HR ANALYTICS WITH POWER BI

Project Goal: Analyze the HR data and determine attrition of the company for business decision-making .

Tools: MS Excel and Power BI

Data Source: MeriSKILL

Data Exploration: The original Excel spreadsheet of the HR data sets were duplicated to avoid lossing the data completely in case of error during analysis.I went through the datasets to get familiar with them. This enhance comprehension of the data, to ascertain the number of columns that require cleaning, deleting of redundant columns, renaming columns, dropping of duplicates and necessary columns needed to manipulate for the project goals.The table has 37 columns and 1471 rows

Data Preparation: Analyses were carried out on the duplicated of the original file.some cleaning and manipulation were done in Excel and the rest in power BI

Data Analysis: Different measures were made on using DAX in power Query.

1. Total Employee= COUNTROWS(’HR-Employee-Attrition’)

2. Male = CALCULATE([Total Employees],’HR-Employee-Attrition’[Gender]="male")

3. Female= CALCULATE([Total Employees],’HR-Employee-Attrition’[Gender]="Female")

4. % of Male = DIVIDE([Male],[Total Employees],0)

5.% of Female= DIVIDE([Female],[Total Employees],0)

6. Retention= SUM(’HR-Employee-Attrition’[EmployeeCount])-SUM(’HR-Employee-Attrition’[Attrition Count])

7. Attrition Rate= SUM(’HR-Employee-Attrition’[Attrition Count])/SUM(’HR-Employee-Attrition’[EmployeeCount])

Insights Drawn:

1.The analysis shows that there was a 16.12% attrition rate in the company

2.The singles contributed mostly to the attrition rate having a count of 120 of employees that left the company ,followed by the married of count 84 and the least was the divorced of count 33

3.The males contributed mostly to the attrition rate having 15 of employees that left when compared to the female of 87 employees .

4.In the education field ,the life science has the largest proportion of employees that left the company and least being human resources

5.There was 66% of the employees that travelled rarely and 5 % of them didn't travelled .

6.The research and development department comprises 133 employees that left the company which contributed to the highest proportion of the attrition rate.

7. ere was huge proportion of employees that left the company that worked overtime . Meaning ,over 800 current employees do not work overtime compared to the over 200 employees that do.

8.The education level 3 contributed to the attrition rate and the least being education level 5

9.ere is a strong positive correlation between the age of the employees and the hour rate worked by employees

10.There is a positive correlation between the level of education 1 and 3 and negative correlation between levels 3 and 5 with strong hour rate worked by employees

Recommendations

1. It is highly recommended that clear expectations are given to all new hires on their day-to-day responsibilities and job functions to avoid post - hire shock and eventually leaving the company

2. The singles should be highly motivated by offering support and showing appreciation to reduce the 16.12% attrition

3.The employees training with effective tools should be highly considered for their growth and developments

4.The high performing team members should be rewarded both with compensation and recognition by their leaders to avoid employees jumping ship when better opportunity comes their way.