Compensation 101 for Federal Contractors - Preparing for ... · 1 Compensation 101 for Federal Contractors - Preparing for OFCCP Changes in 2010 May 19, 2010 Please wait while others

1

Compensation 101 for Federal Contractors - Preparing for

OFCCP Changes in 2010

May 19, 2010

Please wait while others arrive, the presentation will begin momentarily.

Visit BCGi Online

• If you enjoy this webinar, D ’t f t t h k t th t i i – Don’t forget to check out our other training opportunities through the BCGi website.

– Join our online learning community by signing up (its free) and we will notify you of our upcoming free training events as well as other information of value to the HR other information of value to the HR community.

www.BCGinstitute.org

2

HRCI Credit

• BCG is an HRCI Preferred Provider

• CE Credits are available for attending this • CE Credits are available for attending this webinar

• Only those who remain with us for at least 80% of the webinar will be eligible to receive the HRCI training completion form for CE submission

• You will receive your HRCI certification documentation within 1 week by email

• COMPare v2.0 has been released!• A free version of this powerful software package is

available to members of BCGi!

NEWS FLASH!

• What is COMPare?– Designed specifically to help federal contractors comply

with compensation analysis requirements from the OFCCP.

– Uses multiple regression, t-tests and specialized processes to evaluate data assumptions, identify problem areas, create reports, and even calculate dollar amounts needed to eliminate statistically significant disparitiesneeded to eliminate statistically significant disparities.

• Become a member of the BCGi online learning community (membership is free) to make sure that you receive access to this great analytical tool!

3

About Our Sponsor: BCG

EEO Consulting since 1974

• Expert Witness in EEO discrimination cases

• Affirmative Action Plan software and services

• Compensation Analysis software and services

• Pre-Employment software and services

• Published: Adverse Impact and Test Validation, 2nd Ed.

55

• Published: Compensation Analysis: A Practitioner’s Guide to Identifying and Addressing Compensation Disparities, 1st Ed.

• Editor & Publisher: EEO Insight an industry e-Journal

www.Biddle.com

Compensation 101 for Federal Contractors - Preparing for

OFCCP Changes in 2010

May 19, 2010

4

Contact Information

• Presenters– Marife Ramos– EEO/AA Senior Consultant

• [email protected]

• 800-999-0438 x129

– Criselda Pontilla– EEO/AA Analyst• [email protected]

• 800-999-0438 x109

• Panelist– Jim Higgins – Director of Compensation

• [email protected]

• 800-999-0438 x 144

7

Agenda

OFCCP Updates, Hot Spots and Trends

Laws and Regulations

OFCCP and Compensation

Compensation Review in an OFCCP Audit

M lti l R i

8

Multiple Regression 101

Pitfalls and Data Issues

Recommendations

5

OFCCP Updates, Hot Spots and Trends

9

OFCCP Hot Spots

Recordkeeping

Adverse Impact in the Selection Process

ARRA AuditsARRA Audits

Rebuilding of Enforcement Capacity• Outreach to Veterans • Outreach to Individuals with Disabilities

10

6

OFCCP Hot Spots

Scheduling Process will be Overhauled• CSAL will continue to be used• April letters already went out

Recidivism Measures• Industry Based• Organization Based

Identify and resolve all discrimination cases• Systemic• Individual complaints

11

OFCCP Trends

Increase in Number of On Site AuditsAudits

Increase Scrutiny of Job Postings

Compliance Officers Doing the

12

Compliance Officers Doing the “Math” on Data

Request for Extension = Notice of Violation

7

Compensation: Laws and Regulations

13


Why Analyze Compensation?

Executive Order 11246Executive Order 11246• According to 41 CFR 60-2.17(b)(3), contractors must

evaluate their “compensation system(s) to determine whether there are gender-, race-, or ethnicity-based disparities.”

According to 41 CFR 60 20 5 the employer’s wage

14

• According to 41 CFR 60-20.5, the employer s wage schedules must not be related to or based on the sex of the employee.

8

Title VII of the 1964 Civil Rights Act


Title VII of the 1964 Civil Rights Act

• It shall be an unlawful employment practice for an employer to fail or refuse to hire or to discharge any individual, or otherwise to discriminate against any individual with respect to his compensation . . . because of such individual's race color religion sex or national

15

of such individual s race, color, religion, sex, or national origin.

Lilly Ledbetter Fair Pay Act of 2007A d Titl VII th ADEA ADA d th


• Amends Title VII, the ADEA, ADA, and the Rehabilitation Act of 1973 to clarify discriminatory compensation decisions/practices are unlawful and the discrimination occurs each time the compensation is paid.

• Recovery is limited (2 years from filing charge)

Paycheck Fairness Act (Pending)Paycheck Fairness Act (Pending)• Only applies to differences by Gender• Geared towards class action lawsuits• Allows recovery of compensatory and punitive

damages.16

9


17

June 16, 2006: The OFCCP released the final compensation analysis standards/guidelines.


Guidelines for Self Evaluation with Compensation Practices for Compliance with Non Discrimination Requirements (the “Guidelines”)

• Provides suggested techniques• Voluntary• Chose Multiple Regression as the analytical

18

• Chose Multiple Regression as the analytical benchmark• To effectively/properly use multiple regression

requires a significant understanding of the underlying statistics and associated assumptions.

…

10

Group by Pay Grade •The focus was

Compensation Analysis in the Past

Compare Average

Compensation Between Groups

Back Pay/Make

Whole Relief

on simple differences in average compensation.

19

T-Tests or “DuBray” Analysis

Cohort Analysis

T-Test (In a Nutshell)

Group 1(Avg. $)

Group 2(Avg. $) = Difference

Is the difference in the Average Salaries statistically significant?

How it works:• The difference is made up of purely random differences that are

20

p p ydue purely to chance AND POSSIBLY inappropriate differences that are due to gender or minority status.

• T-Tests essentially “filter out” the random differences so that, if any real differences between groups exist.

• If there are “real” differences between groups, the difference is said to be “statistically significant.”

11

T-Test (In a Nutshell)

T-test?

Pros• Highly sensitive• Easy to interpret• Works with small

samples

Cons• Too simplistic• Fails to take into

account that real differences may exist

21

samples• Can help pinpoint

areas in need of further investigation

yfor legitimate reasons

• Results in findings of pay disparities when none exist

Compensation Review in an OFCCP Audit

22

12

OFCCP Audit: Compensation

Initial Data Review

Request for Additional Data

Employ Multiple Regression Analysis to assess pay disparities

On-Site (to gather anecdotal evidence)

23

1. Initial Data Review:

• Type 1: OFCCP Red Flag Analyses


Type 1: OFCCP Red Flag Analyses

– GOAL: Identify signs of potential systemic compensation disparities.

– Unofficial (i.e., not official OFCCP policy) . . . but OFCCP has used it!

• 2-30-30-3

• 5-30-10-3

• Initially created using the data given in response to Item 11 of the itemized listing

– OFCCP claims they don’t use this any more but it is still a useful “rule of thumb”

24

13

Type 1: OFCCP’s “Compensation Triggers”2/30/30/3 5/30/10/3


• Test 1: Is there at least one occurrence of a two percent or greater difference in pay between groups?

• Test 2: Are there at least 30negatively impacted women or minorities?

• Test 3: Are at least 30% of women

• Test 1: Is there at least one occurrence of a five percent or greater difference in pay between groups?

• Test 2: Are there at least 30negatively impacted women or minorities?

• Test 3: Are at least 10% of women

25

• Test 3: Are at least 30% of women or minorities negatively impacted?

• Test 4: Are the women or minorities being negatively impacted at a rate that is at least three times the impact of the men or non-minorities?

• Test 3: Are at least 10% of women or minorities negatively impacted?

• Test 4: Are the women or minorities being negatively impacted at a rate that is at least three times the impact of the men or non-minorities?

Type 2: The Search for Low-Lying Fruit:• Red-flag analysis often misses legitimate problem areas


Red flag analysis often misses legitimate problem areas.

• At the end of the day, compensation enforcement is based on individual SSEGs and/or job titles . . . so . . . look for individual job titles with large differences in average salaries between men/women or whites/minorities.

• The degree of “Low-Hanging Fruitedness (sic)” is based on:

Si f diff i l (bi diff b d)– Size of difference in average salary (big differences are bad)

– Number of employees (big numbers are bad here too)

Important note: Large differences in average salaries between groups can mean a legitimate issue . . . or an incorrect grouping of employees.

26

14

2. Request for Additional Data:– If the OFCCP finds a reason to investigate further they will


request additional data. This data typically includes:

OFCCP 12-Factor Data Request

Employee ID Current base salary

Gender PT/FT

Race/Ethnicity Exempt/Non-Exempt

Time in Company Job Title

27

Time in Job Grade or Salary Band

Date of birth Location

• Important note: BCG recommends employers submit the necessary data/fields to explain differences in salary regardless of whether they are requested.

3. Employing Multiple Regression Analysis:


C iCompensation

SSEG

Job Related Variables

Multiple Regression

“Ingredients”

“Tool”

28

Multiple Regression

Potential Problem Area(s)

Anecdotal Evidence

Tool

“Product” (i.e., results)

“Additional Ingredient”

Discrimination

15

What is a Similarly Situated Employee Group (SSEG)?


Similar Work Similar Level of Responsibility

SSEG

29

Similar Qualifications

Similar Skill Levels

Important note: BCG recommends employers create realistic/appropriate SSEGs without consideration of required minimum sample size (i.e., “they are what they are”).


30

16

Multiple Regression Defined

Multiple Regression

– Allows an analyst to determine whether differences in compensation are due to “legitimate job-related factors” or “some other factors”—especially those that that appear to be directly related to gender or ethnicityethnicity.

31

Explaining Compensation: Before Controlling for Legitimate Factors

r = 35


Compensation

(100%)Employee

Gender

r .35

32

Percent of compensation explained by gender (12%)

17

Why Multiple Regression?


Differences in Compensation

Experience

Performance

Gender

Multiple Regression

Allows an analyst to determine whether differences in compensation are due to “legitimate job-related factors” or “some other p

Tenure

Education

Job Market Factors

factors or some other factors”—especially those that that appear to be directly related to gender or ethnicity.

33

Multiple Regression and Correlation

Correlation – describes the degree of relationshipbetween two variables.

Salary Time with Company

Gender

Salary 1 .35 .63

Time with Company .35 1 .20

Gender .63 .20 1

Sample correlation matrix/table:

3

3434

Correlation coefficient (r) between salary and time with company = .35

18

Correlation Coefficient (r = .35)


Think--- “Co-Relation”io

nio

n

35

Co

mp

en

sat

Co

mp

en

sat

Time with CompanyTime with Company

35


ion

ion

Co

mp

en

sat

Co

mp

en

sat

Time with CompanyTime with Company

36

19

• Always between -1.00 and +1.00• Closer to + or – 1.00: stronger the

l i hi

• Always between -1.00 and +1.00• Closer to + or – 1.00: stronger the

l i hiR

The Correlation Coefficient


relationship• Closer to 0.00: weaker the relationships• 0.00: “no relationship”

relationship• Closer to 0.00: weaker the relationships• 0.00: “no relationship”

Range

• Negative numbers: “as one variable goes up the other variable goes down”

• Positive Numbers: “as one variable goes up the other variable goes up”

• Negative numbers: “as one variable goes up the other variable goes down”

• Positive Numbers: “as one variable goes up the other variable goes up”

Direction

• If you square the correlation coefficient, the number you get tells you “the percent of one variable that is accounted for by the other variable.”

• If you square the correlation coefficient, the number you get tells you “the percent of one variable that is accounted for by the other variable.”

Coefficient of Determination

37


en

sati

on

en

sati

on

Regression/PredictionRegression/PredictionLineLine

YY

Co

mp

eC

om

pe

Time with CompanyTime with CompanyXX

38

20

How Does Multiple Regression Help Identify Potential Pay Discrimination?

Model Showing No Discrimination


Compensation Tenure

Education Experience

• All variables together become the basis for a prediction “model” known as a regression model.

Th i d l

39

Performance

Gender

• The regression model predicts a certain percentage of what makes up an employee’s compensation.••R = .67R = .67

••RR22 = 45%= 45%

How Does Multiple Regression Help Identify Potential Pay Discrimination?

Model Showing Discrimination


Compensation Tenure

Education Experience

• Q: So how does regression help to identify discrimination in pay?

• A: If the prediction d l b

40

PerformanceGender

model becomes significantly better afterincluding the protected variable.

••RR22 = 45%= 45%••without without gendergender

••RR22 = 51%= 51%••With With

gendergender

21

A Word About Potentially“Tainted Variables”


TaintedTainted UntaintedUntainted

41

Questions for Contractors before using multiple regression:

D t C id ti G i M th d (S l )


Data Considerations

• Do I have the data needed for this type of analysis (i.e. time in company, previous experience, performance appraisal, etc.)?

Grouping Method (Samples)

• Job Title/Job Code• Pay Grade/Salary Band• SSEG• Job Group

42

• Consider different groups might use different factors.

• Is the data in electronic format?

22

Questions for Contractors before using multiple regression (continued):


How should I consider splitting my employees? Samples:

• Location• AAP

Li f b i

Have I considered sample size?

• When should I use multiple regression?

43

• Lines of business• Exemption Status

regression?• 30 and 5

• When should I do a cohort analysis?

Pitfalls and Issues to Consider

44

23


The dog chasing its tail: Making compensation changes to one group can affect others (for better g g p (or worse)

– Rectifying problem areas for women may create problem areas for minorities

– Rectifying problems in one SSEG may create problems for a department, location, manager, etc.

45

• “Statistical Power” issues

R i l b “d t i t i ”


• Regression analyses can be very “data intensive”

• Missing variables

• Missing data within a variable (regression analyses typically require all data for all records)

• Be sure to analyze your explanatory variables for inequities between groups (e.g., performance appraisal scores)

46

24

• Be sure to evaluate and include an adequate timeframe for your data (e.g., performance appraisal scores, productivity metrics etc )


productivity metrics, etc.)

• Flip-flops in disparities (against men/whites in some circumstances and women/minorities in others) may mean your organization does not systematically discriminate . . . this strategy has been used to undermine class claims of discrimination.

• Statistics are cold and must be supported by anecdotal evidence

• Personnel files/records (i.e., cohort analysis)

47

Recommendations

48

25

Recommendations

• All correspondence, analyses, and results should be covered under attorney-client privilege.

Perform a preliminary “trigger test” analyses on all compensation • Perform a preliminary trigger test analyses on all compensation data prior to submitting plan to OFCCP.

• Identify the factors/variables that affect compensation (may be different by location, department, etc.). Rank-order the list.

• Establish company-wide data collection/retention protocols for those compensation factors (beginning with the top of the list).

• Perform yearly, proactive regression analyses by job title and pay grade or SSEG (Important: Be mindful of “low lying fruit”).

• First perform “preliminary” regression analyses by including only 2-3 primary variables that are readily available.

• Include additional relevant explanatory variables, if necessary.49

• Evaluate all statistically significant differences using a non-statistical cohort analysis (i.e., file-by-file comparison).

Recommendations

comparison). – In most cases, the OFCCP will only issue a Notice of Violation

where there is both statistical and anecdotal evidence of discrimination.

• If proper regression analyses and a file-by-file cohort review fail to identify justifiable reasons for compensation disparities, calculate the amount needed to eliminate statistical significance and consider making changes – (Important: Beware of the dog chasing it’s tail – perhaps conduct

“what if” analyses).

• GET HELP!!!50

26

Additional Resources

51


• Interpreting Nondiscrimination Requirements of Executive Order 11246 with Respect to Systemic Compensation DiscriminationCompensation Discrimination

– http://www.dol.gov/esa/regs/fedreg/notices/2006005458.htm

– This document outlines the OFCCP’s definitive compensation analysis strategy and guidelines.

• Voluntary Guidelines for Self-Evaluation of Compensation Practices for Compliance with Nondiscrimination Requirements of Executive Order Nondiscrimination Requirements of Executive Order 11246 with Respect to Systemic Compensation Discrimination

– http://www.dol.gov/esa/regs/fedreg/notices/2006005457.htm

– This document outlines a recommended compensation analysis structure similar to that used by the OFCCP (and to be used by contractors who wish to request the compliance coordination incentive).

52

27

• Miscellaneous articles and flowcharts on regression and compensation

biddl / ti


www.biddle.com/compensation

• Adverse Impact and Test Validation: A Practitioners Guide, 2nd Ed. by Dan Biddle, Ph.D.

• Miscellaneous resources• Miscellaneous resourceshttp://www.bcginstitute.org/resources_articles_books.php

53

Questions

54

Compensation 101 for Federal Contractors - Preparing for ... · 1 Compensation 101 for Federal Contractors - Preparing for OFCCP Changes in 2010 May 19, 2010 Please wait while others

Documents