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Data flagging

Updated over 3 weeks ago

Figures uses data flagging to ensure the data quality of our benchmarks. When an employee has been flagged by either you, someone from our customer success team, or even automatically, their data is removed from the benchmarks until it can be reviewed by you or your team, from Account > Data Validation.

View from the People page:

What are flags?

Our flags are a system to isolate unusual data. They are attached to an employee’s data, and remove it from our benchmarks.

Categories

We have three different categories for flags:

  • Unusual Compensation: anything wrong with the base salary or bonuses (compensation suspiciously high or low). For example, an employee paid 15€ as a yearly gross salary.

  • Unusual Job Title: if there appears to be a mismatch between your own job title from your HRIS and the Figures’ references. For example, a VP Marketing mapped to a Back-end Developer position inside Figures.

  • Unusual Level: if there appears to be a mismatch between your job title, or level, and the Figures’ references. For example, a CEO mapped as a ‘Junior’ inside Figures.

Where to report unusual data?

  1. Go to Account > Imported Employees

  2. Select the employee you want to work on

  3. Click on Report at the top right

Automated flagging

During your onboarding process with Figures, we are also automatically flagging employees with unusual compensation. We want to make sure you review this data before moving forward.

There are currently 4 reasons for us to flag employees:

  1. Employees with a yearly gross salary under 5.000€ (or equivalent for different currencies).

  2. Employees with a salary under the legal minimum wage for European countries.

  3. Employees without a director level (C-Level, Director, VP, …) with a yearly gross salary superior to 300.000€ (or equivalent for different currencies).

  4. Any employees with a yearly gross salary (excluding bonuses) superior to 2.000.000€.

How to fix flagged data?

To see which data has been flagged, go in Account > Data Validation.

Correct the data either in your HRIS or via spreadsheet.

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