HR Analytics Dashboard: Unlocking Insights with Power BI

Project Overview

In this project, I built a fully interactive HR Analytics Dashboard using Power BI to analyze key workforce trends and provide actionable insights. The project focused on understanding employee recruitment, retention, engagement, and overall workforce performance. By leveraging Power BI’s visualization and analytical capabilities, I transformed raw HR data into a comprehensive dashboard that supports data-driven decision-making.

Dataset Description

The dataset contained four key tables with detailed HR data, including:

• Employee Data – Information on employees such as demographics, job roles, tenure, and performance.
• Recruitment Data – Applicant records, including application dates, education, experience, and hiring decisions.
• Employee Training Data – Training participation records and completion rates.
• Engagement Survey Data – Employee feedback on engagement and workplace satisfaction.

The dataset required cleaning and transformation before analysis, including handling missing values, standardizing formats, and creating relationships between tables to enable deeper insights.

Project Process

Step 1: Data Cleaning & Transformation in Power Query

Before diving into analysis, I cleaned and transformed the raw data in Power Query to ensure accuracy and usability. Key steps included:

• Handling Missing Data: Replaced null values where possible and removed unnecessary columns.
• Standardizing Formats: Ensured consistency in date formats, text capitalization, and categorical labels.
• Creating Calculated Columns: Extracted age from date of birth, tenure from hire date, and standardized job titles.
• Merging & Relating Tables: Established one-to-many relationships between recruitment, employee, training, and engagement survey data to ensure seamless cross-table analysis.

Step 2: Creating DAX Measures for Insights

To drive deeper insights, I created custom DAX functions for calculations, such as:

1. Employee Turnover Rate:

Calculated the percentage of employees leaving each department:

2. Engagement Score vs. Performance Correlation:

To assess the relationship between engagement and performance, I created an average engagement score per performance rating:

3. Percent Change in New Hires by Age Group:

This measure helped track hiring trends across different age brackets:

Step 3: Designing Interactive Dashboards

With clean data and calculated insights, I built visualizations that told a clear story. Key visuals included:

• Recruitment Trends → Stacked column charts to compare hiring trends by education, experience, and gender.
• Employee Retention & Separations → Pie charts and line graphs to analyze the reasons and trends behind separations.
• Workforce Demographics → Bar charts breaking down employees by age, gender, and department.
• Engagement vs. Performance → Scatter plots illustrating the correlation between engagement scores and performance ratings.
• Training & Development Impact → Heat maps showing the link between training participation and promotions.

Step 4: Adding Filters and Drill-Throughs

To enhance user interaction, I implemented slicers for:
✅ Filtering by Department, Job Role, or Performance Rating
✅ Selecting Time Periods to compare trends year-over-year
✅ Drill-through functionality to deep dive into individual employee records

Key Questions Explored & Findings

1. Recruitment Efficiency – What factors influence hiring decisions?

• Only 20% of applicants receive a job offer, meaning the recruitment process is highly selective.
• The average applicant has 10 years of experience, suggesting the company prioritizes experienced candidates.
• Salary expectations are relatively consistent across education levels, with Bachelor’s, Master’s, and PhD holders requesting similar salary ranges. This suggests that education level alone does not strongly influence salary expectations.
• Hiring volume fluctuates across months, indicating seasonal patterns in recruitment.

2. Workforce Demographics/Retention – How is the workforce structured?

• The company has 3,000 employees with an average age of 53.81 years, suggesting an aging workforce.
• Gender split: 56.07% male, 43.93% female.
• Racial diversity is well-balanced, with no single group forming a majority.
• The largest workforce segments are in Field Operations (789 employees) and General Construction (509 employees), while specialized teams like Finance & Accounting (70 employees) and Safety (9 employees) are much smaller.
• The company’s attrition rate is 51.10%, indicating significant workforce turnover.
• Employees leave for a variety of reasons, with similar counts for voluntary resignation, involuntary termination, and retirement (~380 employees each).
• Turnover appears consistent across demographic groups, with no single gender or racial group dominating separations.

3. Engagement vs. Performance – Is there a correlation?

• Employees with higher engagement scores (4-5) are more satisfied and perform better, while those with low engagement (1-2) have lower satisfaction and performance.
• Engagement and satisfaction fluctuate over time, showing dips in certain months, which may indicate seasonal morale challenges.
• Departments with high engagement scores tend to have better employee performance ratings, reinforcing the importance of engagement in productivity and retention.

4. Training & Development Impact – Does training lead to promotions?

• The company spent $1.68 million on training, with an average of 2.98 training sessions per employee.
• 770 employees successfully completed training, while 716 failed, indicating room for improvement in training effectiveness.
• Departments such as IT/IS and Admin Offices show higher failure rates in training, suggesting targeted improvements may be needed in those areas.
• Employees who complete training show higher performance ratings and promotion potential, making training a key driver of professional development.

Conclusion

This HR Analytics Dashboard provided critical insights into recruitment trends, employee retention, workforce demographics, engagement, and training effectiveness. The data-driven approach uncovered key areas for improvement and optimization:

• Recruitment is highly competitive, with only 20% of applicants receiving offers. The company prioritizes experienced candidates, and salary expectations remain consistent across education levels.
• Employee turnover is high (51.10%), with voluntary resignations, involuntary terminations, and retirements occurring at similar rates. Addressing retention strategies—especially among high-risk groups—could reduce attrition.
• The workforce is aging, with an average employee age of 53.81 years, signaling a potential need for succession planning and younger talent acquisition.
• Employee engagement strongly correlates with performance, with higher engagement scores leading to better satisfaction and productivity. However, engagement fluctuates throughout the year, highlighting potential seasonal challenges.
• Training investment is substantial ($1.68M), but effectiveness varies, with nearly equal completion and failure rates (770 vs. 716 employees). Departments like IT/IS and Admin Offices struggle more with training success, indicating potential opportunities for training program improvements.

Business Recommendations:

✔ Refine recruitment strategies to increase efficiency and ensure the best candidates progress through the hiring process.
✔ Focus on engagement initiatives to boost morale and reduce turnover, particularly in months where satisfaction scores dip.
✔ Improve training effectiveness by identifying causes of high failure rates and enhancing program content in lower-performing departments.
✔ Consider succession planning, as the aging workforce may present future workforce gaps if not proactively addressed.