Overview
The Compensation employee lifecycle category displays adjusted pay gaps of employees by demographics data over time. Please see our reports overview to understand how our reports are structured.
Understand Compensation reports
Compensation reports use Dandi's proprietary machine learning model to cluster your employee compensation data based on a number of attributes, including job level, job title, department, location, and tenure. It then simultaneously processes multiple algorithms before choosing the one that delivers the highest statistical significance in normalizing, calculating, and predicting both compensation and the gaps therein based on diversity attribute(s).
The dashed line is the Equity Index, which is the expected mean value calculated by Dandi's machine learning algorithms. The Confidence Score is the statistical measure of how well Dandi's proprietary machine learning model approximates the true adjusted pay gap.
The adjusted pay gap is displayed as a percentage value as of the most recent data pull, either above or below the Equity Index. The report also surfaces is pay gap for the previous three months as an area graph in the background, based on historical data availability.
By default, compensation is measured on an annual basis and includes the total salary as provided by your HR system.
Within Dandi Explore, the table below the graph surfaces the following for each segment:
- Pay gap percentage
- Compensation value
- Employee count
Clicking on the pay gap percentage or compensation value will filter by that segment, and clicking on the employee count number will display the appropriate employee list for that segment.
All reports provide a historical snapshot of the specified workforce segment as of the date indicated. You can track how the adjusted pay gap is changing over time, and focus your efforts on areas that need it most.