Workplace Diversity and Financial Performance
In June 2023, the Supreme Court ended race-conscious admissions to colleges and universities across the U.S. (Totenberg, 2023). This ruling did not impact employers’ obligation to provide a fair and equitable workplace to their employees. However, within the context of the Court’s decision, questions have been raised around the necessity of corporate DEI programs. For example, in July 2023, Republican Attorneys General from 13 states sent letters to Fortune 100 companies, urging their restriction of corporate DEI policies.
Numerous studies have supported an assertion that companies do benefit from more racial, ethnic, and gender diversity. Diversity has been linked with cultivating more creative and innovative workplaces. Individuals from different backgrounds with varying expertise, lived experience, and knowledge allow companies to access a wider range of skills and consider risk differently when addressing complex challenges. Previous studies have strongly indicated workforce diversity to be beneficial for company performance (Greenfield, 2019; Hunt et al., 2018). For example, The Wall Street Journal found that the top 20 companies with the most diverse employee populations in the S&P 500 index had a higher operating profit margin and average annual total return on shares compared to the 20 least diverse companies (Holger, 2019). Yet, female, Black, Indigenous, and people of color (BIPOC) individuals are consistently underrepresented in leadership roles (Krivkovich et al., 2022).
Until recently, however, it had not been possible to conduct an empirical and statistically significant analysis of the relationship between corporate diversity and financial performance. Demographic information is collected by the U.S. Equal Employment Opportunity Commission (EEOC) through Equal Employment Opportunity Component 1 (EEO-1) data forms, which cover race/ethnicity, sex, and job categories. Historically, this has been a non-public form.
However, in April 2023, the U.S. Department of Labor (DOL) released EEO-1 forms from 2016 to 2020 as the result of a FOIA request by the Center for Investigative Reporting. Diversity research provider DiversIQ has also compiled all voluntarily published EEO-1 forms. Across the DOL and DiversIQ EEO-1 datasets, our sample comprised 4,970 EEO-1 forms from 1,641 unique companies collected between 2016 and 2022.
The Data & Methods
Our analysis focused on the EEO-1 forms available from 2016 through 2022 (n = 4,970) across 1,641 companies. From the EEO-1 forms, workforce diversity variables were identified. For each company present in the EEO-1 dataset, financial data for the appropriate year were obtained from the financial database provider Refinitiv and matched against the dataset for that year. For example, 2019 EEO-1 data were matched against 2019 financial information; a five-year performance metric for a 2019 EEO-1 form looks at the performance five years prior to 2019. Only partial financial data were available for some companies. Further details on the sample size can be found in the report’s appendix.
The variables used in this analysis are included below in Table 1.
Relationships between workforce diversity and financial performance were then assessed using ordinary least squares (OLS) linear regression. OLS regression is a statistical analysis used to assess the relationship between two variables (e.g., as the percentage of BIPOC management increases, how does the return on assets change?). OLS regression can provide information on both the direction (positive or negative) and strength of the relationship. The results of this method can be assessed for statistical significance using p-values. The p-value is used to verify hypotheses, where a smaller p-value indicates a lower likelihood of a value occurring by chance. Traditionally, p < 0.05 indicates a value is unlikely to occur by chance and is therefore statistically significant, which is what the following analyses use.
Limitations of the study should be considered as results are reviewed. Firstly, linear regression was limited to smaller sample sizes in the analysis of smaller sectors such as Real Estate, Consumer Staples, and Communication Services. Additionally, these data spanned multiple years and a complex economic environment; changes in financial performance may also be attributed to other factors beyond workforce diversity. The longitudinal analysis attempted to control for these externalities, but aggregate results do not.
It is important to note that the EEO-1 report’s gender and race definitions are also insufficient to capture the bias and discrimination that may impact a company’s workplace. There are many dimensions of diversity; this report pulled from the existing data set, which captured only binary gender and government-defined and simplified categorization of people’s races and ethnicities. The available research does not include a wide range of classes known to need legal protection from discrimination – such as sexual orientation, gender identity, pregnancy status, veteran status, or religion. They also do not allow for complexity within the listed definitions; for example, within the Asian category, there are significant cultural nuances and differences. Within race, within Black, there are significant differences in experience by skin tone (Peck, 2023).
Compared to general population levels obtained from the 2021 American Community Survey, Asian, Black, and male individuals are overrepresented in our dataset while White, Latine, Indigenous, two or more races, and female individuals are underrepresented (Figure 1).
Key Findings
The analysis of 1,641 U.S.-based and publicly traded companies between 2016 and 2022 strongly indicates that a diversity benefit exists and that companies are incentivized to be attentive and proactive in capturing it. The key findings of this research are as follows:
There is a diversity benefit. Across the full data set, higher percentages of BIPOC (non-White) management are positively correlated with increases in enterprise value growth rate, free cash flow per share, income after tax, long-term growth mean, 10-year price change, mean return on equity (ROE), return on invested capital (ROIC), and 10-year total revenue compound annual growth rate (CAGR).
All statistically significant relationships between BIPOC management and financial performance were positive in the Communication Services, Consumer Discretionary, Consumer Staples, Financials, Health Care, and Information Technology sectors.
Companies with large market capitalizations displayed a clear and statistically significant positive relationship with diverse management. This may be because they are more willing to dedicate resources to equity and inclusion programs.
The Energy, Materials, and Real Estate sectors scored lower than their peers across almost all criteria related to their racial justice management and strategy. These sectors also did not realize a performance benefit from increased manager diversity.
Workforce diversity increased sharply in 2020. Brokers’ projections for companies with diverse managers also shifted to be more positive during this time.
Analysis is constrained by the lack of reporting by companies on their hiring, promotion, and retention rates.
Investors are incentivized to advocate for corporate disclosure of quantitative data of diversity, equity, and inclusion (DEI) initiatives.
