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Ensuring Figures data quality
Ensuring Figures data quality

Learn more about how we provide you with the most trustworthy salary data benchmark

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Written by Tech Support
Updated this week

Your data, as close to the source as possible with HRIS integrations

Figures uses HRIS integrations to collect real-time compensation data for its benchmarking. This integration ensures that the data is as close to the source as possible, allowing for more accurate and reliable benchmarking. Our data is synced with your HR tools every day. This also helps to ensure that the data is up-to-date and reflects the most recent compensation trends.

Overall, HRIS integration is a critical component of Figures' data collection process and helps to ensure that our clients can trust the accuracy and reliability of our benchmarking data.

We integrate with +35 HRIS, to learn more go here.

Automated data flagging

Once we collect your data from your HRIS, automatic checks for data quality are made. No automatic integration is perfect, and we want to make sure we catch any errors that might have gone through. Any data considered ‘unusual’ is flagged and quarantined until a human being can look at it and correct it. While quarantined, the data is not used in our benchmark.

Compensation threshold

Once we have collected compensation data, we quarantine any compensation outside of expected ranges:

  • We remove any compensation under the legal minimum wage of its country

  • We have a catch-all threshold of 5.000€ yearly

  • Non C-Level above 300.000€ base salary yearly

  • Any employee above 2.000.000€ base salary yearly

Once the data has been confirmed to be true or is corrected, it’s added back to the benchmark. We still love a good outlier from time to time.

To learn more about our data flagging system, go here.

Human touch

While automated flagging can catch unusual data, it’s not perfect. So our team of Customer Success Manager reviews our data one last time. Here’s some examples of what our CSMs are looking for:

  • Are the job titles in the solution matching your industry?

  • Do you only have junior or senior employees?

  • Are there all of the usual positions in a company (CEO, CFO, HR, …)?

Our goal is to ensure the data used in the solution has been vetoed and thoroughly checked, and you have the best onboarding experience to our solution. We do want you to have access as soon as possible to our benchmarking, but we need to make sure we don’t use just any data.

Manual reporting

At any point, if data seems suspicious to you or one of our CSM, it can be reported. As for the automated flagging, it will quarantine the data until it’s verified by both parties.

Data Quality indicator: What goes into the soup?

Not all data we collect is included in our benchmark. To ensure the highest accuracy and relevance, we exclude quarantined data and datasets with insufficient sample sizes. Our 'Data Quality Indicator' reflects our confidence in the reliability of the data for a given average or benchmark.

Data Quality indicator

Our Data Quality is graded on a scale of Fair, Strong, and Excellent.

  • Fair: Data sourced from at least 8 employees and 3 distinct companies.

  • Strong: Data sourced from fewer than 20 employees, or less than 5 distinct companies, or datasets showing considerable variety in salary.

  • Excellent: Data sourced from more than 20 employees and more than 5 distinct companies with salaries showing little variance.

Please note that any data that does not meet the criteria for the Fair grade is not used in our benchmarks.

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