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About the pay gap insight and how it’s calculated.
Related pages:
For a general overview on how People Analytics generates insights, see Insights 101
Overview
Are women paid less than men in your organization?
Figuring this out is not as easy as comparing average salaries. The Pay gap Insight answers a more nuanced question: are women underpaid — all else being equal?
The provided analysis answers the question from multiple perspectives.
Access the Pay Gap Insight analysis
The Pay Gap Insight report can be accessed in two ways:
From the Overview page, in the Insights tab
From the Stories page, within the Rewards chapter
Pay Gap analysis structure
The Pay Gap Insight allows you to examine pay discrepancies at different points of occurrence and at different levels of comparison.
The first row of tabs is for selecting one of three critical points where salary discrepancies occur:
Current Salaries
Initial Salaries
Salary increases
For each point of occurrence, you can examine the discrepancies through three different levels of comparison.
Levels of comparison
The Pay Gap analysis makes a comparison at two different levels:
Organization-wide disparity
This level will reveal any disparities in pay at the level of your whole organization, taking into account all of your currently active employees, after accounting for variables we know can influence pay levels (such as prolonged leaves, age, tenure, etc.).
Like-for-like disparity
This level of analysis reviews any pay disparity differences between more granular employee segments (e.g. teams, departments, divisions, locations, etc.) after accounting for variables that are known to influence pay (such as prolonged leaves, age, tenure, etc.).
Current Salaries pay comparison
The Current Salaries comparison shows the differences in the current salaries in ranges for both genders.
The bolded labels between ranges and darker dots represent the median values.
The red flag signals that the current pay gap is significantly explained by gender.
You can filter and group data by all employee segments available to your organization.
Grouping data by a certain employee segment will yield a breakdown chart that summarizes differences between male and female salaries, while indicating if the difference is statistically significant.
Initial Salaries comparison
The Initial Salaries comparison shows the differences in the initial salaries between the genders.
Salary Increases comparison
This tab shows three parameters:
Absolute salary increases
Relative salary increases
Number of months between salary increases
📖 NOTE: In the range charts, different line patterns carry specific meaning:
Striped line - “Due to a low number of observations, we haven’t tested the significance”
Grey line - “No significant difference was observed”
Colourful line with the red flag - e.g. “Female employees get significantly higher hikes ($500 - 10%) than male employees ($200 - 4%)”
Notes
This part of the Pay Gap analysis provides information about the analysis and helps you understand what our team did to find meaningful insights.
Playbook
This section contains the prescriptive part of the analysis. If your organization has a gender pay gap issue, the playbook will show a number of ways to address it.
Why is the Pay Gap Insight important?
In some cases, despite an apparent difference in pay, gender may be a minor factor that just happens to correlate with another, true underlying cause, such as differences in years of experience.
Yet in other cases, the wage gap might be attributable to gender — a situation that requires your attention. As explained in our blog post on equal compensation, unfair compensation policies end up costing an organization more in the long run.
How the gender pay gap is calculated
People Analytics estimates a salary equation in order to understand whether gender is a significant or incidental factor in wage discrepancies. Typically, it takes the following form:
Salary_i = Gender_i\beta_1
+ Characteristic_i\beta_2 + ...
+ Characteristic_i\beta_n + \epsilon
In this equation, gender is one of several traits that might contribute to an employee's salary. Other traits may include employees' age, tenure, and so on. The equation assigns a weight to each of these traits, a number that explains how much the trait contributes to employee salaries.
Our statistical algorithm is able to analyze a range of employee traits from your data set. The Pay Gap Insight is available to all clients on appropriate plans, regardless of whether the analysis reveals a significant contribution of gender to their pay differences or not.
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