Human Resource - Analytics - Tools - Prediction

Here, you will find how HR can use Analytics and understand the employees' behavior pattern.

I have performed detailed step by step analysis for Employee data that can help HR understand how the trend of employees leaving is . Diagnose the reasons - salary of employees who left , department from where the most employees left and more .

Further based on this analysis , I have created a predictive model that will help in estimating when an employee is most likely to leave.

Before diving into the code, you may read here to understand the basic terms being used throughout.

In the past, most of the focus on the ‘rates’ such as attrition rate and retention rates. HR Managers compute the previous rates try to predict the future rates using data warehousing tools. These rates present the aggregate impact of churn, but this is the half picture. Another approach can be the focus on individual records in addition to aggregate.

HR Analytics

Often the data is in vast amount and handling it becomes a laborious task. But all of it can be managed simply by using Machine Learning. It will not only make the tasks easier for the HR and also allow them to focus on other areas as well.

HR Analytics is all about understanding people and trends related to them.

Employee Churn Prediction

Churn - When an employee is likely to leave. This is an important part as the leaving of an employee affects the company and its overall growth.

From the analysis and predictions what we understood is :

1. Employee with highest performance rating has greater satisfaction compare to those with lower rating .
2. Employees who left had lower salaries

Recommendations :

1. Ensure improved salary rate for employees
2. Create a friendly and comfortable office environment
3. Develop strategies according to changing trends