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Competition - HR Analytics in Tableau
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    Creating a Human Resources analytics dashboard using Tableau

    📖 Background

    Employee attrition is a critical concern for organizations across industries. High attrition rates can impact productivity, disrupt team dynamics, and increase recruitment and training costs. Understanding the factors that contribute to attrition is essential for organizations to develop effective retention strategies and create a positive work environment.

    In this project, we aim to analyze the relationship between attrition rates and various satisfaction factors, specifically focusing on work-life balance and job satisfaction. Work-life balance is crucial for employees to maintain a healthy integration of work and personal life, while job satisfaction reflects the contentment and fulfillment individuals derive from their roles.

    By exploring the connection between attrition rates and these satisfaction factors, we seek to gain insights into the drivers behind employee retention and turnover. Through data analysis and visualization, I aim to identify patterns, trends, and potential correlations that can guide organizations in implementing targeted initiatives to improve satisfaction, reduce attrition, and foster a more engaged and productive workforce.

    By examining a comprehensive dataset comprising employee demographics, performance ratings, and satisfaction metrics, I will uncover valuable insights into the relationship between attrition and key factors affecting employee satisfaction. This project aims to provide actionable findings and a deeper understanding of the dynamics that influence attrition rates in the organization.

    With the aid of Tableau,I will create interactive dashboards that consolidate and visualize the data, enabling stakeholders to explore the relationship between attrition rates, work-life balance, and job satisfaction. These dashboards will empower decision-makers to identify areas for improvement, develop targeted retention strategies, and enhance overall employee satisfaction and engagement.

    Through this project, I strive to contribute to the body of knowledge on employee attrition and provide meaningful insights that can drive positive change within the organization. By leveraging data analytics and visualization techniques, we aim to support evidence-based decision-making and foster a work environment that promotes employee well-being, job satisfaction, and long-term retention.

    💾 The data

    Your team created the following files:

    Employee (employee.csv)

    Column nameDescription
    Employee IDA unique ID that identifies an employee, connects to the Performance Rating table
    FirstNameFirst name of an employee
    LastNameLast name / surname of an employee
    GenderSelf-defined employee gender identity
    AgeCurrent age of an employee
    BusinessTravelFrequency of business travel
    DepartmentMost recent department that employee belongs/belonged to
    DistanceFromHome (KM)Kilometer distance between an employee’s home and their office
    StateState where the employee lives
    EthincitySelf-defined employee ethnicity
    EducationA unique ID that identifies an employees education level, connects to the Education Level table
    EducationFieldEmployee field of study
    JobRoleMost recent department that employee belongs/belonged to
    MaritalStatusCurrent/latest employee marital status
    SalaryMost recent record of employee salary
    StockOptionLevelThe banding level for stock options that the employee has
    OverTimeIndicates whether an employee is expected to work overtime in their role
    HireDateDate the employee joined the company
    AttritionIndicates whether an employee has left the organization
    YearsAtCompanyNumber of years since the employee joined the organization
    YearsInMostRecentRoleNumber of years the employee has been in their most recent role
    YearsSinceLastPromotionNumber of years since the employee last got promoted
    YearsWithCurrManagerNumber of years the employee has been with their current manager

    Performance Rating (performance_rating.csv)

    Column nameDescription
    PerformanceIDA unique id that identifies a performance review
    EmployeeIDA unique ID that identifies an employee, connects to the Employee table
    ReviewDateDate an employees' review took place
    EnvironmentSatisfactionRating for employees' satisfaction with their environment
    JobSatisfactionRating for employees' satisfaction with their job role
    RelationshipSatisfactionRating for employees' satisfaction with their relationships at work
    WorkLifeBalanceRating for employees' satisfaction with their relationships at work
    SelfRatingRating for employees' performance based on their own view
    ManagerRatingRating for employees' performance based on their manager’s view
    TrainingOpportunitiesWithinYearNumber of training opportunities offered in the last 12 months
    TrainingOpportunitiesTakenNumber of training opportunities taken

    Education Level (education_level.csv)

    Column nameDescription
    Education Level IDA unique id that identifies a education level
    Education LevelA unique ID that identifies an employee, connects to the Employee table

    The data files can be downloaded from the sidebar on the left (under Browse and upload files).

    🧾 Executive summary

    The objective of this project was to analyze employee attrition rates and investigate the relationship between attrition and various factors impacting employee satisfaction. Through data exploration and visualization using Tableau, we gained valuable insights into attrition patterns and their connection to key metrics.

    Firstly, our analysis revealed a high attrition rate among employees in the age group of 20-29, indicating a need for further investigation into the underlying causes. However, as the age increases, there is a steady decline in the attrition rate, suggesting that employees tend to become more committed and less likely to leave the organization as they gain experience and tenure.

    Furthermore, when comparing attrition rates with different year-based metrics, such as "Years in Company," we observed a consistent trend of attrition rates decreasing as the number of years increased. This finding highlights the importance of providing growth opportunities, career progression, and job stability to employees, as these factors contribute to higher retention rates and lower attrition.

    Moreover, our analysis focused on exploring the relationship between attrition rates and satisfaction metrics like "Work-life Balance" and "Job Satisfaction." We found that employees who reported dissatisfaction in these areas had higher attrition rates compared to those who were neutral or satisfied. This emphasizes the significance of creating a positive work environment, promoting work-life balance, and ensuring job satisfaction to improve employee retention and reduce attrition.

    It is crucial for organizations to develop targeted retention strategies, invest in employee development programs, and create a supportive work culture that promotes satisfaction and well-being. By prioritizing these aspects, organizations can enhance employee engagement, increase retention rates, and ultimately drive overall business success.

    In conclusion, this project serves as a foundation for evidence-based decision-making to address attrition challenges. By leveraging the insights derived from the analysis, organizations can proactively identify risk areas, implement targeted interventions, and create a work environment that fosters employee satisfaction and long-term retention.

    🌐 Link to your Tableau Public dashboard

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