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Regional Paper Company Employee Lifecycle Data
Data Science and Analytics
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About
Employee churn metrics for the Dunder Mifflin Paper Company branch in Scranton, Pennsylvania, offer a detailed look into the factors that drive staff turnover within a professional setting. By examining variables such as tenure, salary, and self-reported satisfaction, organisations can identify why individuals might choose to leave. This predictive resource allows for the classification of staff into different risk categories based on their likelihood of departure, enabling management to take proactive steps to improve retention and workplace morale. The material provides a relatable context for unravelling the complexities of employee satisfaction and work-life balance within a regional office environment.
Columns
- EmployeeID: A unique numerical identifier assigned to each individual member of staff.
- Branch: The geographic location of the employee, representing one of the 12 regional sites across the United States.
- Tenure: The total number of years an employee has served within the organisation.
- Salary: The annual gross pay of the employee, ranging from £40,000 to £98,000.
- Department: The specific business unit where the individual works, such as Sales, Accounting, or Customer Service.
- JobSatisfaction: A self-reported score on a scale of 1 to 5, where 5 indicates the highest level of contentment with the role.
- WorkLifeBalance: A rating from 1 to 5 reflecting the employee's perception of their balance between personal life and professional duties.
- CommuteDistance: A categorical description of the distance travelled to the office, such as Short, Medium, or Long.
- MaritalStatus: The legal marital status of the staff member, including categories for Single, Married, and Divorced.
- Education: The highest academic qualification achieved by the employee, such as High School, Bachelor's, or Master's degrees.
Distribution
The data is delivered in a CSV file named
office_churn_dataset.csv, with a file size of 209.54 kB. It contains 1,543 records across 10 detailed columns. Data integrity is high, with core identifiers and categorical fields showing 99% to 100% validity. The resource is scheduled for weekly updates to ensure the information remains current for analytical purposes.Usage
This resource is ideal for developing machine learning models aimed at predicting staff turnover. It can be used to classify employees into risk groups—Class A (Highly likely to leave), Class B (Moderately likely to leave), and Class C (Slightly likely to leave). Analysts can employ the data for exploratory analysis to find correlations between commute distance, salary, and satisfaction levels. It also serves as an excellent educational tool for students practicing data cleaning and categorical data handling.
Coverage
The geographic scope is limited to the United States, specifically focusing on 12 regional branches including locations like Scranton, Los Angeles, and New York. Demographic coverage includes a diverse workforce with varying education levels, dominated by Bachelor's degree holders, and a mix of marital statuses. The records span a wide range of tenures, with some employees having been with the company for up to 27 years.
License
CC0: Public Domain
Who Can Use It
Human resources analysts can use this data to build internal retention frameworks and identify departments at risk of high turnover. Data science students and educators can utilise the records to teach classification algorithms and predictive modelling. Business managers can also gain insights into how work-life balance and environmental satisfaction impact the overall health of an organisation.
Dataset Name Suggestions
- Dunder Mifflin Employee Retention and Churn Metrics
- Office Workforce Satisfaction and Turnover Analysis
- Regional Paper Company Employee Lifecycle Data
Attributes
Original Data Source:Regional Paper Company Employee Lifecycle Data
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