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Shift Your DEI By The Numbers
Collect DEI data consistently and comprehensively to bring clarity and accountability to DEI initiatives and achieve lasting results.
Your DEI By The Numbers
Collect DEI data consistently and comprehensively to bring clarity and accountability to DEI initiatives and achieve lasting results.
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Uncover actionable steps to foster a culture of inclusion and belonging, with the ultimate goal of retaining and promoting women of color in technology roles.

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[1] https://justcapital.com/reports/share-of-largest-us-companies-disclosing-race-and-ethnicity-data-rises/

More than Half of the Largest Companies in the US Publicly Share Some Workforce Diversity Data, and a Small but Growing Number Share Intersectional Data
A report by JUST Capital[1] found that as of September 2021, 55 percent of the companies in the Russell 1000 disclose at least some data on the race/ethnicity composition of their workforce. Publicly disclosing the demographic characteristics of a workplace enable better benchmarking, goal setting, and accountability for DEI goals. For advocates of women of color in tech, intersectional data is the gold standard. Only 11 percent of Russell 1000 companies share intersectional data on the race/ethnicity and gender composition of their workforce. While this figure remains low, the good news is that it has increased from three percent in November 2019.

Why It Matters

[8] Opportunity@Work. (2020). Navigating with the STARs. Opportunity@Work.

[9] Employment and Social Development Canada. (2019). Women and the Workplace: How employers can advance equality and diversity. Employment and Social Development Canada.

How do you know what percentage of tech jobs on your team or in your enterprise should be held by women of color? Without looking closely at how many women of color are in the talent pool for those jobs, it’s difficult to justify a target. How do you know if your efforts to expand your talent attraction pipeline result in a more diverse talent pool? Without keeping a pulse on the diversity of your workforce over time, it is impossible to measure progress. Connecting diversity, equity, and inclusion (DEI) efforts to measurable metrics is crucial for evaluating progress and achieving meaningful change. Without such metrics, even the most well-intentioned efforts can fall short.

[8] Opportunity@Work. (2020). Navigating with the STARs. Opportunity@Work.

[9] Employment and Social Development Canada. (2019). Women and the Workplace: How employers can advance equality and diversity. Employment and Social Development Canada.

Fortunately, data collection and analysis are foundational in nearly every business discipline. Successful executives, HR professionals, and team leaders already know how to use objective data to prioritize decisions and to connect actions and results. Further, organizations are already in the habit of collecting DEI data. The Equal Employment Opportunity Commission (EEOC) requires companies with more than 100 employees to submit demographic workforce data, including data on race/ethnicity and gender. The human resources information systems (HRIS) used by most companies make reviewing these characteristics by location, team, or job level straightforward.

For organizations serious about increasing the representation of women of color in tech, the right data, used the right way, will be instrumental for delivering on that commitment. The following sections describe what the right data encompasses and how to collect and analyze it, including by setting internal organizational baselines, measuring against external benchmarks, and tracking DEI metrics between different stages of talent acquisition and talent management to unearth barriers.

[1] https://justcapital.com/reports/share-of-largest-us-companies-disclosing-race-and-ethnicity-data-rises/

More than Half of the Largest Companies in the US Publicly Share Some Workforce Diversity Data, and a Small but Growing Number Share Intersectional Data
A report by JUST Capital[1] found that as of September 2021, 55 percent of the companies in the Russell 1000 disclose at least some data on the race/ethnicity composition of their workforce. Publicly disclosing the demographic characteristics of a workplace enable better benchmarking, goal setting, and accountability for DEI goals. For advocates of women of color in tech, intersectional data is the gold standard. Only 11 percent of Russell 1000 companies share intersectional data on the race/ethnicity and gender composition of their workforce. While this figure remains low, the good news is that it has increased from three percent in November 2019.

Action Steps

These action steps can help employers foster a culture of inclusion and belonging, which are critically important to retaining and promoting women of color in technology roles.  

Disclose EEO-1 Reports publicly. EEO-1 Reports detail a company’s workforce composition according to 14 intersectional demographic groups (race/ethnicity and gender) and 10 job categories (or levels, including senior leadership, professionals, technicians, service workers, and others). Companies with more than 100 employees are required to file EEO-1 Reports with the EEOC, and companies can voluntarily release these filings publicly. EEO-1 Reports provide useful baseline data for those focused on women of color in tech. While the EEO-1 Report does not break down the demographic composition of tech jobs within a company (more on this below), it can be helpful to refer to the percent of women of color in leadership, the percent of women of color in professional-level jobs, and the gap between those figures. The template for the EEO-1 Report that all companies with over 100 employees are already required to file is reproduced below for reference:

Supplement EEO-1 Report disclosure with an annual update on women of color in tech jobs across the company. Baseline data on women of color in tech can be difficult to publish because tech jobs cut across companies and job categories. Companies in all sectors have tech jobs, for example Computer Programmers at software publishing firms, Cybersecurity Specialists at online retailers, and Database Administrators at banks. Tech jobs also show up in many EEO-1 job categories, for example Chief Technology Officers are classified as executives, Software Developers as professionals, and Computer Support Techs as technicians. For this reason, companies may consider a supplemental annual update on the composition of their tech workforce.

[2] https://equalitydata.herokuapp.com/

Salesforce Tech Workforce Readout Salesforce has developed a public dashboard that disaggregates intersectional workforce composition by tech and non-tech categories.[2] Companies collect the data to be able to produce such a readout, but few do so.
Hispanic or Latino
Not Hispanic or Latino
Male
Female
Male
Female
Job Category
White
Black or African American
Native Hawaiian or Pacific Islander
Asian
American Indian or Alaskan Native
Two or More Races
White
Black or African American
Native Hawaiian or Pacific Islander
Asian
American Indian or Alaskan Native
Two or More Races
Executive/Senior Level Officials and Managers
First/Mid-Level Officials and Managers
Professionals
Technicians
Sales Workers
Administrative Support
Craft Workers
Operatives
Laborers and Helpers
Service Workers

[3] https://www.shrm.org/resourcesandtools/tools-and-samples/how-to-guides/pages/enterprise-develop-dei-initiative.aspx

Use a platform that can deliver on DEI goals. The richest data takes into consideration differences between roles, teams, and levels of seniority, and can be used to pinpoint where in the talent acquisition and management processes women of color are under-indexed. The best tool for this is a Human Resources Information System (HRIS) platform that is built to enable analysis across the following criteria: employee characteristics, employee outcomes, and employee reporting structure. Employee characteristics include gender, race/ethnicity, age, nativity, education, disability status, and other characteristics that can contribute to employment barriers, such as national origin, sexual orientation, nativity, or language preference. Employee outcomes include tenure (start date to present), promotional history, compensation history, performance review metrics, and job satisfaction. Employee reporting structure includes location, team or vertical, manager, and contract type.

[3] https://www.shrm.org/resourcesandtools/tools-and-samples/how-to-guides/pages/enterprise-develop-dei-initiative.aspx

Fortunately, the functionality to collect and analyze this data exists in most HRIS platforms. These platforms already collect data on race, ethnicity, and gender in order to compile EEO-1 reports. The platforms store data on employee outcomes and reporting structure in order to put together organizational charts, create directories, and manage performance evaluations. In some organizations, the HR system and the payroll system will be different, so some work may be required to link data across these systems. SHRM, the leading HR membership association, has also provided guidance on leveraging HRIS and payroll systems to achieve DEI goals.[3]

[4] National Academies of Sciences, Engineering, and Medicine. (2022). Transforming Trajectories for Women of Color in Tech (E. Hammonds, V. Taylor, & R. Hutton, Eds.). The National Acadamies Press.

Collect data on the diversity of applicants. Gathering demographic data on applicants can help track progress on recruitment and hiring and provide valuable information for making strategic shifts as needed. Importantly, disaggregating data by tech and non-tech positions, job titles, gender, and race/ethnicity—with particular attention to the intersection of race/ethnicity and gender—can provide nuanced information about recruitment and hiring patterns, while also providing data for internal accountability.[4] Many Applicant Tracking System (ATS) platforms have the functionality to include diversity surveys in an application or to send a diversity survey to candidates after they have applied. The platform will then track that candidate across stages in the talent acquisition process and can produce data on conversion rates between stages—and, ultimately, hiring rates—by demographic group.

Benchmark the “top of the funnel”—or the recruitment stage—against the expanded talent pool of workers in jobs that use a similar skillset to tech jobs, and utilize skills-training organizations to access these individuals. The pool of workers in jobs that use many (but not all) of the skills often required in tech jobs is five times larger and has twice as many women of color as the pool of workers already in tech jobs today. Accessing this larger talent pool is critical for increasing the number of women of color in tech. Skills-training organizations can ensure that workers have not only relevant skillsets from their previous employment and education history but also the tech skills required by the target job. Through working with these organizations, hiring managers should aim for the benchmark set by the expanded talent pool before advancing to the next stage in the hiring process. See Appendix 1 for detailed, regional benchmark data.

Benchmark the “bottom of the funnel”—or the hiring stage—against the tech sector in a given region. Underrepresented women of color currently hold six percent of tech jobs nationally. If all employers, in aggregate, meet or exceed that benchmark for their new hires, the share of women of color in tech jobs would tick upward. Because hires are usually made within a local labor market, however, companies can benchmark their hires against the regional share of tech jobs held by women of color. Employers should aim to meet or exceed the current representation of women of color in tech jobs in their region. See Appendix 1 for detailed, regional benchmark data.

[5] https://blog.ongig.com/diversity-and-inclusion/diversity-goals/

[6] https://www.cnbc.com/2020/06/19/no-job-hire-made-unless-minority-candidate-interviewed-vmware-ceo.html

Review the tech job talent acquisition pipeline for where women of color are underrepresented. Companies can use their ATS system (described above under Collect and Strengthen Baseline Data) to see if and where women of color are falling out of the talent acquisition pipeline. Then companies can develop policies and goals to target the specific stage where women of color are under-indexed. Examples of stage-specific interventions include Hilton’s policy of requiring a 50 percent diverse slate of candidates for all open positions, or VMware’s requirement that at least one women or racial/ethnic minority candidate be interviewed.[5,6]

[6] Wittemyer, R., Nowski, T., Elingrud, K., Conway, M., & Jalbert, C. (2018). Rebooting Representation. Pivotal Ventures & McKinsey & Company. 

Uncover occupational segregation between job levels in tech. Companies can use their HRIS platform (described above under Collect and Strengthen Baseline Data) to review occupational segregation across job levels in tech. For example, nationally, underrepresented women of color make up seven percent of Database Administrators And Architects but two percent of Computer Network Architects. There is a significant falloff there that could be addressed with DEI interventions related to advancement.

[6] Wittemyer, R., Nowski, T., Elingrud, K., Conway, M., & Jalbert, C. (2018). Rebooting Representation. Pivotal Ventures & McKinsey & Company. 

Compare rates of turnover and rates of advancement at the job level for women of color and their peers. Companies can use their HRIS platform (described above under Collect and Strengthen Baseline Data) to review whether women of color are leaving tech jobs sooner or advancing up them more slowly, relative to their peers. Companies that identify disparities can review DEI interventions related to retention.

[7] Allen, J. (2021). The Status of Women of Color in the Workplace 2021. Women of Color in the Workplace. 

[8] Thomas, R., Cooper, M., Cardazone, G., Urban, K., Bohrer, A., Long, M., Yee, L., Krivkovich, A., Huang, J., Prince,S., Kumar, A., & Coury, S. (2020). Women in the Workplace 2020. McKinsey & Lean In. 

Conduct a pay audit to assess equity. Companies can use a payroll integration with their HRIS platform to conduct a pay audit. Because gender and race disparities in salary accumulate over time and impact retention and advancement, periodic audits to assess pay equity can help employers re-calibrate salaries to ensure that employees are being compensated fairly and equitably. Relatedly, employers can track promotions and raises, as well as furloughs and layoffs, by race and gender to ensure employees are being treated equitably.[7,8]

[9] Wittemyer, R., Nowski, T., Elingrud, K., Conway, M., & Jalbert, C. (2018). Rebooting Representation. Pivotal Ventures & McKinsey & Company. 

 

Salesforce makes equal pay audits a regular part of its organizational process. Wherever they find unexplained differences in pay between men and women, they compensate the affected employees for the difference.[9]

[6] Wittemyer, R., Nowski, T., Elingrud, K., Conway, M., & Jalbert, C. (2018). Rebooting Representation. Pivotal Ventures & McKinsey & Company. 

Elevate what works. Data empowers diversity officers and leadership to make a strong case for specific interventions and to assess the relative merits of different approaches. Data can also uncover best practices, for example by speaking with the manager of a team with much lower turnover rates for women of color in tech, or by reviewing the hiring process of the team that makes offers to a high share of women of color.

[10] https://justcapital.com/reports/share-of-largest-us-companies-disclosing-race-and-ethnicity-data-rises/

Communicating Progress A report by SHRM and the Harvard Business Review found that forty-seven percent of respondents to a DEI survey measure progress toward their diversity and equity goals at least twice a year. Firms that the authors classify as “leaders” are twice as likely as “laggards” to share those metrics with all employees (47 percent versus 24 percent).[10]

[11] https://www.hrdive.com/news/compensation-dei-goals-diversity-execs-accountable-mercer/586238/

Hold managers and executives accountable to diversity metrics. Employers can incorporate performance goals related to diversity, equity, and inclusion in their performance reviews, including the extent to which managers are fostering an inclusive culture, the extent to which they are building diverse teams, and so on. Financial incentives for meeting goals and benchmarks can further signal the importance of this work. A study by Mercer estimates that as of September 2021, 15-20 percent of S&P 500 firms include DEI metrics in their executive incentive plans, and 5-10 percent use quantitative DEI metrics to award incentives (rather than, for example, the subjective assessment of a compensation review board).[11]

[6] Wittemyer, R., Nowski, T., Elingrud, K., Conway, M., & Jalbert, C. (2018). Rebooting Representation. Pivotal Ventures & McKinsey & Company. 

Enable goal setting and generate buy-in across levels of leadership. With data collection and measurement, senior leadership can set clear, actionable, and measurable goals. Setting goals around clear metrics ensures that everyone is speaking the same language and is guided by the same North Star, from diversity officers to affinity groups, to hiring managers. Because these goals are in a common language, they can “waterfall” down to other executives, hiring managers, and team leadership in charge of operations. By treating DEI metrics as business goals, data collection and usage will become embedded within the processes of recruitment, hiring, retention, and advancement.

Appendix 1: Equation for Equality Report - Regional Benchmark Data

The representation of women of color in the technology talent pool across U.S. regions

Leverage the regional benchmark data to measure the “top of the funnel”- or the recruitment stage- against the expanded talent pool of workers in jobs that use a similar skill set to tech jobs, and utilize skills-training organizations to access these individuals. You can also leverage the regional benchmark data to measure the “bottom of the funnel” – or the hiring stage – against the existing tech workforce in a given region. This allows you to measure how many women of color are needed in the tech workforce in a region, and how employers can contribute to bridge the gap.

Metro NameNumber of Workers (Tech Sector)Underrepresented Women of Color (Tech Sector)Percent (Tech Sector)Number of Workers (Full Tech Talent Pool)Underrepresented Women of Color (Full Tech Talent Pool)Percent (Full Tech Talent Pool)
Not in identifiable area663251310125%39954902768437%
New York-Newark-Jersey City, NY-NJ-PA454754308877%217559025756812%
Washington-Arlington-Alexandria, DC-VA-MD-WV3206483100810%101702015030715%
Dallas-Fort Worth-Arlington, TX223525159577%82383210830613%
Los Angeles-Long Beach-Anaheim, CA219705162157%128303417867514%
San Francisco-Oakland-Hayward, CA21457767203%710644615929%
Chicago-Naperville-Elgin, IL-IN-WI214387118686%100742510613411%
Seattle-Tacoma-Bellevue, WA20579368773%549054354406%
Boston-Cambridge-Newton, MA-NH17130539962%711844397666%
Atlanta-Sandy Springs-Roswell, GA1682312327514%69483612531418%
Philadelphia-Camden-Wilmington, PA-NJ-DE-MD14643479785%6761676533110%
San Jose-Sunnyvale-Santa Clara, CA13231622012%345870194396%
Phoenix-Mesa-Scottsdale, AZ11913284247%4697845976613%
Houston-The Woodlands-Sugar Land, TX1176301154610%63482710344516%
Minneapolis-St. Paul-Bloomington, MN-WI11637638083%473559254315%
Denver-Aurora-Lakewood, CO10982556665%427999355258%
Austin-Round Rock, TX10470355875%3640004098011%
Baltimore-Columbia-Towson, MD10110695029%3472424435513%
Miami-Fort Lauderdale-West Palm Beach, FL915791228313%52694613218325%
San Diego-Carlsbad, CA8355439575%3845983926910%
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