Overview

In a bustling corporate environment, the HR manager finds themselves faced with a complicated challenge: a notable surge in employee attrition rates within the organization. As a key stakeholder responsible for nurturing a conducive work culture and ensuring talent retention, the HR manager is keen to find out the underlying reasons driving this trend. With a collection of data at his disposal, ranging from demographic details like age, gender, and marital status to employment specifics such as job roles, tenure, and performance ratings, the HR manager wants to know important insights.

As an HR Analyst, I have been assigned to find out the information using the given dataset and present findings using Microsoft Excel to the stakeholders in order to help them understand important insights and improve their decision making.

Problem Statement

Q.1.) Total number of employees working in the organization, out of which how many of them left and how many are actively working?

Q.2.) Out of those employees who left the organization, how many of them lived near-by, far and very-far from the office location?

Q.3.) Out of those employees who left, what was the top 3 highest number recorded when it comes to job roles they worked in?

Q.4.) Which age group did the ex-employees belong to along with their gender and what was their highest age group out of 5 groups?

Q.5.) What was the percentage of female attrition as compared to male attrition?

Important Insights:

1. ) There is a record total of 2,925 employees out of which 2,433 are actively working and 492 of them left.
2. ) 296 employees lived near-by, 102 far and 94 very-far based on distance in kilometers from the office location.
3. ) When it comes to job roles the employees belonged to, the highest number was recorded from the laboratory technician department (130), followed by Sales Executive role (113) and Research Scientist (99)
4. ) Those employees who belonged to the age group of 26 - 35 had the highest number of 242 where 146 were male and 96 were female
5. ) 63% of the employees who left belonged to the male category whereas the remaining 37% belonged to the female category.

Power Query Window:

Raw Data:

Final Dashboard: