This slidecast provides an overview of the compensation self-audit process. We discuss why an organization would perform a self-audit, the self-audit framework, construction of similarly situated employee groupings, edge factors, data availability and collection, multiple regression analysis, practical and statistical significance, and follow-up investigations

1. Understanding the Compensation Self-Audit Presented by Stephanie R. Thomas, Ph.D. Thomas Econometrics sthomas@thomasecon.com

2. Overview Why conduct a compensation self-audit The self-audit framework Similarly situated employee groupings Edge factors Data measurability, availability and collection Multiple regression analysis Practical and statistical significance Follow-up investigations SEET MCG

3. Why Conduct aCompensation Self-Audit? Legal requirements (e.g., OFCCP) Settlement or verdict provisions Employment practices liability insurance requirements Component of employment litigation risk management program SEET MCG

4. Why Conduct aCompensation Self-Audit? Self-audit provides organization with the opportunity to: Identify which measurable characteristics drive compensation differences amongst comparable employees Uncover potential problem areas , and guide follow-up and corrective action SEET MCG

5. The Self-Audit Framework Legal counsel (corporate counsel and/or outside counsel) should be involved in the self-audit from the onset First step is to gain a thorough understanding of how and why employees are compensated SEET MCG

6. How are Employees Compensated? Understand the compensation structure across the entire organization Grade / step system? System with more discretion, such as minimum and maximum guidelines? Structure is likely to vary across business lines, sectors, etc. Annual salary for administrative staff Base plus bonus for sales team SEET MCG

7. How Are Employees Compensated? Examine compensation practices with respect to transparency and consistency Decisions should be based on a consistent set of well-articulated factors Benchmarks should be in place to ensure that no employee passes certain points in the pay range without satisfying certain skill, competency, and experience thresholds SEET MCG

8. How Are Employees Compensated? If this initial investigation reveals a lack of consistent, well-articulated factors, this must be addressed prior to launching a full-scale audit Efforts to develop a systemic process for compensation decision-making should be undertaken immediately SEET MCG

9. Why Are EmployeesCompensated At Different Rates? Two aspects to consider: Which employees should be grouped together for comparison purposes; What factors explain pay differences within each group of comparable employees SEET MCG

10. Which Employees Should Be Grouped Together? Construction of “Similarly Situated Employee Groupings” Appropriate comparison groups are an essential prerequisite for a meaningful analysis SEET MCG

11. Similarly Situated Employee Groupings No definitive ‘rules’ for constructing similarly situated employee groupings (SSEGs) OFCCP proposed the following definition of SSEG: Groupings of employees who perform similar work, and occupy positions with similar responsibility levels and involving similar skills and qualifications SEET MCG

12. Similarly Situated Employee Groupings OFCCP also notes that other ‘pertinent factors’, such as department, functional division, geography, etc., should also be considered SEET MCG

13. What Factors Explain Differences Within SSEGs? Identify factors used to determine compensation levels among similarly situated employees Typically, these factors include: Length of service Time in job or time in grade Relevant prior experience Education and certifications The factors that explain differences within SSEGs are collectively referred to as “edge factors” SEET MCG

14. Edge Factors Edge factors may differ throughout the organization: CPA certification may be an edge factor for employees working in accounting department CPA certification is likely not to be an edge factor for employees working in the sales department SEET MCG

15. Edge Factors The compensation model structures do not have to be identical across SSEGs Perfectly acceptable to have a different model for the sales department, for example, and the research and development department If different edge factors exist for different SSEGs, the model structures should reflect this SEET MCG

16. Data Measurability,Availability and Collection After identifying factors determining compensation, the question then becomes: whether these factors can be measured whether data for these factors readily exists within the organization SEET MCG

17. Data Measurability,Availability and Collection Some factors are easy to measure e.g., seniority, time in job, time in grade Some factors may be difficult to measure because of data limitations e.g., relevant prior experience may be only available from hard-copy resumes Some factors are difficult to quantify e.g., publications in “top tier” journals SEET MCG

18. Proxy Variables If an edge factor cannot be easily quantified, or if data collection would be prohibitive, a proxy variable is often substituted A good proxy variable is: One that is easily measurable Highly correlated with the edge factor for which it is being substituted. SEET MCG

19. Proxy Variables In some cases, a good proxy variable will be easy to identify In other cases, a proxy variable may be difficult to identify and/or may be less than perfect e.g., using age at hire as a proxy for prior experience SEET MCG

20. Proxy Variables Caution should be exercised in the use of proxy variables, since they may not truly reflect what one is attempting to measure SEET MCG

21. Data Measurability,Availability and Collection After data is collected and assembled, it should be reviewed for potential problems: Incomplete or missing data points Mixture of hourly rates and annual salaries “Full time equivalents” issues The data should be internally consistent within SSEGs SEET MCG

22. Multiple Regression Analysis

23. Multiple Regression Analysis Multiple regression analysis is the most commonly used framework It is generally accepted and is a widely used statistical technique SEET MCG

24. Multiple Regression Analysis Multiple regression analysis shows how one variable – in this case, compensation – is affected by changes in another variable In this context, it provides a dollar estimate of the “effect” of the edge factors on compensation SEET MCG

25. Multiple Regression Analysis Multiple regression analysis is one of the preferred techniques because: The calculations involved in estimating the effects are relatively easy to calculate; The interpretation of the “effects” are straightforward; The entire compensation structure can be expressed with one equation. SEET MCG

26. Multiple Regression Analysis Multiple regression analysis estimates these effects net of all of the other edge factors in the model It allows one to estimate how many more dollars of compensation an individual would be expected to receive if (s)he had one additional year of length of services, holding all other factors constant. SEET MCG

27. Multiple Regression Analysis SSEG #1 – Accounts Receivable Clerks Salary = $55,000 plus $ 1 (length of service) plus $3,000 (time in grade) plus $1,500 (CPA certification) SEET MCG

28. Multiple Regression Analysis With multiple regression analysis, the effects of each of the edge factors can be separated out A separate “effect” is estimated for each of the individual edge factors Can also measure “protected group effect” if gender / race / age variables are included in the model SEET MCG

29. Practical and Statistical Significance When reviewing results of multiple regression analysis, two issues should be kept in mind: Practical significance: the size of the estimated effect relative to (in this context) compensation – is the size of the disparity “big enough” to matter? Statistical significance: how likely the observed effect is the outcome of chance – generally accepted rule of thumb is 2 units of standard deviation SEET MCG

30. Practical and Statistical Significance An estimated effect can fall into one of four categories: SEET MCG P significant, S significant Not P significant, S significant Not P significant, Not S significant P significant, Not S significant

31. Practical and Statistical Significance SSEG #1 – Accounts Receivable Clerks Salary = $55,000 plus $ 1 (length of service) s.d. = 1.25 plus $3,000 (time in grade) s.d. = 4.62 plus $1,500 (CPA certification) s.d. = 2.27 SEET MCG

32. Follow-Up Investigations There are various methods of follow-up: Review of personnel files Review of performance ratings Discussions with managers and human resources personnel Follow-up may be conducted with legal department and/or outside counsel SEET MCG

33. Follow-Up Investigations The key point is that if potential problem areas are identified, action should be taken to further investigate those areas, and corrective action should be taken where appropriate SEET MCG

34. Cautionary Note For Corrective Action If corrective action includes compensation adjustments, it is highly recommended that these adjustments are fully discussed with counsel before implementation What may appear to be a minor change can have wide-sweeping implications for the compensation structure of the entire organization SEET MCG

35. Conclusions Compensation self-audits are performed for a variety of reasons, but the underlying questions addressed by these audits are the same: How are individuals compensated Why are individuals compensated at different rates SEET MCG

36. Conclusions The answers to how and why provide valuable insight into the organization, illuminating the policies and procedures – both formal and de facto – used in the compensation process The self-audit highlights any potential problem areas, guides follow-up investigations, and suggests possible solutions for potential problem areas SEET MCG

37. Understanding the Compensation Self-Audit Presented by Stephanie R. Thomas, Ph.D. Thomas Econometrics sthomas@thomasecon.com