1. Welcome to the course!
Hi, my name is Abhishek and I am Anurag, we welcome you to our course on employee turnover prediction using R.
2. Understanding employee turnover
Employee turnover is all about an employee ending their formal relationship with an organization. In other words, turnover means gradual loss or exit of employees from an organization over a period of time.
Generally, in the industry, employee churn, employee turnover, and employee attrition are used interchangeably.
Let's understand the impact of employee turnover.
3. Why employee turnover matters?
Employees are arguably the most important asset of any organization and one of the most critical issues organizations are facing today is how to retain their employees. Nearly one-quarter of all U.S. workers quit their jobs every year, and in some industries, the turnover rate is considerably higher.
As per the research by SHRM (Society of Human Resource Management) replacing an employee can cost between 50-60% of that employee’s salary with overall costs ranging anywhere from 90% to 200%.
In this course, you will learn how to use employee data to understand which employees are most likely to leave and use that information to design interventions to retain them.
Before we get started, let's understand the types of employee turnover.
4. Types of employee turnover
Turnover is classified as voluntary and involuntary depending on the reasons for employee exit.
When an employee chooses to resign on their own, it is an act of voluntary turnover. Involuntary turnover is when an organization decides to let go of an employee due to contractual obligations, business restructuring or even due to disciplinary actions.
5. Common reasons for employee turnover
Common reasons as stated by employees are finding better opportunity elsewhere, health, relocation, education, and personal reasons.
6. Hidden reasons of employees turnover
However, the underlying reasons for leaving are usually not shared by employees, i.e., the actual drivers of turnover might be different.
In this course, we will help you discover hidden reasons that might affect turnover such as the relationship with the manager, recent salary hike received, extra hours worked, distance from home to office, satisfaction with career and number of years in the company etc.
7. Course overview
The course consists of four chapters.
In chapter 1, we will cover the basics of employee turnover, how to calculate the turnover rate, explore and visualize the relationship of turnover with gender, level etc. and you will also learn how to bring different data sources together.
In chapter 2, you will create new variables, also known as feature engineering and work on the concept of information value to identify important variables driving turnover.
Chapter 3 focuses on building a logistic regression to build employee turnover prediction model.
And in the last chapter, you will evaluate the accuracy of your model and classify employees in risk buckets. You will also calculate the ROI of interventions designed based on your recommendations.
8. Basic requirements for the course
This course heavily relies on the dplyr and ggplot2 packages for data manipulation and visualization.
9. Let's practice!
Now it's time to test your understanding of employee turnover prediction.