Employee-Attrition-and-Performance-Analysis

Employee Attrition and Performance Analysis uses Power BI, SQL, Excel and Tableau to gain insights into the factors influencing employee attrition and performance within the organization by performing data analysis on the HR dataset.

Table of Contents

• Project Overview
• Problem Statement
• Data Source
• Data Cleaning/Preparation
• Live Dashboard
• Inferences
• Recommendations
• Limitations

Project Overview

1. The objective of this project is to gain insights into the factors influencing employee attrition and performance within the organization by performing data analysis on the HR dataset.
2. To identify the patterns, trends and potential areas for improvement that can help the company better understand and manage employee attrition and performance.
3. Tools used in this project are Excel, SQL , Power BI and Tableau.

Problem Statement

1. The high rate of employee attrition can have significant implications for organizations, leading to increased recruitment and training costs, reduced productivity, and decreased employee morale.
2. It is crucial for companies to understand the underlying factors contributing to attrition and take proactive measures to address them.

Data Source

• Domain: HR Analytics
• Dataset Name: HR_1 & HR_2
• Dataset Type: Excel Data
• Dataset Size: 50,000 records each

Data Cleaning/Preparation

• Checked for presence of duplicates and eliminated them.
• Removing irrelevant columns.
• Data type standardization.
• Formatting dates for consistency.
• Formatted numerical data for consistency.

Live Dashboard:

Power BI: https://app.powerbi.com/groups/me/reports/7cb11d2e-8f5b-4900-a38f-e3eb0d2a472b/ReportSection5e54a9e4f1ad1c6f2dbe?experience=power-bi

Tableau: https://public.tableau.com/app/profile/rohanyg/viz/EmployeeAttritionandPerformanceAnalysis/attritionratebydepartment?publish=yes Dashboard using Power BI:

Dashboard using Tableau:

Dashboard using Excel:

Inferences

inferences from the analysis:

1. The employee attrition rate of this organization is 50.21%. According to experts in the field of Human Resources, attrition rate less than 10% is considered as low and healthy in organization. So we can say the attrition rate of the organization is at a dangerous level.Therefore the organization should take measures to reduce the attrition rate.
2. Employees count in all department is almost same. Most of the employees are from Sales Department that is 16.97%, then HR 16.96 %. Attrition Rate is also high in the Sales Department and HR Department.
3. The organization is doing well by spliting travelling among the employees to reduce the burden of employees who travel frequently.
4. Attrition Rate is more and almost same in the age 20 to 50 . It goes decreasing when age is goes greater than 50.
5. Attrition Rate in male and female is almost same.In males attrition rate is 50.27% and in female 49.73%. The male employees in the organization accounts 50.12% and female accounts 49.88%.
6. Most employees is working as Sales executive, Healthcare Represenatative or an Manager in this organization. Highest attrition rates are in sector of Research Scientist, healthcare Representative and Sales Executive.
7. Most of the employees are from Medical Education Field. The distribution of employees from other education field is almost similar that is around 16%. Attrition Rate is high in medical field that is 17.01% and life sciences that is 16.95% of total.Least employees are from Marketing Education Field and attrition rate is low .
8. Total Working Years, DailyRate, Hourly Rate, and Monthlty Rate do not exhibit any correlation with Attrition Rate.
9. Employee who has worked for 2 to 4 years in the same role are having very high attrition rate. Employee who has worked for 10+ years in the same role are having low attrition. Employees gaining 2 to 4 years experience are leaving the organisation. May be they are finding better opportunity somewhere else.
10. Most of the employees have rated their job satisfaction same for all level. Employees who rated their job satisfaction low are mostly leaving the organization.
11. we can't generate any meaningful inisghts from percentage salary hike,performance rating and relationship rating with attrition rate
12. Attrition rate is high at the Entry Level for 1 and 2 level compared to other levels. As the level increases the attrition rate decreases.
13. The Distance From Home doesn't follows any trend in attrition rate.
14. The attrition rate is same around all relationship status but its slightly higher in case of single and divorced.
15. Attrition Rate is around 25 % for 1 year since last promotion. Almost 49% of employee has not been promoted about 1 to 4 years. attrition rate is also around 49% in case of 1 to 4 years.
16. Almost 56.63% of employees has worked for 1-5 years with the same manager. Employees has worked for 1-5 years with the same manager is having high attrition rate.

Recommendations:

1. Enhanced Benefits and Compensation Packages: Offering competitive salary packages, bonuses and benefits to retain employees.
2. Improve Job Satisfaction: Address concerns related to workload, workplace culture, and management. Conducting regular employee satisfaction surveys to identify the area of improvements.
3. Recognition and Appreciation: appreciate the employee efforts and recognize the employees achievement and milestones.
4. Promote Work-Life Balance: Encourage employees to take their allocated vacation days and work life balance is crucial for the long term employee retention.
5. Exit Interviews; To learn why an employee is leaving. Gain feedback on employee experiences and understand how company can improve.
6. Professional Development Opportunities: training programs and career development initiatives, empowering employees to upskill and progress in their careers within the organization.
7. Promote Diversity and Inclusion: Employees from various backgrounds feel respected and valued. Providing equal opportunities for all employees to grow within the organization.

Limitations

• The datasets might lack certain contextual information about the employees, such as personal challenges, external factors affecting their work, or specific project details. This missing context could limit the depth of your analysis. -The analysis might not cover all relevant factors contributing to attrition, such as organizational culture, leadership styles, or macroeconomic factors. A more comprehensive analysis would require a broader scope.
• The analysis appears to focus on descriptive statistics and visualization. While these provide insights into historical data, incorporating predictive models could enhance the project by forecasting future attrition trends.
• Implementing A/B testing methodologies could provide a more scientific approach to understanding the impact of specific interventions or policies on employee attrition.
• Machine learning algorithms, like classification or clustering, could offer deeper insights. Not utilizing advanced ML techniques might limit the depth of your analysis.