Value-based comparison
When pursuing pay equity, one of the most powerful insights is the “equal pay for work of similar or equal value”. Within PayAnalytics you can create and view this report in our Value-based comparison feature, available within the Report section of the navigation.
This feature enables you to conduct a pay equity analysis to ensure that employees are compensated fairly for work of equal value. Once you've completed and imported the results of a job evaluation, (to find out more about this topic, see Job evaluation), the Value-based comparison feature allows you to dive deeper into the data to reveal any inequities, verify compliance, and plan for adjustments if needed.
In this article we will guide you how to use and understand the Value-based comparison report, covering:
Understanding value-based comparison within pay equity analysis
The value-based comparison feature is designed to ensure equal pay for work of equal value. It gives insightful and actionable information when comparing work that is different in nature, but similar or same in value. It helps you analyze and compare compensation based on the actual value of work, rather than job titles or other surface-level characteristics. This is particularly useful when working with job roles that might differ in function but are of similar or equal value based on factors like skills, responsibility, and working conditions.
By focusing on job value rather than job title, this feature helps you identify pay disparities that could otherwise go unnoticed. Once disparities are detected, you can make data-informed recommendations to ensure equitable pay.
Prerequisites: importing job evaluation data
Before using the Value-based comparison feature, you’ll need to have conducted a thorough job evaluation process. This involves evaluating each job role across multiple factors (e.g. responsibilities, skills required, complexity) to assign a total "job value score" to each position or job. This score reflects the overall value of each job role to the organization.
Once the job evaluation is complete, you can either import the job score data as a column in your employee dataset into PayAnalytics or, highly recommended, implement the job evaluation within PayAnalytics directly to re-use the framework and job scores in the future (for more information about job evaluation process, see Job evaluation).
In case you opt to implement the job evaluation within PayAnalytics, you will need to assign it to the dataset for which you plan to run your value-based comparison analysis. Within the relevant employee dataset, navigate to Dataset Configuration and select the relevant Job Evaluation as illustrated in the following picture:
Job evaluation section
Three steps to implement your job evaluation
The step-by-step process for effectively using the job evaluation feature in PayAnalytics includes:
Conducting a value-based comparison analysis
Interpreting the value-based comparison results
Taking action on your findings
To start the process, from the navigation bar head over to Reports > Value-based Comparison > Select a dataset to get started with this feature.
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In case you forgot to assign a job evaluation to your dataset yet, you can head over to Dataset Configuration and select the relevant Job Evaluation. You will not be able to make updates to the configuration, including adding a job evaluation if you have already run a pay equity analysis on the dataset. In this case, we recommend creating a duplicate of the dataset and configuring the job evaluation in the new version.
Conducting a value-based comparison analysis
Value-based comparison provides a comparison of compensation based on the value of the work, highlighting the difference between different predominant demographic groups.
Value point mapping: You need to instruct PayAnalytics on how to establish the value of jobs, by mapping two key data fields:
Job Title/ Job Group, which provides a way for the system to identify and compare jobs
Job Value (points), which provides a way for the system to compare job value
In case you are using the job evaluation feature within PayAnalytics, these two fields would be automatically populated from the dataset configuration.
Using preset configurations: We provide several presets matching legal requirements in different countries including Sweden, Norway and Canada, and specific regions across Canada, as shown in the following picture:
Preset configurations for value-based comparison
Regardless of whether your country is displayed in the list of presets, you can use the value-based comparison feature, if you want to analyze equal pay for work of similar or equal value.
Other settings: When you select a preset, the following settings will be automatically pre-populated. Otherwise, you will find the system's default settings (click here for more information on System parameters), and can make a decision that matches your organization's requirements for:
Aggregate, which describes the statistical way the data would be aggregated in the report. Either average or median, with the default setting of median.
Threshold, which is the percentage that defines the proportion of employees a demographic group should contain to be considered the predominant demographic. On a scale of 0 to 100 percent (%), with the default setting of 60%.
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Sections to display, which include various methods of displaying the comparison of equal pay for work of equal value. You can select as many as are relevant from:
Group overview (default setting)
Within group (optional)
Comparison (optional)
Distribution overview (optional)
You can learn more about the visualizations and how to interpret the results in each of the section displays next.
Interpreting the value-based comparison results
After configuring your settings for value-based comparison, you’ll find detailed report sections and visualizations that highlight pay comparison across your selected job groups within the organization, including:
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Group overview (default setting) visualizes for each job title/ job group, the median/ average compensation and the predominant demographic - based on the threshold in the configuration (e.g. female, male or no predominance).
Structural lower positioning of certain demographic predominant (e.g. female) jobs compared to neutral or other demographic predominant (e.g. male) jobs at a similar value point level can be an indicator of pay inequalities. In this case, we recommend, that remediation action should be explored through our raise suggestion model, for more information, see Getting suggested remediation actions.
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Within group (optional) visualizes for each job title/ job group, the median/ average compensation of the job group for each of the demographic groups from the dataset configuration (e.g. female, male).
Larger gaps between the demographic groups (e.g. male and female) compensation within the same role, can be indicators of pay inequalities. In this case, we recommend further investigation into explanatory compensation drivers (e.g. demographic imbalance in job levels or tenure). To visit the article that will explain this further, see Understanding & analyzing the compensation model. If compensation drivers do not (fully) explain pay gaps between demographics, remediation action should be explored through our raise suggestion model, visit the Getting suggested remediation actions article to find out more about this topic.
The result of a exemplary analysis is shown in the following picture :
Exemplary analysis result
Comparison (optional) only applicable for job title/ job groups with a predominance (e.g. male or female predominant). Visualizes the median/ average compensation of the job group's predominant demographic (e.g. male) compared to the median/ average compensation of the job groups non-predominant demographic (e.g. female).
Distribution overview (optional), displays the number of employees for each combination of job group and the job groups total value points, where the colors indicate the gender predominance of the groups, as shown in the following illustration:
Distribution overview view
Taking action on your findings
At the top of the Value-based comparison, you have the option to export the full report into Words and PDF format, as illustrated in the following picture:
Exporting the Value -based comparison