HR Analytics Dashboard: Employee Attrition & Workforce Insights

OBJECTIVE: Develop a dynamic HR analytics dashboard to visualize workforce demographics, attrition trends, and key HR metrics. The dashboard empowers HR managers to monitor employee turnover, explore patterns by department, age, tenure, and salary, and gain actionable insights for talent retention strategies.

BACKGROUND: Understanding employee attrition is critical for workforce planning and HR decision-making. This project was designed to consolidate raw HR data into a visually engaging and interactive Power BI dashboard, making it easier to track turnover metrics and segment attrition by demographics, education, job role, and satisfaction level. The goal was to automate data cleaning and support drill-down exploration by department.

TECH STACK:

1. Microsoft Excel: Used to preview and inspect raw data structure prior to import

2. Power BI (Power Query): Used for data cleaning, transformations, and dashboard design

3. DAX Measures: Calculated attrition rate, average salary, and conditional columns

4. Visualizations: Donut charts, area charts, stacked bar/column charts, and matrix table with dynamic filters

PROCESS:

1. Data Cleaning in Power Query:
   ◇ Normalized inconsistent entries in categorical fields (e.g., standardizing "TravelRarely" and "Travel_Rarely" to "Travel Rarely")
   ◇ Replaced "None" values in numerical fields (e.g., years at company) with 0
   ◇ Resolved inconsistent gender labeling (e.g., "Female" → Female)
   ◇ Standardized missing or null values across key columns
   ◇ Set proper data types for analysis (e.g., whole numbers for count-based metrics)

2. Dashboard Construction in Power BI:
   ◇ Created an Attrition Count column and DAX-based Attrition Rate measure
   ◇ Built interactive filters to allow slicing by department (Human Resources, R&D, Sales)
   ◇ Designed layout to emphasize high-level KPIs (employee count, attrition rate, tenure, salary, etc.)
   ◇ Implemented drill-down visualizations to segment attrition by age, education, salary, satisfaction, and job role

KEY INSIGHTS:

1. Attrition Rate: 16% (238 out of 1480 employees)

2. Highest Attrition by Job Role: Research Scientists (100), followed by Human Resources (58)

3. Age Group Most Affected: 26–35 years old (116 attritions)

4. Gender Breakdown: Male attrition (151), Female attrition (87)

5. Salary Impact: Most attrition occurred in employees earning under 5K

6. Satisfaction & Tenure Trends: Many exits occurred within the first 2 years, especially among employees with lower satisfaction ratings

CHALLENGES & SOLUTIONS:

⚠️ Challenge 1: Raw data had inconsistencies and missing values
✅ Solution: Used Power Query to standardize entries and clean nulls automatically on refresh

⚠️ Challenge 2: Multiple formats for categorical variables (e.g., Business Travel labels)
✅ Solution: Re-mapped entries using replace logic and ensured consistency in all category fields

⚠️ Challenge 3: Needed to isolate attrition by various HR dimensions (tenure, job role, education, etc.)
✅ Solution: Created calculated columns and filters for flexible, granular analysis in Power BI

DATA SOURCE:

• Dataset: HR_Data (raw).xlsx

• Source: Internal employee records and HR system exports

VIEW THE DASHBOARD:

Want to explore the dashboard interactively?

👉 Click here to view the full Power BI dashboard — powered by Power BI and built to help HR managers monitor employee turnover, explore patterns by department, age, tenure, and salary, and gain actionable insights for talent retention strategies.

BEHIND THE DASHBOARD:

Curious how the dashboard was built?

👉 View the Power BI file (.pbix) and full calculation logic — includes all calculated fields, data transformations, and layout structure used to create the dashboard.