Oracle in the Hot Seat over Gender Pay Discrimination (Again)

San Mateo, CA On December 18, the California Superior Court refused to dismiss a Complaint alleging that Oracle America, Inc. systematically paid women less than men for comparable work. The California labor lawsuit, describes a pattern all-too-familiar from other gender discrimination lawsuits against Silicon Valley tech giants, including Google, Uber and HP as well as Oracle.

The latest decision does not resolve the workers’ claims under the California Equal Pay Act, but it sheds light on the importance of statistical evidence. Data plays an increasingly important role in these “pattern or practice” class action lawsuits. But statistical evidence of pay disparities, by itself, does not prove discrimination.

Gender Discrimination in Pay

Jewett v. Oracle alleges that Oracle discriminated against female employees by systematically paying them less than it paid male employees doing substantially equal or similar work in similar situations without lawful justification. The lawsuit originally related to claims advanced by Rong Jewett and Sophy Wang, applications engineers and Xian Murray, a systems engineer.

In 2020, the Superior Court certified Jewett as a class action, covering more than 4,000 similarly situated women who worked for Oracle between 2012 and 2016. Estimates of potential damages in the lawsuit have ranged as high as $364 million.

California Equal Pay Act

The California Equal Pay Act prohibits gender pay disparities for equal work, when the work, qualifications required and working conditions are substantially similar. In 2016. California amended the law to look past “equal work” to “substantially similar work.” The latter requires a wider view of a composite of skill, effort, and responsibility, and conditions. In addition, the amendment made it more difficult for an employer to justify pay disparities on the basis of a pre-existing seniority or merit system. These pre-existing systems trapped many women in a historical cycle of pay discrimination. The amendment requires affirmative evidence that the disparity is job-related with respect to the position in question, and is consistent with a business necessity.

Is statistical evidence of disparity enough to show discrimination?

Between 2012 and 2016, Oracle maintained a centrally-determined and uniformly applied set of policies and practices under which employees’ initial pay and pay raises were determined. The evidence offered by the plaintiffs in the Complaint relies heavily on a compliance audit of Oracle’s headquarters. The U.S. Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP) found “systemic discrimination against women” and “gross disparities in pay” at Oracle, even after controlling for job title, full-time status, exempt status, global career level, job specialty, prior work experience and company tenure.

The audit concluded that Oracle systemically discriminated against qualified female employees in its Information Technology, Product Development, and Support lines of business by paying them less than male employees in similar roles. The audit, however, does not specifically refer to any of the specific plaintiffs in the class action Jewett lawsuit.

In September 2020, Administrative Law Judge Richard Clark ruled that the audit offered evidence of a pay disparity, but not intentional compensation discrimination. The ALJ concluded the statistical evidence offered did not support an inference that Oracle was discriminating, or that there were disparities to be explained by either a pattern or practice of discrimination or a policy or practice of relying on prior pay.

In other words, statistical evidence of disparity was not, by itself, evidence of discrimination. The decision was widely seen as a major victory for employers in gender pay discrimination lawsuits, and was the basis for Oracle’s motion to dismiss in Jewett.

Echoes of Title VII “Disparate Impact” lawsuits

The dilemma faced by the plaintiffs in their effort to prove discrimination on the basis of a pattern of pay differences is reminiscent of the challenges faced by plaintiffs who bring employment discrimination lawsuits under Title VII of the federal Civil Rights Act of 1964. In some circumstances a plaintiff may argue that a rule or practice that is neutral on its face is discriminatory in impact.

A classic example might be a requirement that firefighters be at least six feet tall. The rule is neutral on its face, as Oracle’s pay policies and practices appear to have been. Nonetheless, because statistically speaking far fewer women than men are six feet tall or taller, the rule has a disparate impact on women, who are a legally protected class under Title VII (women) than it does on men.

The argument made by the class of women in Jewett was very similar: the application of Oracle’s pay practices and policies had a disparate impact on female employees, who are among the workers the California Equal Pay Act is intended to protect. Both Title VII “disparate impact” lawsuits and California labor lawsuits under the amended Equal Pay Act depend heavily on statistical analysis, at least in the initial stages.

The “extra” factor

Something more is clearly required, however, to support an allegation of discrimination under the Equal Pay Act. In Jewett, Judge V. Raymond Swope quoted from the Second Circuit case Lavin-McEleney v. Marist College: "'We hold that statistical evidence of a gender-based salary disparity among comparable professors properly contributed to plaintiff's case in conjunction with her identification of a specific male comparator.'" It looks like an invitation to the Jewett plaintiffs to provide specific comparators at trial.