By Roberta Rincón, Ph.D., Manager of Research, SWE
I recently read the news that Uber had settled the class action discrimination lawsuit that three software engineers had filed in October 2017. The allegation centered on Uber’s use of “stack rankings” to evaluate employees and determine promotions, ranking them from “worst to best.” The suit also claimed that Uber set employee pay based on past compensation, and that the use of such a system places women and people of color at a disadvantage because they “receive, on average, lower rankings despite equal or better performance.” Also, basing salary on past compensation can keep those with lower starting salaries from ever reaching parity with their white male peers – hence the reason some states are banning this practice.
In addition to a monetary settlement of $10 million, Uber agreed to make systemic changes to the way it evaluates employees for compensation, reviews, and promotions. The company also agreed to regularly report on their workforce demographics. The question is, is this enough? Aside from the immediate monetary compensation to affected employees, will the new assessment process that Uber has agreed to develop benefit Uber employees by addressing the systemic gender and racial biases that exist? Reporting workforce demographics will help, if those reports are detailed enough to show diversity statistics within specific areas of the company, specifically among the engineering staff and management levels, and if the data is utilized to mitigate biases within workplace processes.
One important observation from the SWE literature review authors’ review of 2017 literature is the need for more research on the culture of engineering and STEM, as “…the experience of mistreatment is not the same thing as the perception that it is part of a larger systemic problem.” Companies will not change on their own, not without more individuals coming forward and speaking out, and not without more data to back up their claims.
Research studies have shown that systemic biases are prevalent in many workplaces, impacting performance evaluations and female advancement into leadership positions, reducing the representation of women over time. SWE’s own research on gender and racial bias in engineering found that female engineers and engineers of color were more likely to report getting paid less, receiving less honest feedback on performance, and having less access to networking and advancement opportunities. For women in engineering, the pay gap is real. Though smaller than the 20% gender pay gap that currently exists in the U.S., women in engineering are earning as much as 14% less than their male counterparts. To address these issues, companies must work to understand what the situation looks like within their own organizations. Collecting and reporting data on workforce demographics will indicate whether problems exist, but addressing those problems usually requires a level of social accountability.
For organizations that are less willing to address issues of bias in the workplace, external pressure can lead to change. Under the Obama Administration, the Equal Employment Opportunity Commission proposed to collect summary pay data by race, ethnicity, and sex from employers in 2016, but the Office of Management and Budget (OMB) stopped its implementation in 2017, effectively preventing the federal government from providing the transparency necessary to shed light on gender and racial pay gaps. However, a lawsuit filed in November 2017 against the OMB in response to this decision may change this, particularly in light of the effectiveness of the #MeToo and #TimesUp movements in drawing public scrutiny to the issue. Those who have come forward to share their experiences have already seen positive movement in some sectors. For example, in academia there are efforts underway to address problems with sexual harassment in the workplace through financial incentives/disincentives and new recognition programs to encourage diversity and inclusion.
Requiring employers to make their demographic and pay data more transparent is necessary if we want them to address existing biases in processes that continue to hamper fair and equitable treatment in the workplace. Incentivizing fair and equitable treatment, particularly through financial means, may also encourage more organizations to consider ways to make their workplace climate and culture more inclusive and welcoming. Continuing to make our voices heard, as the women in the Uber case have done, will help turn the tide.