Private reporting
How can I build salary and headcount reports without uploading employee records?
Design the report using sanitized employee sample data that matches your payroll export’s columns. Load the actual employee CSV only in the downloaded HTML template on your computer. This separates online layout design from local analysis of individual salaries and employee records.
Fictional data · worked example
A small payroll example you can reconcile
The fictional file has four unique employee IDs, annual salaries in one common currency, and two departments. These are arithmetic examples, not salary benchmarks or recommendations.
- Employees
- 4
- Annual salary total
- 300,000
- Average annual salary
- 75,000
Sample files are fictional and contain no customer or employee records. Open the sample HTML locally and load the matching CSV. Preview the salary benchmarking template.
Choose a clear reporting unit
For a simple headcount report, use one row per employee. In the example, salaries of 60,000, 80,000, 70,000, and 90,000 total 300,000; dividing by four gives an average of 75,000. Product and Finance each have two employees.
A payroll file may instead have several rows per employee for allowances, pay periods, or adjustments. Counting those rows would overstate headcount. Prepare the correct reporting dataset locally before loading it. Do not combine monthly and annual salary values or different currencies into one unqualified total.
Create the reusable employee report
The salary benchmarking template provides a starting point for salary comparisons. Adapt it to your reporting definition using sanitized sample data.
- Open the fictional employee CSV. Its headers match the salary benchmarking example, including employee_id, department, salary, and market_midpoint.
- Use this sanitized sample data in the online editor. Add a headcount KPI using your chosen definition, an average-salary KPI, and a department breakdown. Keep individual records out of high-level views when they are not needed.
- Download the template and load the fictional file locally. Confirm four employees, the salary total, and the average before moving to a real export.
- Prepare your actual employee CSV in your approved environment and load it in the downloaded HTML file. Reconcile headcount and salary totals with the source system.
Make sure the sample data is really sanitized
Invent employee IDs, roles, salary amounts, locations, and experience values. Removing names while preserving a unique combination of department, level, and salary can still expose an employee. Do not paste real payroll rows into the AI instructions or a support request.
The sample’s market midpoints and ratios are fictional too. Replace them with an authorised, consistently defined source for actual benchmarking. The template does not supply independently verified salary-market data.
Limit what recipients can learn
A department with one employee can reveal that person’s salary even in a summary chart. Review small groups and detailed tables before distributing a report. A filter is a viewing control, not a permission boundary.
Keep populated reports and source CSVs in approved storage. Share a reviewed empty template when recipients only need the layout. If they receive populated outputs, they may be able to read or copy the information those outputs contain.
Common questions
Does a salary chart prove equal pay or legal compliance?
No. A chart summarises the supplied data and definitions. It is not a legal conclusion, a certification, or a substitute for an appropriate review.
Will removing employee names make the report anonymous?
Not necessarily. Small groups and combinations of attributes can identify people. Review the full output and use the level of detail appropriate for its recipients.
Try the workflow with sanitized sample data
Online design and template downloads are subject to your plan. See pricing and editor access.
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