Adverse Impact Analyses Done Right: Straight Talk for Practitioners Patrick M. Nooren Ph.D. June 30. SHRM 61st Annual Conference & Exposition

Transcription

1 Adverse Impact Analyses Done Right: Straight Talk for Practitioners Patrick M. Nooren Ph.D. June 30 SHRM 61st Annual Conference & Exposition 1

2 Contact Information Patrick M. Nooren, Ph.D. Biddle Consulting Group, Inc. 193 Blue Ravine, Ste. 270 Folsom, CA

3 About Biddle Consulting Group Established 1974 Over 200+ cases in EEO/AA (both plaintiff and defense) EEO Litigation Support / OFCCP Audit Support Compensation Analyses / Test Development and Validation Adverse Impact and Test Validation, 2 nd Ed. EEO Insight Refereed Journal ( Software/Web Tools: OPAC (Administrative Skills Testing) CritiCall (911 Dispatcher Testing) AutoAAP (Affirmative Action Software and Services) C 4 (Call Center Employee Testing) Encounter (Video Situational Judgment Test) Adverse Impact Toolkit ( 3

4 Agenda The Current State of Enforcement Adverse Impact - An Overview - Step Analyses - The Typical Approach - The Right Way (Mantel-Haenszel) Summary/Conclusion 4

5 The Current State of Enforcement 5

6 The Current State of Enforcement OFCCP continues to ramp-up auditing and enforcement 6

7 The Current State of Enforcement 95+% of the OFCCP s financial remedies are based on adverse impact in hiring (remainder = compensation disparities) Most prevalent issues in conciliation agreements are applicant tracking/recordkeeping and adverse impact in the hiring process These are both issues that should be identified in an AAP... so why do they appear so often in conciliation agreements? 7

8 Adverse Impact: An Overview 8

9 Adverse Impact: An Overview Adverse Impact: The beginning... 80%? 70%? 90%? 9

10 Adverse Impact: An Overview Adverse Impact: Today... Statistical Significance Practical Significance Step Analyses Mantel-Haenszel/Breslow-Day Logistic Regression 10

11 Adverse Impact: An Overview ADVERSE IMPACT DEFINED BY THE 1964/1991 CIVIL RIGHTS ACT An unlawful employment practice based on disparate impact is established under this title only if: A(i) a complaining party demonstrates that a respondent uses a particular employment practice that causes a disparate impact on the basis of race, color, religion, sex, or national origin, and the respondent fails to demonstrate that the challenged practice is jobrelated for the position in question and consistent with business necessity; OR, A(ii) the complaining party makes the demonstration described in subparagraph (C) with respect to an alternate employment practice, and the respondent refuses to adopt such alternative employment practice. 11

12 Adverse Impact: An Overview Primary Type of Analysis SELECTION RATE COMPARISON 2 X 2 Table Comparison Evaluates hires, promotions, terminations, took v. passed test, etc. Fisher s Exact / Chi-Square Men Pass Women Pass Men Fail Women Fail 12

13 Adverse Impact: An Overview SELECTION RATE COMPARISON Statistically Significant Result + No Job Relatedness / Validity = Adverse Impact Discrimination 13

14 Adverse Impact: An Overview Adverse Impact Discrimination Flowchart or YES Practice, Procedure, Test (PPT) Adverse Impact? NO Is the PPT Valid? END YES NO Alternative Employment Practice? Plaintiff Prevails NO Defendant Prevails YES Plaintiff Prevails 14

15 Adverse Impact: Step Analyses

16 Adverse Impact: Step Analyses Title VII of 1964/1991 Civil Rights Act An unlawful employment practice based on disparate impact is established under this title only if: A(i) a complaining party demonstrates that a respondent uses a particular employment practice that causes a disparate impact... **OFCCP Insight** The OFCCP has every right to investigate the individual practices, procedures, and tests contractors use to screen applicants. However, due to resource constraints they will not typically do so unless there is adverse impact in the overall hiring process. Overall adverse impact has become the red-flag used to identify where/when to investigate further. 16

17 Adverse Impact: Step Analyses 17

18 Step Analysis: Pop Quiz 1. Applications Submitted 2. Application Review Hiring Process Census Data 3. Invitation to Interview 4. Interview Applicant Pool Q1: How would you conduct an overall analysis? Q2: How many steps are there in the process (subject to AI)? Q3: How would you analyze the BQ s for AI? Q4: How would you analyze the pool of applications received (i.e., is the pool tainted )? 5. Offer/Hire 18

19 Adverse Impact: The Typical Approach

20 Adverse Impact: The Typical Approach Analyses by AAP job group regardless of different: > Job titles > Selection processes > Hiring managers > Basic qualifications > Locations (perhaps) > Applicant pools for separate requisitions (perhaps) Typically an aggregation of 12 months (sometimes 18/24 months) worth of transactions into a single 2x2 table Considers everyone who applied throughout the year as available for every hire throughout the year 20

21 Adverse Impact: The Typical Approach ALL applicants and ALL hires for a 12- month period Men Pass Women Pass Men Fail Women Fail There is nothing wrong with this approach... as an initial inquiry only. The problem is that too often this approach is used as the basis for a Notice of Violation (NOV). It is up to the employer to provide rebuttal analyses that more accurately reflect reality. 21

22 Adverse Impact: The Right Way

23 Adverse Impact and Statistical Power Statistical significance: The point at which differences become large enough that one can claim a trend exists. Statistical power: The ability to see those trends if, in fact, they do exist. Statistical power is directly related to effect size and sample size: > Effect size: The size of the difference in selection rates between two groups... the larger the difference the less number of transactions necessary to detect statistical significance > Sample size: With larger numbers of transactions it becomes much easier to detect statistical significance 23

24 Adverse Impact and Statistical Power Company A Company B Company C Company D 1.953

25 Adverse Impact and Statistical Power The OFCCP has no control over effect size (i.e., the difference in selection rates), but they do have some control over sample size... which is why they often request two (2) years worth of data to analyze. However, simply aggregating all applicants and all hires across strata (as is typically done), frequently results in incorrect/misleading findings. 25

26 Adverse Impact Across Years: Simpson s Paradox SIMPSON'S PARADOX EXAMPLE Testing Year Group # Applicants # Selected Selection Rate % 2004 Test 2005 Test Tests Combined Men % Women % Men % Women % Men % Women % Standard Deviations: Fisher Exact Test: Z = 2.12 (Significant) Mantel-Haenszel: Z =.024 (NOT significant) 26

27 Mantel-Haenszel

28 Single Event v. Multiple Event Analyses ALL applicants and ALL hires throughout the time period Men Pass Women Pass Men Fail Women Fail = Chi-Square or Fisher s Exact Req: 1 Req: 2 Req: 3 Men Pass Women Pass Men Fail Women Fail + Men Pass Women Pass Men Fail + Women Fail Men Pass Women Pass Men Fail Women Fail = MH 28

29 Mantel-Haenszel (MH) Defined In the context of selection rate comparison analyses (UGESP 4D), the MH: > is a statistical tool that allows researchers to appropriately combine separate and distinct selection processes into a single analysis > appropriately allows for the benefits of increased sample size while controlling for Simpson s Paradox > can analyze an overall selection process over time OR an individual practice, procedure, or test over time The MH is a useful tool for evaluating whether the employer has a pattern and practice that is possibly discriminatory 29

30 Mantel-Haenszel (MH) Defined The Mantel-Haenszel is not for every situation. It requires separate and distinct pools of applicants/test takers, etc. For example, combining: Requisitions Locations Different jobs in same job group Different hiring seasons and/or groups Not applicable for pooled requisitions or situations where applicants are moved between jobs, requisitions, pools, etc. 30

31 IT S FREE!! Before you start freaking out, remember

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33 Summary/Recommendations Realize that the OFCCP uses the single-pool aggregated approach as their initial Red Flag analysis > If there is no AI... the contractor is likely OK to submit the plan > If there is AI... it is up to the contractor to properly analyze adverse impact and prepare an explanation Do not allow a single-pool analysis to be used as the basis for an NOV... unless it is appropriate Find the step in the process causing the impact (if any) and make sure it is validated (remember, adverse impact only becomes discrimination in the absence of validity) Remember, there are other statistical tools (e.g., logistic regression) that can be used to identify why differences in selection rates exist Be proactive in your defense have a plan work the plan 33

34 Questions? 34