Staffing Timesheets and Billing Dataset
Review approved hours, billing completion and direct contractor margin.
A practical workbook exercise for staffing finance and account managers. Work from the underlying records, compare the relevant totals and explain how you reached your result.
About the dataset
This original synthetic dataset contains 678 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Staffing and recruitment |
| Formats | Excel workbook and CSV files |
| Source records | 678 |
| Related tables | 3 |
| Fields across table schemas | 15 |
| Reporting cutoff | September 30, 2026 |
| Currency | USD for monetary fields |
| Source | Original synthetic data created for Jolene.pro Workbook Studies |
What's included
- Clients: 18 records and 4 fields. One staffing customer.
- Placements: 60 records and 5 fields. One placement with unchanged hourly USD rates.
- Timesheets: 600 records and 6 fields. One weekly timesheet.
Recommended analysis
- How much approved time remains unbilled?
- Which clients have the largest approval backlog?
- Which roles have the lowest direct margin per hour?
- Do any billed timesheets lack approval?
How to work with the data
Use the following relationships to connect the source tables:
- Placements.client_id → Clients.client_id
- Timesheets.placement_id → Placements.placement_id
Check the row grain before joining. Aggregate repeated child records to the required level before combining totals, so parent amounts are not counted more than once.
You can explore the workbook in Excel or Jolene.pro, or use the CSV files with SQL, Power BI and other analysis tools.
Definitions and assumptions
- Rates are USD per hour. No overtime premium, tax, benefits or employer overhead is modeled.
- Billed is a source flag; approval inconsistencies are intentional and should be reported, not silently corrected.
Use the field definitions and nullable-column guidance in the included data dictionary. Interpret blank values and reporting dates according to the scenario notes.
Downloads
The complete dataset ZIP includes the Excel workbook, three matching CSV files, a data dictionary, scenario notes, a source-row preview and license details.
Reuse and attribution
These are synthetic records, not customer data or industry benchmarks. Reuse is allowed under Creative Commons Attribution 4.0 International (CC BY 4.0). Credit Jolene.pro and identify any changes you make.