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Compensation Analysis Services


Increased scrutiny by the Department of Labor's Office of Federal Contract Compliance Programs (OFCCP) has involved efforts to determine whether systemic discrimination exists in Federal Contractor pay practices with regard to females and minorities, as compared to males and non-minorities. OFCCP's compliance evaluations include a request for compensation information. Paragraph 11, of the Itemized Listing, requests that compensation data be submitted in a summary format. Contractors have a choice as to how this data is submitted. In addition, OFCCP has issued Voluntary Guidelines on conducting systemic compensation discrimination analyses for federal contractors in advance of compliance evaluations.

Because pay and other compensation can be analyzed in many ways, Gerstco offers a full spectrum of compensation analysis services to support federal contractors during OFCCP Compliance Evaluations or to assist with the implementation of Agency Voluntary Guidelines.

Desk Audit Submissions

Desk Audit Submissions

Prior to submitting any compensation data, Gerstco can assist federal contractors in determining the type of data to submit by conducting more than one analysis. Compensation information can be analyzed by location and pay grade, job, title, job group or other grouping. The types of analyses that can be provided to support the desk audit include:

Means Analysis

The Mean Statistical Significance Analysis compares the annual compensation of employees in a particular location. The mean (average) pay for females and minorities analyzed by Pay Grade or Job Title can be examined to determine by how many standard deviations they differ from the mean pay of males and non-minorities. Sample Means Analysis Report

Median Analysis

The Median (midpoint) Statistical Significance Analysis can also be used to compare the annual compensation of females and minorities to males and non-minorities in a particular location by Pay Grade or Job Title. Sample Median Analysis Report

Both the Mean and Median Analyses use the appropriate test for Statistical Significance depending on the situation and include the T-Test, Fisher Exact, Chi Square, or other formulae as required.

Compensation Flags Analysis

The Compensation Flags Report examines the annualized pay for females and minorities as compared to males and non-minorities by Pay Grade, Job Title, or Job Group. It compares the mean pay of females to males or minorities to non-minorities and computes the number of employees affected by differences in pay within a selected group. Sample Compensation Flags Analysis.

Pay Discrepancy by Job Title

This Pay Discrepancy by Job Title report examines each Job Title and displays those job titles where there are pay discrepancies between females and males or between minorities and non-minorities. Where there are differences in annual pay, the actual pay difference and the percentage differences are shown. The level of pay differences can be easily reviewed for each Job Title. High percentage pay differences may indicate the need to perform more detailed analyses. Sample Pay Discrepancy Report by Job Title

Pay Discrepancy Detail Report

The Pay Discrepancy Detail Report identifies job titles where the mean pay of females and minorities is less than that of males and minorities. The mean pay and employee counts for the job titles are shown as well as all of the employees in the job title sorted by pay. Employee details including name, race, gender, department and work location are included for reference. Sample Pay Discrepancy Detail Report

Annualized Rollup Compensation Report

The annualized rollup compensation report is a required part of the Desk Audit submittal (Paragraph 11, of the Itemized Listing attached to OFCCP evaluation scheduling letter). The compensation report may be presented by Pay Grade, Job Title or Job Group.

In-Depth Analyses

In-Depth Pay Analysis

When OFCCP's compensation analysis and focus goes beyond the Desk Audit submission, a more detailed salary analysis may be required, such as,

  • Responding to OFCCP questions regarding how pay is determined for specific positions;
  • Performing Cohort Analysis for discrete job titles and small groups of employees;
  • Analyzing employees by organizational units, departments, functions or locations;
  • Performing regression analysis;
  • Performing multiple regression analysis on additional factors which may influence pay.
Cohort Analysis

In cases where statistical analysis fails to account for all significant pay disparities or the when the employee population being analyzed does not lend itself to the use of complex statistical techniques to identify reasons for pay disparities, especially when the number of employees is small, or jobs involve individuals with unique or highly specialized skills, it may be necessary to review the affected employees on a one-to-one basis. The cohort analysis is an individualized look at compensation for similarly situated employees to determine if there are legitimate reasons for disparities in pay. In addition to looking at general factors which influence pay (time with the company, time in a particular job, department, or pay grade, performance ratings, relative experience level, educational attainment, etc), this analysis also considers how, when, and why pay decisions were made to determine if they were made on a consistent, fair and non-discriminatory basis.

In a cohort analysis, a comparison would be made of the experience of similarly situated employees involving elements of the compensation process such as setting starting pay, salary adjustments (annual increases, merit awards, bonus pay, etc.), salary trend lines, promotions, training and development opportunities, and any other factors or events in the company's compensation process. These comparisons may reveal that the pay disparity is a result of individual behavior rather than problems of systemic pay discrimination. Sample Cohort Analysis

Multiple Regression Analysis
Affirmative Action Plan information can also be analyzed company-wide, by AAP location, or other employee groupings under attorney-client privilege using multiple regression methodology. This type of analysis evaluates the degree to which selected employee attributes (i.e., performance, time in grade, time in position, company seniority, etc.) are correlated to pay and the extent to which race, gender, or ethnicity may be a factor in compensation. Appropriate reports and charts accompany delivery of this analysis to company personnel. Sample Multiple Regression Analysis