision-making to enhance overall workforce stability and productivity.
Key Metrics
Attrition Rate
Monthly Attrition Rate: Percentage of employees who leave the company each month.
Departmental Attrition: Attrition rates are segmented by department to identify areas with higher turnover.
Tenure-Based Attrition: Analysis of attrition rates based on employee tenure to understand retention trends over time.
Performance Metrics
Performance Ratings: Regular performance evaluations and ratings for each employee.
Goal Achievement: Tracking the percentage of goals met by employees within a given period.
Productivity Scores: Measurement of employee productivity and efficiency in completing tasks and projects.
Training and Development: Monitoring participation and progress in training programs and its correlation with performance.
Data Collection and Analysis
Data Sources
HR Information System (HRIS): Employee records, performance evaluations, and attrition data.
Employee Surveys: Feedback on job satisfaction, engagement, and reasons for leaving.
Training Records: Participation and completion rates for training programs.
Analytical Techniques
Descriptive Statistics: Summarize the main features of the data, providing simple summaries about the sample and measures.
Predictive Analytics: Use historical data to predict future trends and identify employees at risk of leaving.
Correlation Analysis: Identify relationships between performance metrics and attrition rates.
Findings and Insights
Attrition Trends
High-Risk Groups: Identified departments and tenure groups with the highest attrition rates.
Common Reasons for Leaving: Analysis of exit survey data to determine the most common reasons for employee turnover. Performance Correlations
Performance and Retention: Employees with higher performance ratings tend to have lower attrition rates.
To view the interactive dashboard click on View More Below