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CWC's Comp Auditor® II Software
The CWC Comp Auditor® II is a software program developed by CWC for use by member companies in conducting self-audits of their employee compensation practices for potential pay discrimination. Comp Auditor® II builds upon previous versions of this powerful compensation analysis software by adding the following advanced features that were not available in previous versions:
A new statistical platform, tested by experienced compensation statisticians, that will make running analyses much easier and will enhance the power and flexibility of your analyses.
An enhanced data import function that can accommodate many common errors in the structure of data you import.
An analyzer that locates missing or zero values in fields critical to your analysis, permitting you to locate records that require correction and to make the necessary adjustments to your data.
The ability to create user defined fields, such as dummy variables and new calculated number fields that can be derived from imported data.
The ability to create special combinations of race and gender characteristics to conduct customized mean and regression analyses.
Enhanced displays, such as a dashboard view of your compensation project that allows you to see how you have defined your data fields and to make modifications as needed.
The ability to create, save and share your projects with other users and to reload them into Comp Auditor® II at any time to resume your work. This gives you the capability of working on more than one compensation project at the same time.
Significantly enhanced reporting and exporting features that display your data and analyses clearly, enable you to create PDF files and export data to Excel® and Access®.
A flexible feature for defining Similarly Situated Employee Groupings (SSEGs).
CWC’s Comp Auditor® II also retains many of the powerful features of the original versions, including:
The ability to import and analyze your data regardless of the structure of data your import or the size of your import table.
A comparison of "median" or "mean" compensation by race and gender.
t-Tests to measure the statistical significance of differences in pay.
Regression analyses to determine whether statistically significant pay differences can be explained by legitimate business reasons.
Cohort analyses that compare the pay of similarly-situated men and women, or minorities and non-minorities.