Leveraging-Feature-Engineering-in-Employee-Promotion-Process-using-SAS-Studio

Assignment for Data Management

Introduction

Employee promotion is a significant milestone that signifies an organization’s trust and recognition of an employee’s abilities and achievements, providing them with the opportunity to advance to higher positions. Effective promotion processes are crucial for an organization’s progress and prosperity, as they acknowledge employees’ efforts and commitment, enabling them to assume leadership roles and contribute to shaping the company’s culture and future.

However, the process of deciding on employee promotions is complex. It involves a combination of subjective and objective factors. Objective factors include measurable metrics such as job performance, tenure, education, training records, and previous promotions. Subjective factors, such as leadership skills and team collaboration, are more challenging to quantify. To enhance the accuracy of predictions and capture both objective and subjective factors, this study aims to develop a feature engineering technique using the employee evaluation promotion dataset.

Aims and Objectives

1. To develop feature engineering techniques for the employee evaluation promotion dataset.
2. To determine the key factors which significantly impact employee promotion.
3. To investigate the correlation of between input features and employee promotions using statistical tests.

Methodology

Dataset: Kaggle

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