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Meeting of July 18, 2012 – Public Input into the Development of EEOC's Strategic Enforcement Plan

Written Testimony of Marc Bendick, Jr., Ph.D.1
Bendick and Egan Economic Consultants, Inc

Madam Chair and Distinguished Commissioners:

Thank you for this invitation to testify. I am Dr. Marc Bendick Jr., an employment economist who has been involved in EEO issues as a researcher and expert witness for more than 30 years.

My response to your request for input on national enforcement priorities makes one recommendation: that the agency should allocate a very substantial share of its enforcement resources -- for example, half -- to strategic enforcement campaigns in a small number of industries where research indicates that discrimination is particularly egregious and the potential for improved employment outcomes is particularly large.

In this testimony, I first argue that such industry-level strategic targeting offers a “win–win” opportunity that would simultaneously benefit taxpayers, employees, and employers. I then provide eight suggestions concerning how to implement this approach.

Taxpayers Deserve State-of-the-Art Management Practices

The first reason for implementing industry-level strategic targeting is that it represents well-established, state-of-the-art practices in enforcement. It would support the efficient and effective management that taxpayers should expect from federal agencies.

Targeting enforcement where significant violations are most likely to be found is standard practice in compliance management throughout the private and public sectors. In accounting and auditing, auditing less than 100% of financial data and targeting the highest-risk items is a professional practice that has been widely accepted for decades.2 Within the federal government, enforcement prioritization is a standard practice in agencies ranging from the Internal Revenue Service3 to the Environmental Protection Agency.4 Many state and local governments also use statistical data to target enforcement actions, for example in allocating occupational health and safety inspections.5

In the EEOC’s sister enforcement agency, the OFCCP, prioritization in allocating its primary enforcement activity -- employment reviews of federal contractor establishments with 50 or more employees -- has long been practiced. OFCCP has sufficient staff and budget to review only about 2.5% annually of the approximately 200,000 federal contractor establishments it supervises. For several decades, the OFCCP has analyzed establishments’ EEO-1 reports to create statistical formulas predicting the probability that a review will find a significant violation of federal requirements. For example, the agency’s practices around 2004 have been described follows:6

The system the OFCCP has historically been using to select establishments for compliance audit includes processing information reported in a contractor’s EEO-1 Report into an Equal Employment Data System (EEDS). The EEDS system compares the establishment’s workforce with those of other industry establishments within the same geographic area. With the aid of Westat, an outside consultant, the OFCCP developed a new statistical model called the Federal Contractor Selection System (FCSS). The new targeting model analyzes EEO-1 and 2000 Census data to identify establishments that appear likely to have systemic discrimination. Using the new system, the OFCCP has selected 3,560 establishments for possible compliance reviews during the new OFCCP scheduling cycle which began July 2004.

Suggestions that such OFCCP practices are relevant to the EEOC often are dismissed by noting that, unlike the OFCCP, the EEOC’s primary enforcement actions are responses to worker complaints, not agency-initiated employer reviews. However, this reaction ignores a more fundamental similarity between the two agencies. Like the OFCCP, the EEOC must select a very limited number of enforcement actions to pursue from among many times that number of potential actions. For example, in FY 2011, the EEOC received 99,917 charges but reported only 10,234 resolutions of charges -- only 9.1% as many -- and initiated litigation only 300 times.7

In deciding which charges to pursue and how deeply to pursue each of them, the EEOC traditionally delegates extensive discretion to its field offices, sometimes combined with efforts to persuade those offices to reflect national priorities (for example, in recent years, systemic discrimination8). My recommendation today calls for shifting the balance of decision-making away somewhat from such local discretion toward more nationally-identified strategies. However, I am not suggesting moving away from using employee charges as the basis for EEOC enforcement, but rather modifying the criteria used to select which charges are pursued.

Discrimination Would be Identified and Addressed More Effectively

Given the EEOC’s anti-discrimination mission, my recommendation is justified only if it will result in more equal opportunity in the workplace than under the present approach.

One indicator that this would be the result is the substantial body of scholarly research which identifies industries or occupations where employment practices are substantially more problematic than in the American labor market as a whole. The EEOC itself has produced several such studies; the agency’s website today offers reports on the finance industry, mass media, high-end department stores, and law firms.9 My recommendation calls for the agency to substantially expand such studies and -- more importantly- to systematically connect their findings to agency dexisions concerning wihic charges to pursue.

Most of the research identifying particularly discrimination-prone industries has been produced by economists and others working independently of the EEOC. Rather than attempting a comprehensive inventory of this large body of work, I will simply provide three examples drawn from my own research.10

The first example involves a study, conducted with my colleague Dr. Mary Lou Egan, of African American professional and managerial employees in the advertising industry.11 As employment discrimination has sharply diminished across the overall American labor market over recent decades, systemic barriers to equal opportunity in this $31 billion a year industry have remained largely intact. Across multiple measures of employment outcomes for Black professionals and managers compared to Whites with similar qualifications, the Black–White gap averages 38% larger in advertising than in the overall U.S. labor market. Moreover, the divergence between racial equality in this industry and the rest of the labor market is more than twice as large today as 30 years ago. For example:

  • Earnings: Black college graduates working in advertising earn $.80 for every dollar earned by their equally-qualified White counterparts This racial pay gap is more than twice as large in advertising as in the overall labor market.
  • Employment: Census data suggests an expected representation of African Americans of 9.6% among advertising managers and professionals. The current 5.3% representation reaches only 55% of that benchmark, and eliminating this shortfall would require hiring or promoting 7,200 additional Black professionals and managers.
  • Employer Segregation: African Americans are often excluded from “general market” advertising agencies and find work only in agencies specializing in “ethnic markets.” About 16% of large establishments in the industry employ no Black managers or professionals, a rate 60% higher than in the overall labor market.
  • Occupational segregation: Blacks are only 62% as likely as their White counterparts to work in advertising agencies’ powerful “creative” and “client contact” functions and only 10% as likely to hold a position paying $100,000 or more per year. Such occupational segregation currently affects 3,500 Black professionals and managers employed in the industry.

A second example involves my study, again conducted with Mary Lou Egan, of women in the construction trades.12 Among “blue collar” occupations, the construction trades offer employment for persons without extensive post-secondary education that is unusually attractive in both financial and non-financial terms. Women represent only about 3.0% of on-site workers in the construction industry today. The expected representation of women among these workers is estimated at between 5.5% and 8.1%, implying an underutilization of women in the construction industry of between 220,000 and 700,000 workers nation-wide. This under-utilization characterizes all major construction occupations, from laborers and helpers to skilled crafts such as carpenters and electricians. It is deeply embedded in the attitudes and employment practices (“workplace culture”) dominant throughout the construction industry, and involves widespread bias, both conscious and unconscious, often including blatant harassment. Hence it is perhaps not surprising that this under-representation has remained virtually unchanged for more than three decades.

A third example involves my study, conducted in conjunction with the Restaurant Opportunity Center of New York, of recent immigrants and other persons of color in the restaurant industry.13 While millions of people are employed in restaurants, only a subset of jobs in that industry pay enough to support a family at a middle class standard of living. Prominent within that subset are server (waiter/waitress/bartender) positions in upscale restaurants. Using a research technique called paired comparison testing,14 this study rigorously documented that, when white and race-ethnic minority job seekers with equal qualifications applied for server positions in New York City fine dining restaurants, minorities were only 54% as likely as whites to receive a job offer. This discrimination was documented in 31% of restaurants tested, including some of the nation’s most prominent multi-establishment chains. Post-hiring differences in treatment appear even more widespread, with minority restaurant servers averaging 12% lower earnings than their equally-qualified white peers. Ensuring equal treatment in hiring would expand minority access to well-paid restaurant server positions by Manhattan alone by 3,500 positions.

When anti-discrimination enforcement resources have been strategically concentrated on such “hot spot” industries, substantial improvements in industry employment practices have sometimes been achieved. Over recent decades, such strategic efforts have been undertaken by several of the nation’s prominent plaintiff-side class action private law firms, with targets such as the supermarket industry, large chain retailers, and the financial services industry. The results have been thousands of new employment opportunities for women, race-ethnic minorities, and other protected classes. Many of these opportunities have come from firms which were the defendants in litigation. Others have come from other firms in the industry who were prodded to change their employment practices by observing the litigation being brought against their industry peers. Furthermore, through pursuing repeated cases against firms in the same industry, the litigators became increasingly knowledgeable and efficient in bringing each case.

Employers Benefits from Strategic Targeting

It would be naïve to expect the employer community to be broadly enthusiastic about EEOC enforcement activities of any sort. However, an initiative to pursue enforcement more strategically, if correctly implemented, should enhance employer support, for at least two reasons. First, strategic targeting should result in fewer enforcement actions where employers expend large amounts of resources defending against charges involving few employees and small amounts money -- circumstances which, I have observed, many employers particularly resent.

Second, strategic targeting should result in fewer enforcement actions being brought against employers who are trying in good faith to comply with anti-discrimination laws and regulations. Research suggests that such employers may constitute as many as 80% or more of employers today.15 By concentrating enforcement on the most egregiously-behaving minority of employers, the EEOC may be able to mitigate opposition to its enforcement activity on the part of the majority of employers.

Eight Implementation Steps

To implement the approach I am recommending, I urge the Commission to undertake eight specific actions.

  • First, the EEOC should engage outside researchers to synthesize existing research on industry-level patterns of employment discrimination and advise the agency on the targeting implications of this research.
  • Second, the EEOC should proactively analyze its own rich EEO-1 data resources to identify priority industries where enforcement actions should be concentrated.16
  • Third, the EEOC should enhance its capacity to identify all complaints and enforcement actions against individual firms and industries, including those involving the EEOC, OFCCP, state and local fair employment practice agencies (FEPAs), and private litigators.
  • Fourth, based on the results of the first three steps, the EEOC should develop -- and publicly announce through its strategic enforcement plan -- its industry-level enforcement priorities.
  • Fifth, the EEOC should develop policies and procedures for systematically assessing the employment impacts --- the number and quality of jobs -- of potential enforcement activities.
  • Sixth, the EEOC should develop policies and procedures for ensuring that its field offices’ choice of charges to pursue reflect the priorities identified in step four and the employment impacts identified in step five.
  • Sixth, the EEEOC should develop policies and procedures for coordinating its use of Commissioners’ Charges and Directed Investigations with complaint-based enforcement to support strategic enforcement campaigns within priority industries.
  • Seventh, the EEOC should expand its “national law firm” concept to develop specialized litigation teams that handle enforcement nationwide for individual priority industries.
  • Eighth, The EEOC should aggressively publicize its enforcement activities within each industry, seeking to maximize the influence of these efforts on peer firms not directly affected by the enforcement actions.17

Footnotes

1 Bendick and Egan Economic Consultants, Inc., 4411 Westover Place, N.W., Washington, DC 20016; (202) 686-0245; bendickegan@mindspring.com; www.bendickegan.com.

2 See AICPA, Audit Sampling-AICPA Audit Guide (New York: American Institute of Certified Public Accountants, 2008); National Academy of Sciences, Statistical Analyses and Models in Accounting (Washington: National Academies Press, 1988); and L. Rittenberg, K. Johnstone, and A. Gramling, Auditing: A Business Risk Approach (Mason OH: South-western, 2010).

3 The IRS describes its statistical targeting of audits of individuals’ federal income tax returns as follows:

Some returns are selected for examination on the basis of computer scoring. Computer programs give each return numeric “scores.” The Discriminant Function System (DIF) score rates the potential for change, based on past IRS experience with similar returns. The Unreported Income DIF (UDIF) score rates the return for the potential for unreported income. IRS personnel screen the highest-scoring returns, selecting some for audit and identifying those items on these returns that are most likely to need review.

(IRS, The Examination (Audit) Process, downloaded on May 2, 2011, from http://www.irs.gov/newsroom/article/O,id=151888,00.html).

4 For example, in 2010, the EPA proposed a statistical scoring system to identify public water systems where significant non-compliance with the Safe Water Drinking Act is most prevalent. Points are assigned for each water system’s uncorrected violations of multiple agency rules over the previous five years, with each violation weighted by the seriousness of its impact on public health. Water systems whose total score exceed 11 points receive priority for agency enforcement efforts (EPA List of Significant Non-Compliers (Waterworks-Enforcement Targeting downloaded on May 2, 2011 from http://www.vdh.state.va.us/DrinkingWater/compliance/snclist.htm.

5 For example, in scheduling health inspections, the Minnesota Occupational Safety and Health Administration prioritizes industries where the Federal OSHA Data Initiative, workers’ compensation data, and Bureau of Labor Statistics occupational illness and injury rates indicate the highest risk. Based on its analyses of these data, in 2004, the Minnesota agency allocated 60% of its routine inspections to only eight industries, including construction, furniture manufacturing, food and kindred products, and rubber and plastics manufacturing. The counterpart agency in Oregon develops its inspection schedule based on points reflecting each employer’s history of disability claims and OSHA violations and the history and rates for that employer’s industry (OSHA, Enforcement: Targeting High-Risk Worksites, 2004, downloaded on May 2, 2011 from http://www.osha.gov/dcps/osp/oshpa/2004_report/emnforcment.html.

6 Seyfarth Shaw, OFCCP Plans New Initiatives, at www.sayfarth.com/dir_docs/, downloaded May 2, 2011.

7 Statistics downloaded from http://www.eeoc.gov/statistics on July 15, 2012.

8 Systemic Task Force Report, March 2006 (www.eeoc.gov/eeoc/task_report/).

9 These documents are available at http://www.eeoc.gov/eeoc/statristics/reports/index.cfm.

10 An additional relevant study of mine which I do not discuss here describes widespread discrimination in the fire-fighting industry: Denise Hulett, Marc Bendick, Jr., Sheila Thomas, and Francine Moccio, “Enhancing Women’s Inclusion in Firefighting in the USA,” International Journal of Diversity in Communities, Organisations, and Nations 8 (2008), pp. 189-208. One example of a study by researchers other than me is: Mary Graham, and Julie Hotchkiss, “A More Proactive Approach to Addressing Gender -Related Employment Disparities in the United States, Gender in Management: An International Journal 24 (2009), pp. 577-595. This analysis identifies Mining & Construction and Transportation, Communications & Utilities as priority industries for anti-discrimination enforcement.

11 Marc Bendick, Jr., and Mary Lou Egan, Research Perspectives on Race and Employment in the Advertising Industry (Washington, DC: Bendick and Egan Economic Consultants, Inc., for the NAACP and the Madison Avenue Project, 2009). See also Marc Bendick, Jr., Mary Lou Egan, and Louis Lanier, “The Business Case for Diversity and the Perverse Practice of Matching Employees to Customers.” Personnel Review 39 (2010), pp. 468-48.

12 See Marc Bendick, Jr., Mary Lou Egan, John J. Miller, and Louis Lanier, The Availability of Women, Racial Minorities, and Hispanics for On-Site Construction Employment. (Washington, DC: Bendick and Egan Economic Consultants, Inc., for the U.S. Department of Labor, November 2010).

13 See Marc Bendick, Jr., Rekha Rodriguez, and Sarumathi Jayaraman. “Employment Discrimination in Upscale Restaurants: Evidence from Paired Comparison Testing.” Social Science Journal 47 (2010), pp. 802-818, and The Great Service Divide, Occupational Segregation and Inequality in the New York City Restaurant Industry (New York: Restaurant Opportunity Center of New York and the New York City Restaurant Industry Coalition, 2009).

14 See Marc Bendick, Jr., “Situation Testing for Employment Discrimination in the United States of America,” Horizons Strategiques 5 (July 2007), pp. 17-39.

15 See Marc Bendick, Jr., “Using EEO-1 Data to Analyze Allegations of Employment Discrimination.” Presentation, American Bar Association National Conference, 2000; A. Blumrosen, M. Bendick, Jr., J. Miller & R. Blumrosen, Employment Discrimination against Women and Minorities in Georgia. Rutgers, NJ: Rutgers University Law School, 1999.

16 One example for this type of analysis is presented in Marc Bendick, Jr., et al, Gender Occupational Segregation: An Analysis of Employer EEO-1 Reports (Washington, DC: Bendick and Egan Economic Consultants, Inc,., for the Women’s Bureau, U.S. Department of Labor, 2000),

17 See Marc Bendick, Jr., and Mary Lou Egan, “Changing Workplace Cultures to Reduce Employment Discrimination.” Presentation to the Conference on Low Wage Workers in the New Economy, Washington, DC May 2000.