Employee Attrition Analysis: Identifying Organizational and Managerial Drivers of Turnover

A data-driven analysis of human resources workforce data aimed at uncovering key factors behind employee attrition and providing actionable insights for HR policies.

Project Demo: The analysis has been converted to HTML and is hosted on GitHub Pages for easy viewing.

Data Source:
Human Resources Data Set – Kaggle

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Project Overview

This project examines historical employee data to understand attrition patterns and identify organizational and managerial drivers of turnover. The analysis focuses on:

• Understanding the main reasons employees leave the organization
• Identifying patterns in attrition based on:
  • Department
  • Manager
  • Performance score
  • Recruitment source

The goal is to provide evidence-based recommendations for HR policies that improve employee retention and reduce talent loss.

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Workflow

The project is structured into several stages:

1. Data Preparation

   • Importing the dataset into a Jupyter Notebook
   • Cleaning and preprocessing data to handle missing values and ensure consistency

2. Descriptive Analysis

   • Examining termination types (voluntary vs involuntary)
   • Department-level attrition analysis
   • Manager-level attrition patterns
   • Performance score trends
   • Recruitment source performance

3. Insights and Recommendations

   • Translating descriptive findings into actionable suggestions for HR sub-teams

4. Project Deployment

   • Notebook converted to HTML using nbconvert
   • Hosted on GitHub Pages for easy sharing