HR-Analytics-using-Power-BI

Objective

The purpose of this project is to help an organization to improve employee performance and reduce attrition by creating an HR analytics dashboard. The dashboard provides valuable insights into employee data, which can be used to make data-driven decisions and improve employee satisfaction and retention.

Data Cleaning and Processing

Several steps were taken to prepare the data for analysis. Null values were removed and duplicate values were eliminated. Spelling errors were identified and corrected, and appropriate data types were assigned. Additionally, a conditional column was added for attrition count, which assigned a value of 1 for 'yes' and 0 for 'no' based on the attrition column. Furthermore, a new measure was created to calculate the attrition rate, which was derived by dividing the total attrition count by the total employee count.

Key Performance Indicators (KPIs)

To start the analysis, I have identified the key performance indicators (KPIs) to track and monitor employee performance and attrition. The following KPIs were created with card visualizations in Power BI:

1. Overall Employee
2. Attrition count
3. Attrition rate
4. Active Employee
5. Average age

Dashboard and Insights

HR_Analytics_video.mp4

I have used several charts and visualizations to gain insights into the employee data. Here are some of the key insights gained from the analysis:

1. Tree map chart: The chart showed the distribution of attrition by gender. The data showed that 150 males and 87 females had left the company, indicating that male employees were leaving the company more than female employees.
2. Pie chart: The chart displayed the attrition count by Department. The data showed that the attrition count was highest in the R&D Department, with 56.12% of employees leaving, followed by the Sales Department, with 38.82% of employees leaving.
3. Stacked column chart: The chart showed the number of employee by age group. The data revealed that the age group from 25-34 had the highest employee count of 337.
4. Matrix table: The table displayed job roles by job satisfaction scores, highlighting the big numbers in dark green. The data showed that Sales Executive had the highest employee count, followed by research scientists and laboratory technicians.
5. Stacked bar chart: The chart displayed the attrition count by education field. The data showed that the attrition count was highest in the Life Sciences field of employees leaving, followed by the Medical Field of employees leaving.
6. Donut charts: The chart displayed the Attrition rate by gender for different age group. The data revealed that the age group from 25-34 had the highest attrition count of 112.

Filters

Finally, department filters were implemented at the top of the dashboard, which allowed users to filter the entire dashboard by selecting a specific department.

Suggestions

Some suggestions for the HR department to improve employee performance and retention:

1. Investigate the reasons behind the higher attrition rate among male employees and take appropriate measures to address their concerns and needs.
2. Identify the root causes of the high attrition rate among employees in the R&D and Sales Department and take necessary steps to retain employees in these areas.
3. Address the concerns of employees in the age group of 25-34, who have the highest attrition rate, and provide them with better opportunities for career growth and development.
4. Conduct a review of the job roles with the highest attrition rate, such as Sales Executives, Research Scientists and Laboratory Technicians, to identify the reasons behind the high attrition rate and take necessary steps to address these concerns.
5. Identify the root causes of the high attrition rate among employees in the Life Sciences and Medical Fields and take necessary steps to retain employees in these areas.
6. Provide training and development opportunities for employees to help them enhance their skills and progress in their careers, which can improve job satisfaction and reduce attrition.
7. Provide employees with a supportive work environment, opportunities for work-life balance, and recognition and rewards for their contributions to the company, which can increase employee engagement and retention.

Conclusion

This HR analytics dashboard showed important information about employees that can help make better decisions and keep employees happy and working for the organization. By taking actions to address the issues that employees face and creating a positive work environment, the HR department can help employees perform better and stay in their jobs longer. This can help the organization make more money and be more successful.