Diversity in the Technology Sector: Federal Agencies Could Improve Oversight of Equal Employment Opportunity Requirements

Technology companies are a major source of high-paying U.S. jobs, but some have questioned the sector's commitment to equal employment opportunity. EEOC provides federal oversight of nondiscrimination requirements by investigating charges of discrimination, and OFCCP enforces federal contractors' compliance with affirmative action requirements. GAO was asked to review workforce trends in the technology sector and federal oversight.

This report examines (1) trends in the gender, racial, and ethnic composition of the technology sector workforce; and (2) EEOC and OFCCP oversight of technology companies' compliance with equal employment and affirmative action requirements. GAO analyzed workforce data from the American Community Survey for 2005-2015 and EEOC Employer Information Reports for 2007-2015, the latest data available during our analysis. GAO analyzed OFCCP data on compliance evaluations for fiscal years 2011-2016. GAO interviewed agency officials, researchers, and workforce, industry, and company representatives.

The estimated percentage of minority technology workers increased from 2005 to 2015, but GAO found that no growth occurred for female and Black workers, whereas Asian and Hispanic workers made statistically significant increases (see figure). Further, female, Black, and Hispanic workers remain a smaller proportion of the technology workforce—mathematics, computing, and engineering occupations—compared to their representation in the general workforce. These groups have also been less represented among technology workers inside the technology sector than outside it. In contrast, Asian workers were more represented in these occupations than in the general workforce. Stakeholders and researchers GAO interviewed identified several factors that may have contributed to the lower representation of certain groups, such as fewer women and minorities graduating with technical degrees and company hiring and retention practices.

Both the U.S. Equal Employment Opportunity Commission (EEOC) and the Department of Labor's Office of Federal Contract Compliance Programs (OFCCP) have taken steps to enforce equal employment and affirmative action requirements in the technology sector, but face limitations. While EEOC has identified barriers to recruitment and hiring in the technology sector as a strategic priority, when EEOC conducts investigations, it does not systematically record the type of industry, therefore limiting sector-related analyses to help focus its efforts. EEOC has plans to determine how to add missing industry codes but has not set a timeframe to do this. In addition, OFCCP's regulations may hinder its ability to enforce contractors' compliance because OFCCP directs contractors to set placement goals for all minorities as a group rather than for specific racial/ethnic groups. OFCCP also has not made changes to its establishment-based approach to selecting entities for review in decades, even though changes have occurred in how workplaces are structured. Without taking steps to address these issues, OFCCP may miss opportunities to hold contractors responsible for complying with affirmative action and nondiscrimination requirements.

GAO makes 6 recommendations, including that EEOC develop a timeline to improve industry data collection and OFCCP take steps toward requiring more specific minority placement goals by contractors and assess key aspects of its selection approach. EEOC neither agreed nor disagreed with its recommendation, and OFCCP stated the need for regulatory change to alter placement goal requirements. GAO continues to believe actions are needed, as discussed in the report.

Since the 1990s, the technology sector has become a major source of  employment in the United States, and the sector is projected to continue  to grow and produce high-paying jobs. As the technology sector has  grown, the nation’s overall workforce has become more diverse and this  trend is expected to continue into the future. Recently, media reports,  technology workforce organizations, and policymakers have raised  questions about diversity in the technology sector workforce and the  extent to which companies are making changes to improve diversity and  prevent discrimination. Diversity has been a focus not only because of  concerns about equal access to these growing and high paying jobs, but  because studies have associated a diversity of perspectives with  enhanced innovation and other business advantages. Federal law  promotes equal employment opportunity by prohibiting companies from  discriminating in employment on the basis of race and gender, among  other things, and generally requires companies contracting with the  federal government to comply with affirmative action and other equal  employment opportunity provisions. The U.S. Equal Employment  Opportunity Commission (EEOC) and the U.S. Department of Labor’s  Office of Federal Contract Compliance Programs (OFCCP) are the  primary federal agencies that enforce these requirements.

You asked us to review gender, ethnic, and racial diversity trends in  technology companies and federal oversight of antidiscrimination laws in  this sector. This report examines (1) the demographic trends in the  representation of women and racial and ethnic groups in the technology  sector for the last 10 years, and (2) the efforts by EEOC and OFCCP to  oversee technology companies’ and technology contractors’ compliance  with equal employment opportunity and affirmative action requirements.

There is no common definition of technology workers or which industries  comprise the technology sector. Therefore for this report, we defined  technology workers as people who work in occupations in the fields of  computing, engineering, and mathematics. We defined the technology  sector as a group of industries with the highest concentration of  technology workers, such as computer systems design and software  publishing, which is an approach similar to what other federal agencies  have used recently to analyze trends within this sector. To describe the  demographic trends within the technology workforce from 2005 through  2015, we analyzed workforce data from the American Community Survey  (ACS) administered by the U.S. Census Bureau and from the EEOC’s  Employer Information Reports (EEO-1).

For this report, we used ACS data to estimate populations in technology  occupations which we refer to as technology workers, or the technology  workforce. We compared the technology workforce to the general  workforce, which we defined as workers in all other occupations,  excluding workers in technology occupations, as a benchmark to  understand trends for the technology workforce in the context of overall  workforce trends. In addition, we conducted further analysis of ACS data  to compare technology workers within and outside the technology sector.  Using EEO-1 data, we also analyzed workforce trends among similar  occupations in the workforces of companies within and outside the  technology sector. Our analysis was not designed to determine the  presence or absence of discrimination.

To understand diversity in academic preparation for technology  occupations, we reviewed 2014 degree completion data from the National  Center for Educational Statistics’ Integrated Postsecondary Education  Data System (IPEDS) as tabulated by the National Science Foundation.  Using a variety of sources, such as academic research and interviews  with representatives from academia, we defined technology-related fields  as degree programs in computer science, engineering, and mathematics.  Through a review of documentation, electronic testing, and/or interviews  with agency officials knowledgeable about the data, we found these data  sufficiently reliable for our purposes.

To review EEOC and OFCCP’s oversight efforts related to technology  companies’ and federal technology contractors’ compliance with federal  equal employment opportunity and affirmative action requirements, we  reviewed relevant federal statutes, regulations, and agency policies and  conducted interviews with agency officials. We analyzed OFCCP data on  affirmative action compliance evaluations from fiscal year 2011 through  2016. We assessed the reliability of the data by reviewing agency  documentation and interviewing agency officials, and we determined that  the OFCCP data were sufficiently reliable for our purposes.

Additionally, we interviewed academics and representatives from  workforce and industry organizations that either promote diversity or  advocate for the technology sector, as well as representatives of eight  information technology companies who work on diversity and inclusion  and compliance issues, to obtain information about challenges and  opportunities for diversity in the sector, and perspectives on federal  oversight of antidiscrimination laws. The views expressed by the  companies’ representatives may not be representative of all technology  companies on these issues. See appendix I for more information on our  methodology.

We conducted this performance audit from May 2016 to November 2017  in accordance with generally accepted government auditing standards.  Those standards require that we plan and perform the audit to obtain  sufficient, appropriate evidence to provide a reasonable basis for our  findings and conclusions based on our audit objectives. We believe that  the evidence obtained provides a reasonable basis for our findings and  conclusions based on our audit objectives.

The technology sector has major employment hubs across the country,  including the San Francisco Bay area, the greater New York City region,  and the Washington-Arlington-Alexandria region (see fig. 1). In addition,  technology workers are employed at companies outside the technology  sector, such as in the retail or financial services industries. For example,  a large retail company may require technology workers to create and  manage their online sales activities, but the company itself would be  considered part of the retail industry.

Federal Requirements Related to Equal Employment Opportunity and Affirmative Action

Private companies are generally prohibited by federal law from  discriminating in employment on the basis of race, color, religion, sex,  national origin, age, and disability status. Additionally, federal contractors  and subcontractors are generally required to take affirmative action to  ensure that all applicants and employees are treated without regard to  race, sex, color, religion, national origin, sexual orientation, and gender  identity, and to employ or advance in employment qualified individuals  with disabilities and qualified covered veterans. EEOC is responsible for  enforcement of federal antidiscrimination laws, and OFCCP enforces  affirmative action and nondiscrimination requirements for federal  contractors. EEOC and OFCCP have some shared activities and have  established a memorandum of understanding (MOU) to minimize any  duplication of effort. For example, under the MOU, individual complaints  filed with OFCCP alleging discrimination under Title VII are generally  referred to EEOC. In addition, on occasions when EEOC receives a  complaint not within its purview, such as cases that involve veteran  status, but over which it believes OFCCP has jurisdiction, it will refer the  complaint to OFCCP.

U.S. Equal Employment Opportunity Commission

The EEOC, created by Title VII of the Civil Rights Act of 1964, enforces  federal laws that prohibit employment discrimination on the basis of race,  sex, color, religion, national origin, age, and disability. As the nation’s  primary enforcer of antidiscrimination laws, EEOC investigates charges of  employment discrimination from the public, litigates major cases, and  conducts outreach to prevent discrimination by educating employers and  workers. In fiscal year 2016, EEOC received about 91,500 charges,  secured more than $482 million for victims of discrimination, and filed 114  lawsuits.

According to EEOC, many states, counties, cities, and towns have their  own laws prohibiting discrimination, usually similar to those EEOC  enforces, as well as agencies responsible for enforcing those laws, called  Fair Employment Practices Agencies. However, in some cases, these  agencies enforce laws that offer greater protection to workers. An  individual can file a charge with either the EEOC or with a Fair  Employment Practices Agency. When an individual initially files with a  Fair Employment Practices Agency that has a worksharing agreement  with the EEOC, and the allegation is covered by a law enforced by the  EEOC, the Fair Employment Practices Agency will dual file the charge  with EEOC (meaning EEOC will receive a copy of the charge), but will  usually retain the charge for processing. If the charge is initially filed with  EEOC and the charge is also covered by state or local law, EEOC dual  files the charge with the state or local Fair Employment Practices Agency  (meaning the Fair Employment Practices Agency will receive a copy of  the charge), but EEOC ordinarily retains the charge for processing.

EEOC also pursues a limited number of cases each year designed to  combat systemic discrimination, defined by the agency as patterns or  practices where the alleged discrimination presented by a complainant  has a broad impact on an industry, profession, company, or geographic  location. EEOC can also initiate a systemic investigation under Title VII  with the approval of an EEOC commissioner, called a “commissioner  charge”, provided the commissioner finds there is a reasonable basis for  the investigation. In addition, EEOC district directors can approve  systemic investigations, called “directed investigations” which are initiated  by EEOC field office directors under the Age Discrimination in  Employment Act and the Equal Pay Act.

Under Title VII, EEOC generally requires that large employers and non- exempt federal contractors file Employer Information Reports (EEO-1  reports) annually, which collect employees’ demographic data by  business location on sex, race, and ethnic group for 10 occupational job  categories. According to EEOC documentation, EEO-1 data are used in  investigations of Title VII violations, litigation, research, comparative  analyses, class action suits, and affirmative action plans.

Office of Federal Contract Compliance Programs

The OFCCP is responsible for ensuring that the nearly 200,000 federal  contractor establishments comply with federal nondiscrimination and  affirmative action requirements. Under Executive Order 11246 and other  federal laws and regulations, covered federal contractors and  subcontractors are prohibited from discriminating in employment on the  basis of race, color, religion, sex, sexual orientation, gender identity, or  national origin and are required to take affirmative action to help ensure  that all applicants and employees are treated without regard to these  factors. In general, OFCCP’s regulations require covered contractors to  comply with certain recordkeeping and reporting requirements, and  provide for enforcement procedures such as compliance evaluations and  complaint investigations to assist OFCCP in ensuring federal contractor  compliance with these regulations.

Among other provisions, OFCCP’s regulations generally require that  covered contractors prepare and maintain an affirmative action program  (AAP). Under OFCCP’s regulations, an AAP is a management tool that  is designed to ensure equal employment opportunity, with an underlying  premise that the gender, racial, and ethnic makeup of a contractor’s  workforce should be representative of the labor pools from which the  contractor recruits and selects. Companies must create an AAP for  each business establishment—generally, a physical facility or unit that  produces the goods or services, such as a factory, office, or store for the  federal contractor. An AAP will also include any practical steps to  address underrepresentation of women and minorities, such as  expanding employment opportunities to underrepresented groups.  Covered contractors must also comply with certain recordkeeping  requirements, including records pertaining to hiring, promotion, lay off or  termination, rates of pay, and applications, among other records.

OFCCP’s enforcement program represents the majority of the agency’s  activity and is carried out primarily by using compliance officers, who  evaluate contractors’ compliance with various requirements, according to  agency officials. In addition to conducting compliance evaluations,  OFCCP also conducts investigations in response to complaints. In 2016,  we reported that according to OFCCP officials, responding to complaints  accounted for close to 16 percent of OFCCP’s enforcement activities.  OFCCP selects contractor establishments for evaluations based on a  number of neutrally applied factors, such as employee count at the  establishment, contract value, or contract expiration date. We previously  found that OFCCP reviews, on average, 2 percent of federal contractor  establishments annually.

As we previously reported, as part of its compliance evaluations, OFCCP  is to review the selected contractor’s hiring, promotion, compensation,  termination, and other employment practices to determine whether  contractors are maintaining nondiscriminatory hiring and employment  practices. OFCCP conducts evaluations at the establishment level.  When a contractor establishment is selected for evaluation, OFCCP  sends the contractor a “scheduling letter” requesting the AAP and  supporting data, such as the percentage of women and minority staff at  the workplace by job group. Then, a compliance officer is to conduct a  desk audit, which is an off-site review of the submitted materials. If  necessary, the compliance officer may also conduct an on-site review or  further off-site analysis to make a final determination as to whether the  contractor is in compliance. In addition to looking at whether federal  contractors maintain nondiscriminatory hiring and employment practices,  which can result in finding discrimination violations, OFCCP also  frequently finds other types of violations, such as failure to keep  necessary records or conduct annual reviews of equal employment and  affirmative action efforts. These findings by the agency often require  administrative changes on the part of the contractor, such as improved  record-keeping. There are many different forms of remedies for  discrimination violations, including financial, employment, and  organizational change remedies. Although rare, under some  circumstances, OFCCP may bar a contractor from doing business with  the government.

Technology Workforce Grew between 2005-2015, but Women and Some Minority Groups Continued to be Less Represented

Compared to General Workforce, the Technology Workforce Grew at a Higher Rate and Continued to be More Educated and Better Paid

From 2005 to 2015, the estimated number of workers in the technology  workforce—people who worked in mathematics, computing, or  engineering occupations—increased at a higher rate (24 percent) than  the estimated number of workers in the general workforce (9 percent),  according to ACS data. In 2015, the technology workforce comprised an  estimated 7.5 million workers, an increase of slightly over 1.4 million  workers since 2005. (For a complete list of the occupations we include  as technology occupations, see appendix II).

Most technology workers have a college degree and have a higher  median income than workers in the general workforce. Specifically, in  2015, an estimated 69 percent of technology workers held at least a  bachelor’s degree, compared to 31 percent of workers in the general  workforce. In 2015, the estimated median income for technology  workers was $81,000 compared to $42,000 for the general workforce.

Women and Certain Minority Groups Continued to be Less Represented in the Technology Workforce and Sector

Comparison of Technology Workforce to General Workforce, by Gender and Race

From 2005 to 2015, the percentage of women in the technology  workforce remained flat and women remained a smaller proportion of the  technology workforce compared to their representation in the general  workforce. In 2015, women represented 22 percent (about 1.6 million  workers) of workers in technology occupations, compared to 48.7 percent  of workers in the general workforce (see fig. 2).

Although the estimated percentage of minority technology workers as a  whole had grown since 2005, we found that this trend did not apply to  Black technology workers. Specifically, from 2005 through 2015, although  the number of Black workers increased as the technology workforce  grew, there was no statistically significant change in their representation  as a percentage of the entire technology workforce. In contrast, from  2005 to 2015, Hispanic and Asian technology workers had statistically  significant increases in their representation in the technology workforce.

Even with the increase in their numbers in the technology workforce,  Black and Hispanic technology workers remained a smaller proportion of  these workers compared to their representation in the general workforce.  In contrast, Asian workers were an increasing share of the technology  workforce, where they remained more represented than they were in the  general workforce (see fig. 3).

We found that when we examined gender representation for each  minority group, both Black and Hispanic men and women were less  represented in the technology workforce compared to their representation  in the general workforce. The same was true for White women, whereas  White men, Asian men, and Asian women were more represented in the  technology workforce compared to their representation in the general  workforce (see fig. 4).

We defined the technology sector as those companies that have the  highest concentration of technology workers and are in such industries as  computer systems design and software publishing. Companies  categorized as outside the technology sector, for example, retail or  finance companies, may still employ some technology workers.  However, we found differences in median incomes for technology workers  within and outside the technology sector. In 2015, technology workers  employed in the technology sector earned an estimated median income  of $89,000 compared to median incomes of $78,000 for those working  outside the technology sector.

We also compared the characteristics of technology workers within the  technology sector and outside the technology sector, and found male and  Asian technology workers were relatively more represented in the  technology sector than outside the technology sector. Similar to the lower  representation of female, Black, and Hispanic technology workers in  technology occupations, we found technology workers from these groups  were also more likely to work outside the technology sector than in the  technology sector. For example, according to our analysis of 2015 ACS  data, women represented an estimated 18 percent of all technology  workers employed in the technology sector, compared to 25 percent of all  technology workers employed outside the technology sector (see fig. 5).  White technology workers were also more represented outside the  technology sector than within the technology sector.

Companies in the technology sector also employ non-technical workers  such as sales people, and the lower representation of women and certain  minorities in the technology sector was also present in such non-technical  job categories. According to our analysis of EEO-1 data, women were  less represented across the full range of management and non- management positions at companies within the technology sector,  including at leading technology companies, compared to their  representation in companies outside the technology sector. We  determined this by comparing specific occupations at companies both  within and outside the technology sectors using 2015 EEO-1 data. For  example, women held about 19 percent of senior-level management  positions at companies in the technology sector compared to nearly 31  percent of such positions at companies outside the technology sector in  2015. Women were also less represented in all of the remaining job  categories (mid-level managers, professionals, technicians, and all other  jobs) in the technology sector. (See fig. 6.)

Comparing EEO-1 data at three points in time for 2007, 2011, and 2015,  we found women’s representation in management positions as well as  among professionals and technicians at companies within the technology  sector remained at about the same level, and decreased for “all other  jobs” (see table 1).

Similar to women, Black and Hispanic workers were less represented  across multiple job categories in companies within the technology sector  compared to those outside the technology sector (see fig.7). For  example, 1.8 percent of senior level managers in the technology sector  were Black compared to 3.4 percent of senior level managers in all other  sectors. Appendix IV provides percentages for each minority group in  different job categories within and outside the technology sector. The  lower representation of Black workers in the technology sector relative to  their representation in other sectors was consistent across all job  categories (mid-level managers, professionals, technicians, and “all other  jobs”). Hispanic workers were less represented in the technology sector  compared to outside the technology sector across all job categories  (senior and mid-level managers, professionals, technicians, and “all other  jobs”). Compared to their representation across job categories within the  technology sector in general, Black and Hispanic workers had slightly  greater representation at the leading technology companies in senior  management and technician categories, and lower representation among  mid-level managers, professionals, and holders of “all other jobs.”

Asian workers comprised a greater proportion of managerial and  professional roles in the technology sector than in other sectors,  according to our analysis of 2015 EEO-1 data. Asian workers represented  11.0 percent of senior level managers in the technology sector compared  to 4.3 percent in industries outside the technology sector. This higher  representation of Asian workers in the technology sector was consistent  among mid-level managers, professionals and technicians. Asian workers  were more represented in the same categories at the leading technology  companies. However, a lower proportion of Asian workers held senior  management positions compared to their representation in professional  positions in both the technology sector and leading technology  companies. Further, the proportion of Asian workers in mid-level  management positions was also lower than their representation in  professional positions, from which mid-level managers might be selected,  in both the technology sector and leading technology companies. In  contrast, a higher proportion of White workers were in senior and mid- level management positions compared to their representation in  professional positions in both the technology sector and leading  technology companies.

Comparing EEO-1 data at three points in time—2007, 2011, and 2015— we saw varied representation across job categories in the technology  sector by race/ethnicity. For example, Black workers decreased in their  representation in all job categories in the technology sector from 2007 to  2015. In contrast, Hispanic and Asian workers increased in their  representation in all job categories we examined from 2007 to 2015 (see  table 2).

Several Factors May Contribute to the Lower Representation of Women and Certain Minority Groups in the Technology Workforce

Several factors may contribute to the lower representation of female,  Hispanic, and Black workers in the technology workforce and at  companies in the technology sector, based on research and interviews  with researchers and representatives from workforce and industry  organizations and technology companies. These include the lower  diversity of degree earners in technology-related fields, and company- based factors such as hiring practices and retention of women and  underrepresented minorities.

The smaller proportion of women in the technology workforce may reflect  the number of women earning technology-related degrees. Slightly over  two-thirds of technology workers report having earned their bachelor’s  degree in a computer, engineering, mathematics, or technology field.  However, according to our analysis of 2014 IPEDS data, the percentage  of technology-related bachelor’s and master’s degrees earned by women  is far less than for men, although women were comparable to men in their  receipt of science, technology, engineering, and math (STEM) degrees,  and surpassed men in obtaining degrees in all other fields. In 2014,  about 60,000 women were awarded technology-related bachelor’s or  master’s degrees (compared to about 50,000 in 2004) and about 190,000  men were awarded such degrees (compared to about 147,000 in 2004).  (See fig. 8.) An estimated 218,000 technology workers were added to the  technology workforce in 2015, according to our analysis of 2015  American Community Survey data from the U.S. Census Bureau. In  addition, technology degrees are also issued at the associate’s level.

Two researchers told us that women often have the academic preparation  to enter into technology-related degree programs, but they may choose  not to pursue such degrees because of instances of gender bias within  technology classes. Our prior work reported on studies that found women  leave STEM fields at a higher rate than their male peers, citing one study  that found women leave STEM academic positions at a higher rate than  men in part due to dissatisfaction with departmental culture, faculty  leadership, and research support. Further, a 2012 consulting firm report  found that businesses viewed as male-dominated tended to attract fewer  women at the entry level.

In addition, according to our analysis of 2014 IPEDS data, three minority  racial or ethnic groups each constituted 10 percent or fewer of bachelor’s  and master’s degree earners in a technology-related field. Specifically,  among the 202,200 earners of degrees in a technology-related field in  2014, there were about 20,000 Hispanic recipients, 13,000 Black  recipients, and 18,000 recipients who were Multiracial or other race,  which includes American Indian or Alaska Native, Other or Unknown  Race, and Two or more Races, i.e. respondents who selected one or  more racial designations. Among all minority groups, Asian students,  including Pacific Islander, earned the highest proportion of technology- related degrees (about 24,000 individuals). (See fig. 9).

One barrier to entry into technology degree paths for Black and Hispanic  students may be lower likelihood of access to preparatory academic  programs in secondary school. In 2016, we reported that the K-12 public  schools in the United States with students who are mostly Black or  Hispanic offered disproportionately fewer math and science classes for  their students. One researcher told us some colleges and universities,  to help these students be academically successful, provide additional  academic support such as tutoring to help bridge knowledge gaps. To  address the uneven access to preparatory math and science classes,  representatives from five technology companies told us they have started  to invest in exposing Black and Hispanic children to technology  occupations by, for example, developing online resources targeted to  them and their parents and creating partnerships with secondary schools  to improve their academic preparation in computer science.

However, we have previously also reported that the number of students  graduating with STEM degrees may not be a good measure of the supply  of STEM workers because students often pursue careers in fields  different from the ones they studied. For example, a lower percentage of  women who obtained technology-related degrees became technology  workers compared to men who earned the same degrees, according to  our analysis of 2015 ACS data. Specifically, among women who earned  technology degrees, an estimated 33 percent worked as a technology  worker compared to 45 percent of men who earned technology degrees.

Several representatives we interviewed from workforce and industry  organizations and technology companies told us that recruitment  practices may also have affected diversity in the technology workforce.  For example, representatives from three workforce and industry  organizations said technology companies tend to recruit from a select  number of universities and colleges, thereby limiting their pool of potential  applicants. To address this, representatives from several of the  technology companies we interviewed told us they had changed  recruitment practices and offered internships targeted to  underrepresented groups. For example, representatives of four  technology companies told us that their companies had expanded  recruitment to include more schools. Representatives from two  companies told us they offer programs such as summer and semester  internships for which the company actively recruits from Historically Black  Colleges and Universities and other specific schools to increase its pool  of diverse candidates.

In addition, representatives from workforce organizations and technology  companies discussed concerns and strategies to address companies’  hiring practices and internal cultures that may limit workforce diversity.

For example, one of these representatives said that technology  companies often offer financial incentives to current employees to make  referrals for new hires, which can result in reliance on social networks.  These networks may be largely comprised of the same race and this  practice therefore makes it harder for potential candidates from  demographically different groups to have their resumes reviewed.  Another workforce organization representative reported that some hiring  managers filter out eligible candidates if their background and  qualifications are not the same as those of previously successful  employees. To address these concerns, representatives from one  technology company told us that they had moved away from depending  on referrals since this practice may result in leaders hiring people within  their own networks, which generally does not increase diversity of gender  or race/ethnicity. In addition, representatives from another company said  they plan to begin reviewing resumes with names removed to limit bias by  the reviewer. Further, representatives we interviewed from three  technology companies told us they offer training to employees to help  employees identify their own, unconscious biases.

Other factors may affect retention of women and underrepresented  minorities. For example, a representative from a workforce organization  said that women leave technology occupations at a higher rate than men  because they feel as if they have not been given the same opportunities  for promotion and advancement within the company. A 2016 study that  examined women in engineering and science found that women’s  concerns about pay and promotion are often an issue in male-dominated  fields regardless of the industry. Further, this study found that retention  difficulties become more severe as the share of men in the workforce  increased and that affected women’s pay and promotion.

Representatives from one company told us another challenge is the lack  of Black workers at the top levels, which might make it more difficult for  Black employees in particular to see a leadership path. Representatives  we interviewed from five technology companies told us they had  implemented efforts to increase retention and promotion rates among  minority and female workers, for example, by developing a diversity and  inclusion newsletter, employee resource groups with executive  sponsors, and internal training and classes for employees to improve  their readiness to be promoted.

Representatives from five technology companies told us that commitment  of top leadership is an important factor that can help women and  underrepresented minorities in the technology sector. For example,  representatives from one company told us that top management support  for diversity efforts, such as setting hiring goals, can help move a  company in the direction of achieving representation goals and that  leadership is very important to this effort. Representatives from several  companies told us that there is often a business case for such changes:  These companies work in a diverse, global environment and strive to  make better products for diverse users. However, our prior work on  workforce diversity in the financial services sector found that some  diversity initiatives faced challenges gaining the "buy-in" of key  employees, such as the middle managers who are often responsible for  implementing such programs.

EEOC and OFCCP Have Taken Steps to Oversee Equal Employment Opportunity and Affirmative Action Requirements, but Face Limitations

EEOC and OFCCP Have Taken Steps to Oversee Compliance in the Technology Sector

According to EEOC officials, EEOC primarily oversees compliance with  equal employment opportunity requirements by investigating workers’  individual charges of employment discrimination filed against companies.  EEOC has publicly acknowledged the low levels of diversity in the  technology sector. However, we were unable to identify a specific  number of charges received by EEOC against companies in industries  that are part of this sector because EEOC does not require investigators  to record the industry of the charged company. EEOC’s database of  charges and enforcement actions—the Integrated Mission System  (IMS)—has a data field for the North American Industry Classification  System (NAICS) industry code, the standard used by federal statistical  agencies in classifying business establishments. However, we found that  it is completed for only about half the entries in the system. EEOC  officials in both the San Francisco and New York district offices told us  that, while they cannot readily identify individual charges against  technology companies, they believe they have received far fewer charges  against technology companies than they would have expected given the  public attention to the issue of diversity in the technology sector. In  terms of systemic cases, according to EEOC, as of June 2017, the  commission had 255 systemic cases pending since fiscal year 2011 involving technology companies (13 of these were initiated as  commissioner charges and 8 were directed investigations involving age  discrimination or pay parity issues). Officials from the New York region  reported that they had seen an increase in systemic cases against  technology companies in the past 3 years, largely involving practices of  information technology staffing firms.

Several EEOC officials we interviewed noted that technology workers  may be initiating few complaints at the federal level due to factors such as  fear of retaliation from employers or the availability of other employment  or legal options. According to EEOC officials, fear of retaliation can affect  charges across sectors and, given the growth in the technology  workforce, an individual who feels discriminated against may simply leave  the company because there are many other opportunities for individuals  with technical skills. They also said that technology workers may  generally have greater wealth and can afford to hire private attorneys to  sue in state court rather than go through the EEOC. Moreover, they said  that some states, including California, have stronger employment  discrimination laws that allow for better remedies than federal laws, which  could lead employees to file charges at the state level rather than with the  EEOC.

In addition, EEOC has acknowledged in a 2016 report that binding  arbitration policies, which require individuals to submit their claims to  private arbiters rather than courts, can also deter workers from bringing  discrimination claims to the agency, leaving significant violations in entire  segments of the workforce unreported. The report stated that an  increasing number of arbitration policies have added bans on class  actions that prevent individuals from joining together to challenge  practices in any forum. The report concluded that the use of arbitration  policies hinders EEOC’s ability to detect and remedy potential systemic  violations. Researchers report that the use of such clauses has grown  and data on federal civil filings for civil rights employment cases reflect a  marked reduction in the number of such filings.

Beyond pursuing charges, EEOC has taken some steps to address  diversity in the technology sector including research and outreach efforts.  In May 2016, citing the technology sector as a source for an increasing  number of U.S. jobs, EEOC released a report analyzing EEO-1 data on  diversity in the technology sector in tandem with a commission meeting  raising awareness on the topic. In addition, EEOC’s fiscal year 2017- 2021 Strategic Enforcement Plan identified barriers to hiring and  recruiting in the technology sector as a strategic priority. EEOC has also  been involved in outreach efforts with the technology sector. For example,  the EEOC Pacific Region described more than 15 in-person or webinar  events since 2014 in collaboration with OFCCP and local organizations  focused on diversity in the technology sector. The topics of these events  included equity in pay and the activities of these two agencies in  enforcing nondiscrimination laws. Finally, in fall 2016, EEOC initiated an  internal working group to identify practices to help improve gender and  racial diversity in technology, but as of June 2017 had no progress to  report.

OFCCP’s regulations require covered federal contractors to take  proactive steps to ensure equal employment opportunity. OFCCP  annually conducts routine evaluations of selected federal contractors,  which includes those in the technology sector, for compliance with federal  nondiscrimination and affirmative action requirements. To the extent  that technology contractors are selected for evaluation through OFCCP’s  normal selection process, these contractors are assessed for compliance  with nondiscrimination and affirmative action laws as are other selected  contractors. While evaluation of technology contractors occurs in the  course of OFCCP’s routine activities, OFCCP does not currently use type  of industry as a selection factor, according to officials. We also found that  few (less than 1 percent) of OFCCP’s 2,911 closed technology contractor  evaluations from fiscal years 2011 through 2016 resulted in discrimination  violations, though 13 percent resulted in other violations, such as record- keeping violations and failure to establish an affirmative action program  (AAP). An AAP is a key tool OFCCP requires contractors to complete to  ensure equal employment opportunity. The remaining 86 percent of  evaluations either found no violations or ended in administrative closure.  Technology contractor evaluations that had discrimination violations  resulted in back pay, salary adjustments, or other benefits totaling more  than $4.5 million for 15,316 individuals (averaging about $300 per award)  for fiscal years 2011 through 2016. The vast majority of discrimination  violations were on the basis of gender or race/ethnicity rather than  disability or veteran status. Corrective actions OFCCP identified for  federal technology contractors over this timeframe also included requiring  contractors to fill a total of 410 job vacancies as they arise with applicants  who had been denied employment on the basis of discrimination. In  addition, OFCCP recently filed three complaints against technology  companies.

According to our analysis, OFCCP conducted evaluations on 36 of the 65  leading technology companies from fiscal year 2011 through fiscal year  2016. During this timeframe there were 272 reviews of establishments— physical business locations—affiliated with these 36 companies. Based  on these evaluations, 15 of the 36 companies had administrative  violations, and 2 of the 36 also had discrimination violations. As a result of  the discrimination findings against these leading technology companies,  541 individuals received monetary benefits totaling $783,387 (an average  of $1,448 per award).

In terms of other steps to conduct oversight of the technology sector,  OFCCP officials in the Pacific Region said they are hiring compliance  officers with legal training to be better able to address needs for reviews  in the technology sector, such as responding to lawyers representing  technology contractors. Officials in both the Pacific and Northeast regions  work closely with statisticians and labor economists on their cases, an  effort officials said has increased over the past few years. OFCCP has  also requested funding in its fiscal year 2018 congressional budget  justification to establish centers in San Francisco and New York that  would develop expertise to handle large, complex compliance evaluations  in specific industries, including information technology.

EEOC Cannot Analyze Charge Data by Industry to Identify Priorities and OFCCP Faces Challenges to Oversight of Technology Companies

We found that by not requiring an industry code in its investigations data,  EEOC cannot analyze charge data by industry to help identify  investigation and outreach priorities, in contradiction to EEOC strategic  planning documents and EEOC Inspector General reports, which have  emphasized the importance of doing so. By not requiring the use of the  NAICS code for each entry in IMS, EEOC is limited in its ability to use  these data for the purposes of identifying charges by industry sector and  conducting sector-related analyses. Officials were aware of substantial  gaps in coding of charges by industry and acknowledged limitations in the  commission’s ability to analyze its investigations data by industry.  However, officials expressed concern that routinely creating more  complete records of the companies against which charges had been filed  would require investigators to divert attention from their efforts to  investigate charges. EEOC officials explained that the charging party  provides initial information on the respondent company and requiring  EEOC personnel to generate this information would slow down the  process. They said their priority is to investigate individual charges, not to  address larger trends or target specific industries. “The Strategic Enforcement Plan recommends using EEOC data to allow our  enforcement and outreach efforts to focus on areas of significant concern. This  might include tailoring outreach efforts for industries that experience greater  likelihood of certain charges or informing enforcement decisions based on  knowledge that certain industries have persistent problems, such as harassment.  The data maintained in IMS provide a rich resource of information that can be  used to explore the characteristics of industries that appear to have higher levels  of certain allegations than comparative industries.”

In addition, reports completed by the Urban Institute for the EEOC Office  of Inspector General in 2013 and 2015 similarly recommended analysis of  charge data, including by industry, to help identify priorities and measure  performance.

While EEOC has plans to review a year of IMS data to clean it and  determine how best to add missing industry codes, among other  objectives, officials could not provide a specific timeframe for when this  review would begin and end. Standards for internal control in the federal  government state that management should use quality information to  achieve the agency’s objectives and objectives should be defined in  specific terms so they are understood at all levels of the entity. This  involves clearly defining what is to be achieved, who is to achieve it, how  it will be achieved, and the time frames for achievement. Efforts to scrub  these data and identify missing codes could help EEOC determine how to  collect industry information on an ongoing basis for all entries. Doing so  would also help EEOC determine the level of NAICS code that would be  feasible and useful for investigators to identify and input into IMS.  Without analyzing its data on charges across industries, EEOC’s ability to  proactively identify priorities for its outreach and enforcement resource  use is limited.

We found that OFCCP also faces challenges that may hinder the  agency’s oversight of technology companies. Specifically, OFCCP  reported facing delays in receiving information from federal contractors,  including technology companies, but has not yet evaluated whether its  own policies and practices also impede its efforts to hold federal  technology contractors responsible for the legal requirements to take  affirmative action and not discriminate against protected groups. In  addition, OFCCP regulations do not require federal contractors to  disaggregate data for the purpose of determining placement goals for  hiring, which may hinder contractors’ efforts to implement effective  affirmative action programs.

OFCCP has not analyzed delays in obtaining information from  contractors  OFCCP officials told us that they face delays in obtaining complete,  accurate, and timely documentation from federal contractors, including  technology companies, as part of the compliance review process. They  said this limited their access to critical information and hindered OFCCP’s  ability to determine whether discrimination had occurred. Officials in the  Pacific Region reported that when issues are identified during OFCCP’s  initial review that will require additional data, the data requests can be  extensive. Consequently, technology contractors are taking longer to  submit complete and accurate data that are needed to conduct analyses  of the contractor’s workforce. In addition, officials in both the Pacific and  Northeast regions reported that companies may not provide raw data as  requested, or provide access to employees for OFCCP to interview,  which is part of the compliance review process. Using 2015 OFCCP  compliance evaluation data, we previously reported that close to 85  percent of contractor establishments across all sectors did not submit an  AAP within 30 days of being scheduled for an OFCCP compliance  evaluation, as required by OFCCP policy. Officials told us of the  potential need for a more flexible set of investigatory tools or sanctions,  such as subpoena power to speed up data-gathering or penalties for  delays in providing information, in order to obtain accurate and timely  information. In the case of incomplete data, OFCCP officials said one  option is to enter into an agreement with the contractor whereby the  contractor will gather the missing data, and OFCCP will monitor the  contractor’s efforts and review detailed records at a later date. However,  they said that such an agreement could give the contractor an opportunity  to modify the data in the contractor’s favor. Currently, OFCCP’s primary  sanction is the threat of debarment, which makes a company ineligible to  receive future federal contracts.

At the same time, OFCCP officials acknowledged there may additionally  be delays in their own review processes. In prior work, we’ve reported  concerns by contractors and industry groups about lengthy and expansive  OFCCP evaluations. However, OFCCP has not analyzed its data on  closed evaluations to assess the cause of delays, which would help  determine whether changes should be made to its internal processes or if  stronger sanctions to obtain information from contractors are needed.  Internal control standards state that management should identify,  analyze, and respond to risks related to achieving its objectives. Further,  it states that management should design appropriate mechanisms to  enforce its directives to achieve those objectives and address related  risks. Without more information on the root cause of the delays, these  delays may continue, straining resources and inhibiting OFCCP’s efforts  to identify potential discrimination. “An affirmative action program is a management tool designed to ensure equal  employment opportunity. A central premise underlying affirmative action is that,  absent discrimination, over time a contractor’s workforce, generally, will reflect  the gender, racial and ethnic profile of the labor pools from which the contractor  recruits and selects. Affirmative action programs contain a diagnostic component  which includes a number of quantitative analyses designed to evaluate the  composition of the workforce of the contractor and compare it to the composition  of the relevant labor pools. Affirmative action programs also include action- oriented programs. If women and minorities are not being employed at a rate to  be expected given their availability in the relevant labor pool, the contractor’s  affirmative action program includes specific practical steps designed to address  this underutilization.” “The placement goal-setting process . . . contemplates that contractors will,  where required, establish a single goal for all minorities. In the event of a  substantial disparity in the utilization of a particular minority group or in the  utilization of women or women of a particular minority group, a contractor may be  required to establish separate goals for those groups.”

According to OFCCP officials, a contractor may be required to establish  separate goals for particular minority groups as part of a compliance  review. We found, however, that OFCCP’s regulations do not require  federal contractors to disaggregate demographic data for the purpose of  establishing placement goals in their AAP. This may hinder their efforts to  implement effective AAPs, which are designed to assist the company in  achieving a workforce that reflects the gender, racial, and ethnic profile of  the labor pools from which the contractor recruits and selects. OFCCP  officials in headquarters and in the field said, based on their experience  evaluating companies’ compliance, it was not common for companies to  have placement goals disaggregated by race and ethnicity in their AAPs.  A diversity and inclusion officer we interviewed from one large technology  contractor noted that the requirement in the AAP to identify the need for  placement goals for minorities as a whole does not address  underrepresentation in certain minority groups. According to the officer,  the company does not count Asian workers in setting the company’s  diversity goals because Asians are well represented and the company  believes it should set a placement goal for groups for which the company  knows it needs to make progress. Citing comments received during  development of other regulations, OFCCP officials cautioned that an  analysis of utilization disaggregated by race/ethnicity may be more  challenging for smaller companies with fewer employees.

Further, looking at trends in diversity for minorities as a whole may not  assist a company’s affirmative action efforts to identify groups that need  particular outreach or support. Specifically, our analysis of workforce data  found differences in representation for Black and Hispanic workers in the  technology workforce compared to Asian workers. Under the current AAP  regulations, companies may opt not to detect and address  underrepresentation of particular minority groups since OFCCP does not  require placement goals disaggregated by race/ethnicity. While OFCCP  may be able to detect underrepresentation of particular minority groups  during its reviews, the office reviews only 2 percent of federal contractor  establishments each year. OFCCP officials said that they would need to  amend their regulations in order to require disaggregated race/ethnicity  information for placement goals on AAPs. The officials said  disaggregating race in placement goals could help an establishment  determine how to tailor outreach accordingly or better identify  impediments to its equal employment opportunity efforts. However, they  have not pursued this regulatory change because of competing priorities  on their regulatory agenda. OFCCP’s mission includes holding federal  contractors responsible for the legal requirements to take affirmative  action and not discriminate against protected groups. However, not  requiring contractors to set placement goals for each minority group may  hinder OFCCP’s ability to effectively achieve this mission.

OFCCP has not reviewed key aspects of its current approach to  evaluations  OFCCP officials report the agency intends to incorporate additional  information on gender, racial, and ethnic disparities by industry into its  compliance evaluation selection process, but we found the methodology  to determine the disparities may have weaknesses. We have previously  reported on the challenges OFCCP faces with its enforcement efforts,  and identified additional areas that may limit OFCCP’s enforcement of  federal contractors’ equal employment and affirmative action efforts. For  example, our 2016 report found that OFCCP’s weak compliance  evaluation selection process, reliance on voluntary compliance, and lack  of staff training create several challenges to its enforcement efforts. This  report found that because OFCCP was not able to identify which factors  are associated with risk of noncompliance, the agency does not have  reasonable assurance that it is focusing its efforts on those contractors at  greatest risk of not following nondiscrimination or affirmative action  requirements. OFCCP agreed with recommendations we made to  address these areas and detailed steps the agency would take. In  particular, to strengthen its compliance evaluation process to select  contractors at greatest risk of potential discrimination, the agency stated  that it planned to incorporate information on pay disparities and  employment disparities. OFCCP officials indicated this information  would be based on analysis of gender and race/ethnicity by industry using  ACS data and EEO-1 compensation data that was to be collected  beginning March 2018. However, in August 2017, the Office of  Management and Budget issued a memo suspending the pay-related  data collection aspects of the EEO-1 form. Despite this change, OFCCP  officials said they are exploring other options for focusing on  compensation disparities by industry, including through the use of ACS  data, administrative data, a previous study conducted by the Department  of Labor, as well as options proposed by contractors.

We also found OFCCP’s current methodology for identifying disparities by  industry with the ACS data may have some weaknesses that could affect  the accuracy of the outcomes. For example, its reliance on the broadest  industry level available may not sufficiently identify specific industries at  elevated risk. Further, the methodology includes future plans to conduct  the analysis for metropolitan areas. Given the importance of regional and  local labor markets for assessing affirmative action efforts, regional and  local analysis should also be completed before OFCCP incorporates this  analysis into its selection process. It is important that OFCCP use reliable  information in modifying its basic processes and setting priorities. For the  reasons cited earlier regarding the importance of using quality information  to make management decisions, it is important that OFCCP assess the  quality of the methods for its analysis of employment disparities among  industries. Without doing so, OFCCP may not accurately identify  industries at greatest risk of potential noncompliance with  nondiscrimination and affirmative action requirements so it can focus its  limited investigation resources most effectively.

Further, according to OFCCP officials, although the agency has made  slight changes to various thresholds and factors for its selection process,  the agency has not made any significant changes to the selection process  for about 10 years, and has made no changes to its establishment-based  approach since OFCCP was founded in 1965. While OFCCP currently  grounds its review of a contractor in a particular physical establishment,  OFCCP officials acknowledged the changing nature of a company’s work  can involve multiple locations and corresponding changes in the scope of  hiring and recruitment. Officials we interviewed from five of our eight  selected technology companies discussed their work spread across  locations, including the United States or overseas, and the related  challenges they face with OFCCP’s establishment-based approach to  reviews. One company representative said the AAP is not useful because  site specific plans do not connect to business decisions. However,  OFCCP has not reviewed the implications for the effectiveness of its  mission of continuing with its establishment-based approach to  conducting compliance evaluations.

In addition, OFCCP officials acknowledged their inability, in identifying  establishments for review, to consistently identify and include all  subcontractors to which OFCCP rules should apply. They said the agency  has not assessed the potential significance of any omissions of  subcontractors from the oversight process. Internal control standards  state that management should identify risks throughout the entity related  to achieving its defined objectives to form a basis for designing risk  responses, as well as the importance of periodically reviewing policies,  procedures and related control activities for continued relevance and  effectiveness in achieving the agency’s objectives. OFCCP officials said  they have informally discussed how to adjust their work based on how  work is performed in today’s economy—with virtual sites, workplace  flexibilities, and nontraditional forms of employment. However, due to  competing priorities, they have not conducted a formal review of these  key aspects of its current approach to selecting entities for review. They  acknowledged such a review would be useful. Without assessing its  current approach to its establishment-based reviews and identification of  all relevant subcontractors, OFCCP does not have reasonable assurance  that its approach can identify discrimination occurring within the  companies it oversees and may be missing opportunities to identify more  effective practices or adjust its methods to external changes.

While OFCCP has offered an option—the Functional Affirmative Action  Program (FAAP)—for companies to move away from establishment- based reviews and which may be more appropriate for some multi– establishment contractors, uptake has been low and the agency has not  conducted an evaluation of this program. Since 2002, OFCCP has  allowed companies to create FAAPs, with OFCCP approval, which are  based on a business function or unit that may exist at multiple  establishments. As of May 2017, 73 companies across all industries had  FAAPs in place. Further, some of the companies we interviewed were  unaware that the FAAP was an option or believed it was cumbersome to  establish given the complexity of their workforce. Asked why the FAAP  has not been more broadly adopted, OFCCP officials hypothesized it  could have to do with a requirement intended to ensure that companies  with FAAPs would be reviewed at least as often as others, but that may  result in these companies being reviewed more often than most.  Standards for internal control for government agencies state that  management should periodically review policies, procedures, and related  control activities for continued relevance and effectiveness in achieving  the entity’s objectives. Reviewing and refining the FAAP program could  help OFCCP improve its ability to achieve its objectives and may provide  broader insight for OFCCP’s overall enforcement approach.

Jobs in the high paying technology sector are projected to grow in coming  years. Female, Black, and Hispanic workers, however, comprised a  smaller proportion of technology workers compared to their  representation in the general workforce from 2005 through 2015, and  have also been less represented among technology workers inside the  technology sector than outside it. Both EEOC’s and OFCCP’s mission is  to combat discrimination and support equal employment opportunity for  U.S. workers; however, weaknesses in their processes impact the  effectiveness of their efforts. When conducting investigations, EEOC has  not been consistently capturing information on industry codes. This  impedes its ability to conduct industry sector analysis that could be used  to more effectively focus its limited enforcement resources and outreach  activities. Similarly, OFCCP faces delays in its compliance review process  but it has not analyzed its closed evaluations to understand the causes of  these delays and whether its processes need to be modified to reduce  them. In addition, as part of their affirmative action programs federal  contractors are only required to set placement goals for all minorities in  general. By not requiring contractors to disaggregate demographic data  for the purpose of establishing placement goals, OFCCP has limited  assurance that these contractors are setting goals that will address  potential underrepresentation in certain minority groups.

Further, OFCCP plans to incorporate information on disparities by  industry into its process for selecting establishments for compliance  evaluations, but has not fully assessed its planned methods. Without such  assessment, OFCCP may use a process that does not effectively identify  the industries at greatest risk of potential noncompliance with  nondiscrimination and affirmative action requirements. In addition, key  aspects of OFCCP’s approach to compliance reviews of contractors’  affirmative action efforts have not changed in over 50 years, whereas the  structure and locations of these companies’ work have changed. Finally,  although OFCCP has developed an alternative affirmative action program  for multi-establishment contractors, few contractors participate in this  program. Because OFCCP has not evaluated the program, it does not  have information to determine why there has not been greater uptake and  whether it provides a more effective alternative to an establishment-based  AAP.

We are making a total of six recommendations, including one to EEOC  and five to OFCCP. Specifically:

The Chair of the EEOC should develop a timeline to complete the  planned effort to clean IMS data for a one-year period and add  missing industry code data. (Recommendation 1)

The Director of OFCCP should analyze internal process data from  closed evaluations to better understand the cause of delays that occur  during compliance evaluations and make changes accordingly.  (Recommendation 2)

The Director of OFCCP should take steps toward requiring  contractors to disaggregate demographic data for the purpose of  setting placement goals in the AAP rather than setting a single goal  for all minorities, incorporating any appropriate accommodation for  company size. For example, OFCCP could provide guidance to  contractors to include more specific goals in their AAP or assess the  feasibility of amending their regulations to require them to do so.  (Recommendation 3)

The Director of OFCCP should assess the quality of the methods  used by OFCCP to incorporate consideration of disparities by industry  into its process for selecting contractor establishments for compliance  evaluation. It should use the results of this assessment in finalizing its  procedures for identifying contractor establishments at greatest risk of  noncompliance. (Recommendation 4)

The Director of OFCCP should evaluate the current approach used for  identifying entities for compliance review and determine whether  modifications are needed to reflect current workplace structures and  locations or to ensure that subcontractors are included.  (Recommendation 5)

The Director of OFCCP should evaluate the Functional Affirmative  Action Program to assess its usefulness as an effective alternative to  an establishment-based program, and determine what improvements,  if any, could be made to better encourage contractor participation.  (Recommendation 6)

We provided a draft of this report to the Departments of Labor (DOL),  Commerce, the Equal Employment Opportunity Commission (EEOC) and  the National Science Foundation (NSF).

We received written comments from DOL that are reproduced in appendix  V. In addition, DOL, Commerce, EEOC, and NSF provided technical  comments which we incorporated into the report as appropriate.

DOL agreed with 4 of the 5 recommendations we made to improve  oversight of federal contractors, and identified some steps it plans to take  to implement them. Specifically, the department agreed with our  recommendations to analyze internal process data to better understand  the cause of delays that occur during compliance evaluations, assess the  quality of methods used to incorporate consideration of disparities by  industry into the process to select contractors for review, and to evaluate  its current approach to identifying entities for review in light of changes in  workplace structures, as well as its Functional Affirmative Action  Program.

DOL stated that it appreciated, but neither agreed nor disagreed, with our  recommendation to take steps toward requiring contractors to  disaggregate demographic data for the purpose of setting placement  goals in the AAP rather than setting a single goal for all minorities. The  department said this would require a regulatory change with little  immediate benefit as contractors are already required to collect  demographic data on each employee and applicant, and must conduct in- depth analyses of their total employment processes to identify where  impediments to equal opportunity exist. While we acknowledge these  data collection requirements for federal contractors, we remain concerned  that without requiring contractors to also establish placement goals to  address any underrepresentation for specific minority groups, contractors  may not develop objectives or targets to make affirmative action efforts  work. We maintain, therefore, that DOL should take steps toward  requiring contractors to develop placement goals disaggregated by  race/ethnicity.

EEOC provided us a memo that it characterized as technical comments  on the draft report. In these comments, EEOC neither agreed nor  disagreed with our recommendation to develop a timeline to complete its  planned effort to clean IMS data for a one-year period, which would  include adding missing industry codes, but stated that it was taking some  actions to enhance these data. We continue to maintain a timeline should  be developed to complete this review, which is needed for the  commission to conduct industry sector analysis that could be used to  more effectively focus its limited resources and outreach activities. EEOC  also emphasized the importance of systemic investigations, noting that  while outreach may be somewhat useful in generating charges, individual  charges are unlikely to make a substantial impact on a systemic practice  affecting an entire employment sector. We maintain that the ability to  analyze IMS data by industry could help EEOC to focus its resource use,  including for systemic investigations. EEOC also noted staffing and  resource constraints as issues faced by the commission.

As agreed with your office, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies to the appropriate  congressional committees, the Secretary of Labor, the Chair of the Equal  Employment Opportunity Commission, the Secretary of Commerce, and  the Director of the National Science Foundation. In addition, the report will  be available at no charge on GAO’s website at http://www.gao.gov.

If you or your staff should have any questions about this report, please  contact me at (202) 512-7215 or brownbarnesc@gao.gov. Contact points  for our Offices of Congressional Relations and Public Affairs may be  found on the last page of this report. GAO staff who made key  contributions to this report are listed in appendix VI.

Appendix I: Objectives, Scope, and Methodology

Our two objectives were to: (1) identify the demographic trends in the  technology workforce over the past 10 years, and (2) assess the efforts  by the U.S. Equal Employment Opportunity Commission (EEOC) and the  Department of Labor’s Office of Federal Contract Compliance Programs  (OFCCP) to oversee technology companies and technology contractors’  compliance with equal employment opportunity and affirmative action  requirements. This appendix provides details of the data sources used to  answer these questions, the analyses we conducted, and any limitations  we encountered.

Definition of Technology Sector and Technology Occupations

There is no commonly accepted definition of the technology sector or  technology-oriented occupations. To arrive at our definition for the  technology sector, we identified industries with the highest concentration  of technology-oriented occupations, a similar approach to what other  federal agencies have used recently to analyze trends within this sector.  To identify technology-oriented occupations, we reviewed relevant  research and interviewed researchers and other individuals  knowledgeable about the technology sector. Based on this research, we  defined technology-oriented occupations to include all computer,  engineering and mathematical occupations, including managers. We  selected our occupations using Bureau of Labor Statistics (BLS) Standard  Occupational Classification (SOC) System codes, and crosswalked those  occupations to the corresponding U.S. Census Bureau occupation codes  to conduct our analysis. (For a complete list of the occupations we  included as technology occupations, see appendix II).

We defined the technology sector as a group of industries with the  highest concentration of technology workers. Using data from the  American Community Survey, an ongoing national survey conducted by  the U.S. Census Bureau that collects information from a sample of  households, we identified the 15 industries with the highest concentration  of technology workers. For this analysis, we used Census industry codes  since we used this dataset for many of our analyses. The concentration of  technology workers in these industries ranged from a high of 62.2 percent  in the computer systems design and related services industry to a low of  19.33 percent in the wired telecommunications carriers industry (see table  3). Companies in the technology sector also employ non-technical  workers, such as sales people.

We cross-walked the industries we identified in the American Community  Survey with corresponding industry codes from the North American  Industry Classification System (NAICS), which is the standard used by  federal statistical agencies in classifying business establishments. The  other data sets used in this review use NAICS codes to identify industry.  The NAICS system has six levels of industry classification, with the  smallest level (2-digit code) providing the most general industry  classification, and the largest (6-digit) providing the most specific  classification. In total, we identified 55 6-digit NAICS industry codes that  comprise the technology sector using this method. (See appendix III for a  list of the 6-digit NAICS codes and industry names that correspond to the  Census industries we identified.)

We compared our list of industries to those included in the 2016 reports  by EEOC and the BLS on the technology sector. While each report  includes a somewhat different set of industries depending on the authors’  particular definition of technology occupations, most of the 15 industries  we selected overlap with industries selected in these other reviews.  Stemming from their particular focus, these reports included some  additional industries and/or occupations excluded from our analysis, such  as those in the life sciences. We also compared our findings on the  demographic trends in the technology workforce to 2016 EEOC and  Census Bureau reports that reviewed diversity in the technology sector.  Despite the definitional and methodological variations, the demographic  trends found in these other reports were generally comparable to our  findings.

To determine the demographic trends in the technology workforce over  the past decade, we analyzed quantitative data on technology workers  within and outside the technology sector from 2005 through 2015 from the  Census Bureau’s Public Use Microdata Sample of the American  Community Survey (ACS) for the years 2005, 2007, 2009, 2011, 2013,  and 2015. ACS is an ongoing national survey that collects information  from a sample of households. We analyzed trend data for gender, race,  and ethnicity, and median salary by occupation and sector, and analyzed  point-in-time data on educational background by occupation.

We analyzed the percentage of technology workers who earned  bachelor’s degrees in computer, engineering, mathematics, and  technology fields. For median salary, we analyzed data for workers who  were employed full-time, which included those who, over the past 12  months, reported usually working 35 hours or more per week and 50  weeks or more per year, and those with wages greater than zero.

To account for the sample representation and design used in the ACS,  we used the person weight present in the ACS data. We used the  successive difference replication method to estimate the standard errors  around any population estimate. For each comparison, we tested the  statistical significance of the difference for men and women and for  specific racial and ethnic groups at the p-value <0.05 level. In addition, we  tested the statistical significance of the change between 2005 and 2015  for each gender and racial/ethnic group.

For race categories using ACS data in this report, we included only non- Hispanic members of White, Black, Asian, and Other categories. For the  Asian category, we included Asian American, Native Hawaiian or Other  Pacific Islander. The Hispanic category incorporated Hispanics of all  races. Our analysis included American Indian or Alaskan Native, and Two  or More Races, in the category reported as “Other.”

We assessed the reliability of the ACS generally and of data elements  that were critical to our analyses and determined that they were  sufficiently reliable for our analyses. Specifically, we reviewed  documentation on the general design and methods of the ACS and on the  specific elements of the ACS data that were used in our analysis. We  interviewed Census Bureau officials knowledgeable about the ACS data  and completed our own electronic data testing to assess the accuracy  and completeness of the data used in our analyses.

Employer Information Report (EEO-1) Data

To determine workforce trends in companies within the technology sector  and at leading information technology companies, we analyzed data from  EEOC’s Employer Information Reports (EEO-1) for the years 2007, 2011,  and 2015. We report EEO-1 data starting in 2007 because EEOC made  significant changes to its requirements related to the reporting of EEO-1  data over time. For example, beginning in 2007, EEOC changed its  requirements related to the reporting of data on managers and changed  its practices for collecting certain racial/ethnicity information. EEO-1  reports contain firm-level data that is annually submitted to EEOC,  generally by private-sector firms with at least 100 employees or federal  contractors with at least 50 employees that have a contract, subcontract  or purchase order amounting to $50,000 or more. Companies that fit the  above criteria submit separate EEO-1 reports for their headquarters as  well as each establishment facility. EEOC requires employers to use the  North American Industry Classification System (NAICS) to classify their  industry.

To identify trends using EEO-1 data for workers, we analyzed data for  companies with the NAICS codes we initially identified as technology  industries. We selected the leading information technology companies  using Standard & Poor’s (S&P) 500 Information Technology Index list,  which identifies the largest public information technology companies at a  given time. In October 2016, this list consisted of 67 companies in the  world that have stocks trading with the United States, and we analyzed  EEO-1 data from 65 of these companies. For both analyses, we  analyzed EEO-1 data from all job categories by gender, race and ethnicity, and industry sectors. For job categories, the EEO-1 form  collects data on 10 major job categories including 1) Executives, Senior  Level Officials and Managers; 2) First/Mid-Level Officials and Managers;  3) Professionals; 4) Technicians; 5) Sales Workers; 6) Administrative  Support Workers; 7) Craft Workers; 8) Operatives; 9) Laborers and  Helpers; and 10) Service Workers. In our analysis, “all other jobs”  combines sales workers, administrative support workers, craft workers,  operatives, laborers and helpers, and service workers. We used the  race/ethnicity categories used by the EEOC as follows: White, Black or  African American, Asian (including Native Hawaiian or Other Pacific  Islander), Hispanic or Latino, and “Two or more Races” (including  American Indian or Alaska Native).

We assessed the reliability of the EEO-1 data and determined that  despite limitations, they were sufficiently reliable for our analyses. To  determine the reliability of the EEO-1 data that we received from EEOC,  we interviewed knowledgeable EEOC officials, reviewed relevant  documents provided by agency officials and obtained on its website, and  performed manual data testing for missing variables.

Integrated Postsecondary Education Data System (IPEDS)

For our analysis of technology degree earners, we used degree  completion data tabulated by the National Science Foundation from the  National Center for Education Statistics’ Integrated Postsecondary  Education Data System (IPEDS) for the year 2014. Using a variety of  sources, such as academic research and interviews with representatives  from academia, we defined technology-related fields as degree programs  in computer science, engineering, and mathematics. We analyzed  IPEDS data by race and gender and who had obtained a bachelor’s or  master’s degree in technology-related fields. We determined that the  potential external candidates for technology positions generally had  obtained either a bachelor’s or a master’s degree in a technology-related field. We used the race/ethnicity categories used by IPEDS as follows:  White, Black, Asian (including Pacific Islander), Hispanic, and Multiracial  or other (which includes American Indian or Alaska Native, Other or  Unknown Race, and Two or more Races, i.e. respondents who selected  one or more racial designations). Race and ethnicity breakouts are for  U.S. citizens and permanent residents only, and thus do not include data  on temporary residents. The analysis by gender includes temporary  residents.

To determine the reliability of IPEDs data, we reviewed relevant  documents obtained on the National Center for Education Statistics  website, such as annual methodology reports and the handbook of NCES  survey methods. We determined that data from IPEDs were sufficiently  reliable for our purposes.

To identify how EEOC and OFCCP have overseen technology  companies’ compliance with federal equal opportunity and affirmative  action requirements, we reviewed relevant federal statutes and  regulations, EEOC and OFCCP policies, strategic planning documents,  and operational manuals. We interviewed EEOC and OFCCP officials in  headquarters, and in two regional locations selected based on the large  proportion of technology companies in those areas. At EEOC, we met  with officials from the San Francisco and New York district offices. At  OFCCP, we met with officials from the Pacific and Northeast regional  offices.

To explore charges of discrimination filed with the EEOC against  technology companies, we planned to analyze data from the EEOC  Integrated Mission System (IMS), which contains records on EEOC  charges and enforcement activities. However, since industry code is not a  mandatory field for investigators to complete, roughly half the entries did  not have an industry code. Therefore, we could not reliably identify  technology companies that have faced charges or enforcement. We  attempted to match information we had developed on federal technology  contractors with charges filed in the IMS database. Depending on the  matching method we used, this yielded very different results and we  determined this was not a sufficiently reliable method. Further, any  matching method we used would have excluded technology companies  that did not hold a federal contract.

To obtain information on evaluations of technology contractors completed  by OFCCP and complaints received against technology contractors, we  took a two-step approach. First, using the Federal Procurement Data  System–Next Generation (FPDS-NG), we developed a list of company  establishments and their subsidiaries that received federal contract  obligations in fiscal years 2011-2015 under any of the 55 NAICS codes  we included above as technology industries. We selected only company  establishments that received 50 percent or more of their total federal  contract obligations under these NAICS codes. Each establishment was  counted only once regardless of how many federal contracts it received  during the time period. Using this method, we identified 43,448  establishments in our pool of “technology contractors.” To identify  subsidiaries, which are also subject to OFCCP requirements and  evaluations, we identified any other establishments that shared the global  vendor code with the contractors we identified, regardless of their NAICS  code. This yielded 2,116 additional contractors. Second, we matched the  names (removing suffixes) of the technology contractors and their  subsidiaries that we identified in FPDS-NG against OFCCP’s data on  their evaluations of contractors to identify the evaluations of technology  contractors that OFCCP opened and completed from fiscal year 2011  through fiscal year 2016. We conducted a similar matching exercise to  identify the complaints OFCCP received against technology companies.  In addition, we identified which of the leading technology companies had  completed evaluations between fiscal year 2011 through 2016.

We obtained information during interviews with researchers, and  representatives of workforce and industry organizations and associations.  In addition, we interviewed diversity and compliance representatives of eight of the leading information technology companies located in the San  Francisco Bay area which were also federal contractors to discuss their  efforts to increase diversity and to gain their perspectives on the federal  role in overseeing compliance with nondiscrimination laws. These  companies were:

Hewlett Packard Enterprise Company  Intuit Inc.

This is the list of technology occupations that we used in our analyses.  We selected our occupations using Bureau of Labor Statistics (BLS)  Standard Occupational Classification (SOC) System codes, and cross- walked those occupations to the corresponding U.S. Census Bureau  occupation codes.

Appendix III: North American Industry Classification System (NAICS) Codes Identified as Technology-Related Industries

This is the list of the 55 6-digit North American Industry Classification  System (NAICS) codes we identified as technology-related industries. To  develop this list, we identified the 15 industries with the highest  concentration of technology workers using U.S. Census Bureau industry  codes and then used the U.S. Census Bureau’s 2012 Industry Code List  for Household Surveys to crosswalk the Census codes with NAICS  codes.

Appendix V: Comments from the Department of Labor

Appendix VI: GAO Contact and Staff Acknowledgments

In addition to the contact named above, Betty Ward-Zukerman (Assistant  Director), Kate Blumenreich (Analyst-in-Charge), Sheranda Campbell,  Julianne Hartmann Cutts, Clarita Mrena, Moon Parks, Alexandra Rouse,  and John Yee made significant contributions to all phases of the work.  Also contributing to this report were Rachel Beers, James Bennett,  Hedieh Fusfield, Julia Kennon, Jean McSween, Jessica Orr, Dae Park,  James Rebbe, Almeta Spencer, and Alexandra Squitieri.