Case Study: Gender Pay Gap Analysis

Gender equality in the workplace is essential for fostering a diverse and inclusive organizational culture. One of the aspects of this equality is addressing the gender pay gap, which reflects the disparity in earnings between different genders.

Technical Overview

This article presents an approach to analyzing the gender pay gap through an interactive dashboard that highlights key metrics and visualizations. The analysis utilizes the publicly available IBM HR dataset from Kaggle, which includes information on nearly 1,500 current and former employees. 

The dataset was visualized using Python, employing the Holoviews, Matplotlib, and Panel libraries. Further details and code can be found on the GitHub repository. Two interactive dashboards have been deployed on Hugging Face Spaces, allowing users to explore the insights in an engaging format.

Gender Pay gap analysis

First dashboard explores the relationship between monthly income and hourly rate, considering factors such as employee tenure and age. It also disaggregates these metrics by gender, providing a detailed view of how pay structures differ among employees.

Employee income increases with tenure for both genders. However, after 15 years with the company, income levels become more volatile. Notably, there is a drop in both monthly and hourly pay for females, which may be influenced by a significant outlier in the dataset.

The analysis of income by age shows that average monthly salaries for both genders tend to increase with age. However, after age 40, income levels become more volatile, showing more significant fluctuations. Interestingly, hourly pay appears less influenced by age overall. Women in their early twenties initially earn a higher hourly wage than their male counterparts, but around age 25, men begin to earn more per hour. This difference stabilizes somewhat in middle age and then begins to fluctuate again after age 50.

Second Dashboard focuses on employees' monthly income in relation to gender, departmental affiliation, and turnover by gender.

The data indicate a clear link between compensation and employee retention, with employees earning lower salaries—especially women—being more likely to leave the company. This trend is most pronounced in Human Resources, where both male and female employees who left earned significantly less than their counterparts who stayed. These patterns suggest that retention efforts might benefit from a focus on equitable compensation practices across genders and departments, particularly in roles with high attrition and lower earnings. 

Conclusion

Conducting a gender gap analysis is crucial for companies as it fosters a more inclusive work environment, enhancing employee satisfaction and retention. By addressing gender disparities, companies can boost innovation and improve decision-making through diverse perspectives. This leads to better financial performance and strengthens the company's reputation, making it a strategic move for sustainable growth and success.