By Roberta Rincón, Ph.D., Manager of Research, SWE
A recent article in IEEE Spectrum, We Can’t Tell if Tech is Doing Better on Diversity Because the Data Stinks by Tekla S. Perry, presented an argument for the need for tech companies to collect and release more statistics to show that they are serious about increasing diversity. The article states that recent diversity data released by companies such as Google, Apple, and Facebook are a great start, but they are “only a superficial layer.” To really understand how diverse an organization is, you need to do more than just count people. For example, knowing the gender and racial breakdown of employees at an organization is great, but knowing the gender and racial breakdown of engineers versus retail staff can give more insight into a company’s attentiveness to increasing diversity across all sectors. Knowing the diversity of new hires is helpful, but knowing more about retention and attrition, promotions, and salaries can give a company a more in-depth understanding of the success of their diversity efforts. Such data is necessary to develop impactful diversity goals and metrics to measure progress.
Diversity-serving organizations like SWE have indicated a need for more disaggregated data to better understand the success of underrepresented groups in engineering. Even within engineering education, where a great deal of data is easily accessible, there are limitations. For example, SWE noted the need to better support women who begin their college education at a two-year college and intend to transfer to a four-year university to complete their engineering degrees. However, while some high-level data on transfer students is available, disaggregated data on the gender and race of transfer students in engineering is not easily accessible. How can organizations effectively work to improve the diversity in engineering if they do not know the current state of transfer success for women and minority engineering students? To address this gap in data availability, SWE recently conducted an exploratory study of community college transfers in engineering and computer science in Texas.
To help universities, companies, and policy makers understand the current landscape and develop strong plans and efficient supports, policies, and processes to increase diversity in STEM fields, more detailed data must be collected and reported. To make change happen, we need access to the data to determine where obstacles exist that hinder progress towards our diversity goals.