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HR Employee Performance & Attrition Data
Data Science and Analytics
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About
This dataset provides valuable employee information over time, designed for company employee analytics. It serves as an excellent starting point for organisational studies and evidence-based decision-making, offering rich opportunities for exploration, predictive modelling, and gaining actionable insights into workforce dynamics and HR functions.
Columns
This dataset includes 10 feature columns, each providing key attributes of employees from a company:
- satisfaction_level: The employee's satisfaction score, typically on a 1-5 scale, reflecting their contentment with their job and the company.
- last_evaluation: The score received on an employee's most recent performance evaluation, also typically on a 1-5 scale.
- number_project: The total number of projects an employee has worked on.
- average_monthly_hours: The average number of hours an employee has worked per month.
- time_spend_company: The total number of years an employee has spent with the company.
- work_accident: An indicator (yes/no) of whether an employee has experienced a workplace accident.
- left: An indicator (yes/no) of whether an employee has left the company.
- promotion_last_5years: The number of promotions an employee has received within the last five years.
- Department: The specific department in which the employee works.
- Salary: The employee's annual salary, categorised typically as low, medium, or high.
Distribution
The dataset is provided as a CSV (comma separated values) file, named
HR_comma_sep.csv, with a file size of 551.79 KB. It contains 15,000 employee records and 10 distinct feature columns, offering a substantial sample size for analysis.Usage
This dataset is highly versatile and ideal for optimising key HR functions and various analytical applications:
- Attrition Analysis: Identify factors correlated with employee attrition, such as department, role, or salary. It can be used to segment high-risk employees and predict future attrition rates.
- Performance Management: Analyse the relationship between performance metrics, like evaluation ratings, and salary increments. This can inform recommendations for performance improvement programmes.
- Workforce Planning: Forecast future staffing needs by analysing historical hiring and turnover trends, aiding in the determination of optimal recruitment strategies.
- Compensation Analysis: Benchmark salaries against performance and experience to identify potential pay inequities and inform compensation policies.
- Diversity Monitoring: Assess diversity metrics, such as gender ratios across roles and departments, to identify underrepresented groups within the organisation.
- Succession Planning: Identify high-potential candidates and critical roles, predicting internal promotions or replacements in advance.
Coverage
The dataset contains longitudinal employee data from a single company. While the specific company name is not provided, the data focuses on various attributes of its employees over time. No explicit geographic or demographic scope beyond the general "employees" is detailed.
License
CC0: Public Domain
Who Can Use It
This dataset is valuable for a wide range of users, including:
- HR Professionals: For data-driven decision-making, policy formulation, and improving employee retention and satisfaction.
- Data Scientists and Analysts: For developing predictive models, uncovering hidden patterns, and generating actionable insights into workforce behaviour.
- Organisational Researchers: For academic studies on employee behaviour, performance, and organisational effectiveness.
- Business Leaders: To inform strategic workforce planning and understand factors affecting employee engagement and productivity.
Dataset Name Suggestions
- HR Employee Performance & Attrition Data
- Workforce Analytics Dataset
- Company Employee Dynamics
- HR Insights Employee Records
- Employee Life Cycle Data
Attributes
Original Data Source: HR Employee Performance & Attrition Data
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