Repair Work Orders and Direct Costs Dataset
Reconcile work-order billing with labor and parts costs, while separating unfinished work.
A practical workbook exercise for service managers and finance analysts. Work from the underlying records, compare the relevant totals and explain how you reached your result.
About the dataset
This original synthetic dataset contains 1,080 source records across three related tables. The records are fictional and designed for descriptive business analysis.
Dataset details
| Industry | Repair and field services |
| Formats | Excel workbook and CSV files |
| Source records | 1,080 |
| 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
- Jobs: 180 records and 6 fields. One service work order.
- Labor: 540 records and 4 fields. One recorded labor entry on a job.
- Parts: 360 records and 5 fields. One consumed parts line.
Recommended analysis
- Which completed jobs have negative direct contribution?
- How much cost is recorded against unfinished work?
- Do job types differ in labor and parts mix?
- What error appears if labor rows are joined directly to parts rows?
How to work with the data
Use the following relationships to connect the source tables:
- Labor.job_id → Jobs.job_id
- Parts.job_id → Jobs.job_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
- Calculate job labor and parts subtotals before joining them. A direct many-to-many join duplicates both costs.
- Completed-job contribution excludes overhead, tax splits and warranty provisions. Unfinished jobs are not zero-revenue completed losses.
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.