Employees attrition analysis in Power BI
- Performed
Data Cleaningwith the help of Power Query Editor. - Analysed HR data and found various insights to asssess the attrition and the possible causes behind it.
- Identified trends and patterns by making
Data Visualisationwith the help of donut & pie charts, line charts and bar & column charts.
- Out of 1470 total employees, 237 have left the company till yet and this accounts to about 16% attrition rate.
- The average age of people working in our company is
37 yearsand their average salary is approximately6,500. - Employee Retention rate at company is around
7 yearson average.
- People from education background of
Life Sciencesare most probable to leave (around 38% ). - Employees of age group 26-35 are most likely to leave the company.
- Amongst the people who have left, there are
150 malesand 66% of the employeestravel rarely - Employees having salary upto 5000 are the ones who left the most and their number is 163.
- After completing
1 yearat company, 59 people have left. This attrition number decreases as the years at company increases but it sees a spike as the years at company reaches5 and 10 years. - From 237 people who left, around 112 have rated less than or equal to 2 in Job Satisfaction survey rating.
- 200 People collectively from job roles of
Laboratory Technician, Sales Executive, Research Scientist and Sales Representativehave left.
Males from Life Sciences background & of age group of 26-35 having salary less than 5000 are most likely to leave after completing 1 year at company.
- Salary could be increased and travel plans could be made to engage employees with work & give them job satisfaction.
- Hiring from Life Sciences should be done with more deliberation.
- There should be less pressure on Sales team as these job roles are most affected.
- Identified key factors to reduce attrition
- Improved the hiring process
- Improved Employee experience
- Made workforce more productive
- Gained Employee trust
