HR-Analytics-Dashboard

Dashboard Link : https://app.powerbi.com/groups/me/reports/384d017e-e935-44dc-9e7d-1626c1a36de1/ReportSection

Project Objective

Develop an HR Analytics Dashboard to aid in optimizing employee performance and enhancing retention strategies, ultimately mitigating attrition within the organization.

Steps followed

• Step 1 : Load data into Power BI Desktop, dataset is a csv file.
• Step 2 : Open power query editor & in view tab under Data preview section, check "column distribution", "column quality" & "column profile" options.
• Step 4 : Observations reveal the presence of null and empty values in certain columns.
• Step 5 : To quantify attrition, a new column named "AttritionCount" was created from the existing "Attrition" column. This new column assigns a value of 1 for "Yes" and 0 for "No."
• Step 6 : In the report view, under the view tab, theme was selected.
• Step 8 : Total 8 charts has been created.
• Step 9 : Six card visuals were added to the canvas: the first one represents the count of employees, the second represents the count of attrition, the third represents the attrition rate, the fourth represents the average age, the fifth represents the average salary, and the last card represents the average years of service.

Snap of new column called AttritionCOunt ,

Report Snapshot (Power BI DESKTOP)

Insights

I have conducted an in-depth analysis of the HR Analytics Dashboard to identify patterns related to employee attrition. Here are the key insights derived from the data:

1. Marital Status:

Finding: Approximately 50% of employees who resigned were single.

Recommendation: Consider exploring initiatives or benefits that may be more attractive to single employees to enhance their job satisfaction and retention.

2. Gender:

Finding: Male employees are resigning at a higher rate.

Recommendation: Investigate the factors contributing to higher attrition among male employees and tailor retention strategies accordingly. It might include targeted engagement programs or addressing specific concerns.

3. Department:

Finding: The Laboratory Technician's department has the highest resignation rate.

Recommendation: Evaluate the work environment, workload, or other factors unique to the Laboratory Technician's department to identify potential issues and implement targeted improvements to enhance employee satisfaction and retention.

4. Salary:

Finding: Employees with a salary of up to 5000 are resigning the most.

Recommendation: Consider a compensation analysis to ensure that salaries are competitive in the industry. Additionally, explore non-monetary benefits or incentives that might contribute to employee retention.

5. Education Background:

Finding: Employees with a background in Life Sciences are leaving the company the most.

Recommendation: Examine if there are specific challenges or opportunities for improvement for employees with a Life Sciences background. Tailor training or support programs to address their needs and enhance overall job satisfaction.

6. Age Group:

Finding: The age group between 26 - 35 has the highest resignation rate.

Recommendation: Implement targeted retention strategies for this age group, such as career development opportunities, mentorship programs, or initiatives that address work-life balance concerns.

Conclusion

These insights provide a comprehensive understanding of the patterns within the organization and can serve as a foundation for implementing targeted strategies to improve employee retention and performance. The suggested recommendations aim to address specific areas of concern and create a more inclusive and supportive work environment.