This project analyzes employee attrition data using Power BI with comprehensive dashboards and workforce insights for strategic human resources management.
This project analyzes employee attrition patterns across 1,470 employees to identify retention risks and workforce trends. The analysis examines demographic factors, job satisfaction levels, salary distributions, and tenure patterns that influence employee turnover. Strategic insights support HR decision-making for talent retention, compensation planning, and department-level workforce optimization.
The dashboard provides actionable intelligence for HR managers balancing employee satisfaction with organizational stability. By analyzing historical patterns across departments, education levels, and career stages, this investigation reveals evidence-based findings that inform retention strategies and reduce costly turnover.
The HR database connects employee demographics to job roles, departments, and education levels through a normalized structure. This design enables multi-dimensional analysis across attrition patterns, compensation, and workforce characteristics.
HR analytics reveals a 16% attrition rate (238 departures from 1,470 employees) with significant disparities across departments and demographics. Research & Development shows highest attrition (133 employees), while early-tenure employees (0-2 years) demonstrate peak turnover risk. Male attrition (151) significantly exceeds female (87), and Life Sciences graduates account for 37% of all departures. Analysis identifies actionable opportunities for targeted retention programs and compensation adjustments.
Research & Development accounts for 56% of departures (133 attritions) despite being one of three departments, indicating systemic issues in career advancement and compensation. Male employees show 73% higher turnover rate (151 vs 87 female), with Laboratory Technicians, Sales Executives, and Research Scientists most affected.
Life Sciences graduates represent 37% of attritions (89 employees), followed by Medical degree holders at 27% (63 employees) and Marketing graduates at 15% (35 employees). These patterns suggest misalignment between educational background and career satisfaction within current organizational structure.
Employees with 0-2 years tenure show highest attrition with peak departures in year 1, while those beyond 5 years exhibit significantly lower turnover probability. This highlights critical importance of effective onboarding and early-career support programs.
Employees earning under $5k monthly demonstrate disproportionately high attrition. Retention improves at $5k-10k range with best results above $10k. Average income of $6.5k ($65k annually) sits in high-risk zone, suggesting targeted raises could significantly improve retention.
Early-career mentorship and regular check-ins can reduce first-year turnover risk. Addressing R&D's 56% attrition through competitive compensation and clear advancement paths is critical. Salary adjustments for under $5k earners can improve retention in highest-risk brackets. Specialized development programs for Life Sciences graduates can reduce 37% of departures, while exit interviews can reveal causes of male attrition disparity.
The dataset covers 1,470 employees across three departments (Research & Development, Sales, Human Resources) with 38 attributes including demographics, job roles, education levels, satisfaction metrics, compensation details, and tenure information.
This analysis was built using Power BI Desktop with comprehensive data modeling and interactive visualizations. The implementation leveraged advanced analytical techniques across multiple dimensions:
- Power BI: Interactive dashboards with dynamic filtering, DAX measures, Power Query data transformations, and data modeling with table relationships
- Data Analysis: Descriptive statistics, comparative analysis across departments and demographics, trend identification for tenure patterns, and segmentation analysis for education and compensation groups
- Visualization: Dynamic KPI cards, donut charts for education distribution, bar charts for department comparison, line graphs for tenure trends, and matrix tables for job satisfaction analysis
This repository contains the complete Human Resource Analytics Project with the following components:
HR Analytics Dashboard.pbix- Interactive Power BI dashboard with DAX measures and filtering capabilitiesdataset.xlsx- Complete employee dataset with demographics, job roles, and attrition recordsREADME.md- project documentation with findings and recommendations
