IBM HR Analytics Employee Attrition & Performance

I used a dataset from Kaggle to explore factors that lead to employee attrition.

The aim of visualizing the data was to;

• Identify departments with higher attrition rates to help address any underlying issues
• To analyze the distribution of employees across various age-groups
• To measure employee satisfaction levels
• Help HR department to understand the attrition patterns based on gender to help identify gender disparities and implement targeted attrition strategies.
• Analyze attrition based on education fields

Data Preparation

The data cleaning and transformation was done in Excel using advanced power query editor and Power Bi transform. Excel PowerBi

• Used Nested IF function

= $IFS([@Education]=1,"Below College",[@Education]=2,"College",[@Education]=3,"Bachelor",[@Education]=4,"Master",[@Education]=5,"Doctor")$

= $IFS([@EnvironmentSatisfaction]=1,"Low",[@EnvironmentSatisfaction]=2,"Medium",[@EnvironmentSatisfaction]=3,"High",[@EnvironmentSatisfaction]=4,"Very High")$

• Adding conditional columns
• Using Dax to add new measures

Findings

Data analysis and visualization revealed;

• Research and Development department had the highest attrition, followed by Sales and Human Resource respectively.
• 25-34 and 35-44 age groups had the highest number of employees who were leaving the company and most of them were men.
• Sales Executives had the highest level of satisfaction, followed by Research Scientists and laboratory technicians.
• In terms of education level, employees with a bachelor degree had the highest attrition rate.

Recommendations

• Investigate underlying reasons for high attrition in R&D
• Provide mentorship or leadership programs for younger employees.
• Implement initiatives to improve employee well-being and engagement.
• Recognize and reward high-performing employees.
• Implement flexible work arrangements to support work-life balance for all employees.
• Create a culture of open communication and feedback within the company.

Datasource https://www.kaggle.com/datasets/pavansubhasht/ibm-hr-analytics-attrition-dataset/data