data-analysis-with-excel

Employee Turnover Analysis using Data Analysis in Excel:

This project analyzes employee data using Excel to identify key factors contributing to turnover. By leveraging statistical analysis, pivot tables, and data visualization techniques, it provides actionable insights in order to reduce attrition and improve employee retention strategies. Dataset size : 554KB Rows: 15000 columns: 10

Employee Turnover Analysis Report

1. Introduction

Employee Turnover is a key HR metric that measures the number or percentage of employees who leave an organization over a specific period—typically a year. This analysis helps companies understand why employees leave and what actions can be taken to reduce unnecessary attrition.

2. Objective

The main objectives of this analysis are:

• To identify the key factors influencing employee attrition.

• To assist in workforce planning by forecasting potential turnover.

• To provide actionable insights for improving employee satisfaction and retention.

3. Data Overview

The dataset consists of the following variables:

satisfaction_level: Employee satisfaction level (range: 0 to 1)

last_evaluationTime: Time (in years) since the last performance evaluation

number_project: Number of projects completed by the employee

average_montly_hours: Average number of hours worked per month

time_spend_company: Number of years spent in the company

Work_accident: Whether the employee had a workplace accident (0 = No, 1 = Yes)

left: Whether the employee left the company (0 = No, 1 = Yes)

promotion_last_5years: Whether the employee was promoted in the last five years

sales: Department the employee worked in

salary: Salary level (categorical: low, medium, high)

4. Data Cleaning Process

1. Missing Value Handling

2. Duplicate Records

3. Correcting Column Names

4. Standardizing Categorical Variables

5. Data Type Conversion

5. Pivot Table Analyses

• Departmentwise Turnover

  Purpose: Identify which departments have the highest attrition.

  Insight: Useful for directing retention strategies to specific departments.

• Turnover by Workload

  Purpose: Understand if overworking or underworking correlates with turnover.

• Turnover by Work Accident

  Purpose: Assess if safety or well-being affects retention.

• Salary vs Turnover

  Purpose: Explore whether employees with low salaries are more likely to leave.

• Promotion vs Turnover

  Purpose: Check whether lack of promotion is a reason for leaving.

• Satisfaction Level vs Turnover

  Purpose: Directly tie employee satisfaction scores to attrition likelihood.

6. Key Takeaways

• High Turnover in Certain Departments: Indicates possible management or culture issues.

• Low Salary & No Promotion: Strongly correlated with higher turnover.

• Workload Balance: Both underutilization and overwork can lead to dissatisfaction.

• Satisfaction Level: A critical predictor of employee retention.

7. Conclusion

By leveraging this data-driven approach, the organization can:

Minimize voluntary exits, Improve employee experience, And build a more stable and efficient workforce.