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The summer of 2020 saw an unprecedented number of corporate leaders publicly acknowledge and condemn institutional and structural racism, as part of a national reckoning on racial injustice. Issued in response to widespread protests against police violence, these statements called for an end to racial disparities across all systems, including health care, education, housing, criminal justice, and employment. This movement emerged at a moment when people of color were more likely to be working on the dangerous front lines of a pandemic, for low wages and with scant protective gear, while higher-wage earners sheltered at home.
Businesses claiming to support racial equity are, in reality, committing to change facts such as these: Black workers are more likely to work in low-wage industries with high turnover, earn less than their white counterparts, and report a median net worth of one-tenth that of whites. This fixed inequality holds even for Black college graduates, whose households report a lower net worth than those headed by white high school dropouts. The racial wealth gap is so entrenched that by some estimates, at the current growth rate, it would take Black families 228 years to amass the wealth that white families currently hold.1
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Racial equity describes an alternate reality, in which race no longer predicts, in a statistical sense, how one fares. While most companies recognize that statements alone will not bring their workplaces — or the nation — closer to that reality, few are confident in their next steps. Fortunately, most employers already have what they need to guide their course: data. Over the past decade, data analytics has been used to improve the quality of products and services, improve efficiency in production and distribution, and fundamentally shape business models. Likewise, a different approach to analyzing your workforce data can help identify measurable and meaningful steps toward a more equitable workplace.
Why We Need a Data-Driven Racial Equity Framework
Racial equity strategies must be systemic, race-explicit, and outcome-oriented if they are to succeed.
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1. D. Asante-Mohammad, C. Collins, J. Hoxie, et al., “The Ever-Growing Gap: Without Change, African-American and Latino Families Won’t Match White Wealth for Centuries” (Washington, D.C.: Institute for Policy Studies and CFED, 2016).
2. “Race-Explicit Strategies for Workforce Equity in Healthcare and IT,” PDF file (New York: Race Forward, June 15, 2017), www.raceforward.org.
3. E. Kennedy, “Desert in the Deluge: Using Data to Drive Racial Equity,” Catholic University Law Review 69, no. 1 (winter 2020): 23-52.
4. T. Wang, “Why Big Data Needs Thick Data,” Medium, Jan. 20, 2016, https://medium.com.
5. P.T. Kim, “Data-Driven Discrimination at Work,” William and Mary Law Review 58, no. 3 (February 2017): 857-936.
6. T.Z. Zarsky, “Understanding Discrimination in the Scored Society,” Washington Law Review 89, no. 4 (December 2014): 1375-1412.