Employee Attrition Analytics
8 September, 2020
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RStudio
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Problem:
HR department managers of IBM company want to find out the hidden factors that may lead to employee attrition. The results can also be used as a reference for other companies to decrease employee attrition rates.Solutions:
HR Analytics helps human resources to interpret data, find out the trends and
help take required steps to keep the organization running smoothly and profitably. It has helped human resources to be more active and gain involved role in an
organization's planning and objectives. This poster uses the IBM dataset to study the underlying factors for employee attrition and interpret it through visualizations.
The IBM dataset is very clean which contains 31 columns and 1470 rows. Some information can be extracted by analyzing the relationship between some important features with attrition. For example, the “jobe level”, “over time”, “monthly income” , “number of the company worked”, etc.
The main reason behind attrition is most likely the effort-reward imbalance. This mostly applies to people who are working overtime and who in many cases have a relatively low salary - it should be checked whether there is an effective overtime policy in the company. In addition, the lower the job level, the higher probability for employees to leave. The turnover rate of employees below 35 years old is higher than those over 35 years old. If an employee has been working for more company, the turnover rate of him/ her will be high.