• Author: Szymon Swiezy
• Email: [email protected]
• Website: www.datascienceportfol.io/szymonswiezy
• Dashboard: www.novypro.com/project/hr-analysis-power-bi-9
• LinkedIn: www.linkedin.com/in/szymon-swiezy

The project looks at different parts of employee info to help make smarter decisions. By checking things like which department has the most workers and the gender breakdown, we get a big picture of how the company is doing. This helps us spot any trends or issues and come up with plans to make things better, like keeping employees happy and reducing turnover. It's all about making the organization run smoother and keeping everyone happy at work. The insights gained from analyzing employee data empower us to tailor strategies that not only enhance employee satisfaction but also contribute to the overall success and sustainability of the organization.

The goal is to demonstrate the ability to analyze, visualize, and extract insights driving actionable recommendations using Power BI.

All data used in the HR analysis project is sourced from a single file, which contains diverse information about employees in a fictional company. Each column covers key employment aspects:

• Attribute
• Date of Birth (DOB)
• Employee Age (Emp Age)
• Surname
• Name
• Gender
• Marital Status
• Branch
• Hire Date
• Leave Reason
• Employment Status (Status)
• Department
• Employee Satisfaction
• Annual Salary ($)
• Bonus ($)
• Total Compensation
• Job Title
• Job Description
• Managerial Status (Manager - Y/N)
• Performance
• Leave Date

This consolidated data source enables a comprehensive understanding of the company's workforce situation and facilitates thorough analysis, leading to insightful conclusions and effective actions.

The data is in CSV format and was processed in Power Query. Following initial data exploration, key KPIs and relevant information were selected for analysis, including:

- Total number of employees by department - Employee satisfaction levels - Gender distribution of employees - Gender pay gap within the company - Peak periods of the gender pay gap - Average satisfaction, salary, bonus, and employee count by gender and department - Department with the highest employee attrition rate - Reasons for employee departures - Distribution of employed workers by age group.

The entire dashboard consists of various visualizations and data storytelling, which allows users to have a better understanding during analysis and use of the dashboard. There is also the possibility of applying various filters such as:

• Year
• Branch
• Department
• Gender
• Manager
• Marital Status
• Job Title
• Performance
• Status
• Age Group

The average salary is $70.54k annually and has decreased by 7.6% compared to the previous year.

The average job satisfaction is 3.86 on a scale of 1-5 and has decreased by 7.4% compared to the previous year.

The company employs 292 workers, marking a 16.9% increase compared to the previous year.

The Employee Attrition Rate is 14.7, a significant decrease from the previous year's 28.41.

The majority of employees work in the Production department (65.41%).

Employees in the Management department are the most satisfied, while those in Administration are the least satisfied.

Male employees still comprise the majority, but there's a gradual shift towards gender balance favoring women in recent years.

The gender pay gap stands at 9.63%, equivalent to $7099.

The gender pay gap has persisted within the organization, showing no signs of improvement.

This gap is offset by higher bonuses for women.

The Production department experiences the highest Employee Attrition Rate, nearly 18%.

Employees most commonly leave due to factors like higher salary offers and performance issues.

The majority of employees fall within the 60-69 age group, with a significant number hired in the current year.

Of course, by analyzing the entire dashboard, hundreds of other valuable insights can be drawn due to the large number of variables, and the entire report serves as just an introduction to a more in-depth HR analysis.