Diversity in the Technology Sector: Federal Agencies Could Improve Oversight of Equal Employment Opportunity Requirements
Released: 2017-11-30T00:00:00

Letter

Background

Technology Sector

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.

Conclusions

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.

Recommendations for Executive Action

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)

Agency Comments and Our Evaluation

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.

American Community Survey (ACS) Data

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.

Analysis of EEOC and OFCCP Oversight

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:

Cisco Systems, Inc.

Facebook, Inc.

Google Inc.

Hewlett Packard Enterprise Company Intuit Inc.

Oracle America, Inc.

Appendix II: Technology Occupations

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

GAO Contact

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.