Since the beginning, where there has been data, there have been women. From Ada Lovelace — the first computer programmer — onward, women have been instrumental in using data to advance human understanding. We have been behind the scenes, from mapping stars to putting people on the moon.
While there are many celebrated heroes, there are many women data pioneers lost in history. Part of this is inevitable; not everyone who contributes to humanity is remembered. However, this reflects a worrying trend in women's representation in data and data leadership.
Current State of Women in Data Leadership
The statistics for gender and racial/ethnic diversity in leadership positions are still alarmingly low. According to the 2021 U.S. Bureau of Labor Statistics, only 26% of computer and information systems managers are women. The 2020 World Economic Forum report showed that, globally, only 26% of professionals working in data and artificial intelligence (AI) are women. This underrepresentation of women in the data field also extends to the government sector. The U.S. Equal Employment Opportunity Commission’s report on Women in STEM found that only 25% of STEM leaders and 29% of STEM employees in the U.S. Federal Workforce are women, with only one-third of those African American or Black, Asian, Hispanic, or Latina, American Indian/Alaska Native, Hawaiian or Pacific Islander, or multiracial. This mirrors the larger pattern of limited gender representation in leadership positions worldwide. A study conducted by Deloitte in 2021 found that globally, women hold only 19% of board seats.
The gender gap in data leadership likely will not resolve itself. Data from the National Center for Education Statistics in the United States shows men were four times more likely than women to graduate with bachelor degrees and Ph.Ds in computer and information sciences. A Deloitte 2022 global survey found that 59% of women experienced noninclusive behaviors at work over the past 12 months, up from 52% in 2021. The COVID-19 pandemic has further exacerbated gender inequity. A Deloitte survey from 2020 found that almost 70% of women reported experiencing adverse changes that they believed hindered their career progression. It is not yet clear what the full impact of these disruptions will be on future leaders in this field, but there are some glimmers of hope.
The Potential Consequences of Underrepresentation in Leadership
Underrepresentation of women in data leadership comes at a cost — not just to the women who are impacted but to the organizations that hire them and the general population. Unexplored implicit bias can lead to gaps in data and analysis, resulting in disparities in the design of products as diverse as headphones, fitness monitors, and air-bag safety. Underrepresentation in data leadership and professionals is especially critical as AI becomes more mainstream. AI systems are designed and built by humans who may unintentionally introduce or fail to notice bias through their own prejudices or stereotypes. AI can replicate and amplify implicit bias in the workplace, leading to inequitable outcomes. When the government uses AI for activities such as predictive policing and health care, the impact of bias can be more consequential.
A diverse workforce is better equipped to identify and remove data and AI biases as they interpret data, test solutions, and make decisions. In a 2020 Deloitte survey of United States employees in the AI field, 63% of respondents agreed that AI models would produce biased results if AI continued to be male-dominated. This same survey showed 67% of respondents agreed that having more women in managerial, leadership, and role model positions directly benefits the organization’s employees.Market trends show that women's leadership benefits performance, and more diverse teams provide a higher profit margin. Therefore, from a business and equity perspective, diversity is key for the future of data. This is especially true for the U.S. Federal Government, where critical decisions driven by data impact not just the 330 million people in the United States but globally.
Responsibility as Data Leaders
To address the underrepresentation of women in data leadership, we should increase the number of women entering the field and support and promote the advancement of women representing a variety of racial and ethnic identities as the next generation of leaders. Male allies, in particular, have a responsibility to help prevent and call out noninclusive behavior and create a safe and empowering environment for everyone. To this end, organizations should design processes, policies, and programs with an equity lens. Focusing on equity has been shown to increase representation and reduce gender bias. This can involve adjusting hiring practices and recruitment sources to help minimize implicit bias that keep women from joining the data workforce. Women leaders and male allies can also focus on sponsorship and advocacy to help advance women's careers in data and mentorship for advice and support. Moreover, data leaders should also recognize the importance of building a diverse network across disciplines, organizations, and interests to create a constructive environment that empowers women to thrive.
We are thrilled to take a step forward with the launch of the U.S. Federal Government chapter of Women in Data. Women in Data is a nonprofit organization that raises awareness and educates women in data and analytics, focusing on networking, education, and development. The chapter was officially launched with an inaugural event that brought women and allies together from across the federal government and industry. The event featured a panel of women leaders, including Chief Data Officers, who discussed the importance of diversity in data, analytics, and AI, the role of allies in promoting diversity, and strategies for recruiting and retaining diverse talent.
It was uplifting to see women — whether they were experienced leaders or professionals starting their careers — come together to learn, grow, and build a community. We have places to go, hurdles to overcome, and precedents to set for the next generation. Together, we can.
About the Authors
Adita Karkera serves as the Chief Data Officer for Deloitte Consulting LLP’s government and public services practice and is a fellow at the Deloitte AI Institute for Government. She spent nearly 20 years with the Arkansas Department of Information Systems and was appointed as the state’s Deputy State Chief Data Officer in 2017.
Tess Webre is a manager at Deloitte Consulting LLP’s government and public services practice and currently serves as the Chief of Staff for the Chief Data Officer. She holds a Master of Legal Studies degree from the University of Maryland.
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