If a pay gap exists, you can flag the employees whose pay is below the expected range for review by a compensation expert. To answer this question, you want to build a model that will help you determine what “acceptable” variables influence pay, and check whether “unacceptable” terms (i.e., those representing potential causes of bias, like gender) may have a statistically significant effect in lowering an individual’s pay. The overall question is, “Is there a pay gap at your company? If so, who may need a correction to their compensation?” We hope this guide and workflow can be a starting point for your own analysis in your organization. If you’d like to follow along, download our workflow, attached at the bottom of this post. This post is your guide to conducting a pay equity analysis using Alteryx Designer - specifically, creating a linear regression model that helps you assess whether pay differences exist between people in different demographic groups. This article was written by B Hamel and originally appeared on the Alteryx Data Science Blog here: ĭata can sometimes reveal patterns that provide insights into complex issues, especially around diversity, equity and inclusion.
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