Slidecast: Understanding the Compensation Self Audit

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Understanding the Compensation Self-Audit Presented by Stephanie R. Thomas, Ph.D. Thomas Econometrics [email protected]

description

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

Transcript of Slidecast: Understanding the Compensation Self Audit

Page 1: Slidecast: Understanding the Compensation Self Audit

Understanding the Compensation Self-Audit

Presented byStephanie R. Thomas, Ph.D.

Thomas [email protected]

Page 2: Slidecast: Understanding the Compensation Self Audit

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

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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

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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

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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

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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

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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

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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

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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

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Which Employees Should Be Grouped Together?

• Construction of “Similarly Situated Employee Groupings”

• Appropriate comparison groups are an essential prerequisite for a meaningful analysis

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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

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Similarly Situated Employee Groupings

• OFCCP also notes that other ‘pertinent factors’, such as department, functional division, geography, etc., should also be considered

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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”

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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

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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

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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

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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

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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.

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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

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Proxy Variables

• Caution should be exercised in the use of proxy variables, since they may not truly reflect what one is attempting to measure

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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

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Multiple Regression Analysis

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Multiple Regression Analysis

• Multiple regression analysis is the most commonly used framework

• It is generally accepted and is a widely used statistical technique

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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

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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.

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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.

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Multiple Regression Analysis

• SSEG #1 – Accounts Receivable ClerksSalary = $55,000

plus $ 1 (length of service)plus $3,000 (time in grade)plus $1,500 (CPA certification)

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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

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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

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Practical and Statistical Significance

• An estimated effect can fall into one of four categories:

P significant,S significant

Not P significant,S significant

P significant,Not S significant

Not P significant,Not S significant

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Practical and Statistical Significance

• SSEG #1 – Accounts Receivable ClerksSalary = $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

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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

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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

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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

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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

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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

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Understanding the Compensation Self-Audit

Presented byStephanie R. Thomas, Ph.D.

Thomas [email protected]