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HR Analytics: Predicting Employee Churn in R

Intermediate

Updated 12/2024

Predict employee turnover and design retention strategies.

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RMachine Learning4 hours14 videos50 exercises4,000 XP4,514Statement of Accomplishment

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Course Description

Organizational growth largely depends on staff retention. Losing employees frequently impacts the morale of the organization and hiring new employees is more expensive than retaining existing ones. Good news is that organizations can increase employee retention using data-driven intervention strategies. This course focuses on data acquisition from multiple HR sources, exploring and deriving new features, building and validating a logistic regression model, and finally, show how to calculate ROI for a potential retention strategy.

Prerequisites

HR Analytics: Exploring Employee Data in R

1

Introduction

What is turnover?

Objectives of employee turnover prediction

Importing headcount and turnover data

Exploring the data

What proportion of employees have left?

Which levels have high turnover rate?

Is turnover rate different across locations?

HR data architecture

Filtering the dataset

Combining HR datasets (I)

Combining HR datasets (II)

Master data overview

2

Feature Engineering

Feature engineering

Derive age difference

Derive job hop index

Derive employee tenure

Compensation

Exploring compensation

Deriving Compa-ratio

Deriving Compa-level

Information value

Calculating Information Value

Which variables are important?

3

Predicting Turnover

Data splitting

Split the data

Corroborate the splits

Introduction to logistic regression

Build your first logistic regression model

Build a multiple logistic regression model

Interpreting significance levels

Multicollinearity

Detecting multicollinearity

Dealing with multicollinearity

Building your final model

Building final logistic regression model

Understanding the model predictions

Interpret the results

4

Model Validation, HR Interventions, and ROI

Validating logistic regression results

Create a confusion matrix

Accuracy of your model

Designing retention strategy

Calculate turnover risk probability

Creating turnover risk buckets

What would you do?

Return on investment

Create salary hike range

Calculate turnover rate across salary hike range

Calculate ROI

HR Analytics: Predicting Employee Churn in R

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