People to fill technology jobs, especially data- and software-related positions, are in high demand not only in technology companies but in fields such as advertising, business, finance, government, medicine, and national security, among others. The global value of the big data and data analytics business alone (and the software that underpins it) is expected to reach $512 billion by 2026, up from $171 billion in 2018.
A large and diverse workforce with technology expertise will be needed to meet demand and sustain this growth. However, in recent years, the technology sector as a whole has come under fire for having a diversity problem that makes growth more difficult. In particular, though women make up half of the American workforce, they only account for 12% of American programmers, for example. And among the leading U.S.-based tech firms, “none have more than 32% of women in leadership roles.”
There are a number of factors contributing to why women are still underrepresented in technology. Some studies highlight the so-called “pipeline” issue – a lack of women candidates for tech-related positions. Since women are, in many cases, culturally or socially discouraged from cultivating science and math-based skills, they end up getting degrees in technology disciplines at a lower rate than men, and so fewer women appear in the pool of job candidates for tech positions.
Other studies argue that women’s underrepresentation is derived from structural issues within organizations, such as fewer opportunities within male-dominated workplaces for women to take leadership roles or receive vital mentorship; workplace cultures that are dismissive of issues like sexual harassment; and a preference for leadership and communication styles that men typically possess over the ones that women typically possess--such as dominance and assertiveness over collaboration and empathy.
While there is debate over what causes the underrepresentation of women in technology, there is a growing consensus that successful technology companies need to recruit more women to their teams. Indeed, diversity is more than an organizational afterthought – it is, in many cases, vital to a business’ prolonged success. Research shows that businesses with diverse teams exhibit greater innovation and creativity, cultivate a broader range of skills, increase overall productivity, relate to customers more successfully, and have higher revenues.
Women are already leading innovations in the technology industry. For example: Stanford professor Fei-Fei Li is pioneering artificial intelligence algorithms that include human sensitivity and, in doing so, combatting biases that are often built into “intelligent” machines. Jewel Burks, an expert in computer vision technology, is a leading advocate for racial and gender equality within technology and programming. And Susan Fowler, a former programmer at Uber, turned her experiences into a viral blog post that called-out sexism in the tech industry and ultimately forced Uber – a company notorious for the bad experiences women have had while utilizing its mobile application – to change its policies.
Cultivating Women’s Leadership in Technology and Data
There are a number of ways tech companies can cultivate women’s leadership and center diversity and equity in their organizations.
Strong mentorship is particularly important to creating a new generation of women tech leaders. Mentorship is particularly impactful when women are mentored by people of similar backgrounds. Women entering tech fields often feel best supported by women mentors who understand the particular challenges and barriers they face in a male-dominated field.
Institutional support is vital to women in technology. Many women entering the workforce have to balance the demands of child care and family obligations with their professional goals. Research shows that women still bear a heavier load than men when it comes to child care and household chores, and these added responsibilities can hold them back in their careers. Workplace innovations like flex time, remote work, and childcare assistance can help offset this.
In many cases, organizations need to make structural changes to promote women’s leadership. This may mean diversifying their recruiting efforts, ending biased hiring processes like referral hiring, and establishing clear and measurable criteria for evaluating employees and doling out promotions and raises. Many of the biases that affect organizations are unconscious biases, meaning they are perpetuated without the perpetrator’s active knowledge. Creating clear, objective criteria that can be equally applied to all members of an organization is one way to curb the effects of unconscious bias.
Education is also an important precursor. Increasingly, schools and nonprofit groups are explicitly marketing STEM education to young women. Take the Girl Scouts, which has several programs aimed at cultivating girls’ interest in science, technology, engineering, and math, and there are a number of educational initiatives aimed at bringing girls into STEM; for example, Girls Who Code works with elementary, middle, and high school students to teach programming and engineering skills.
Purdue’s Data Analysis Program Prepares Diverse Students for Tech Careers
Purdue University’s history has been enriched by the contributions of pioneering women – including Amelia Earhart and astronaut Janice Voss. Purdue continues to recognize the importance of diversity in building equitable solutions and driving important innovations. The University boasts an active Women in High Performance Computing group, for instance, and fielded an all-women student supercomputing team. Through excellence in STEM education, Purdue is preparing a new generation of diverse students for high-demand careers in technology and data science.
Purdue’s 100% online Data Analytics Certificate Program is a convenient and customizable jumping-off point for students who aspire to work in data analytics, business intelligence, project management, and IT systems analysis. This 20-40 week program provides students with foundational knowledge in Python and R programming for data analytics, text mining, sentiment analysis, data visualization, and other valuable skills that can be immediately applied in their jobs.
All students in the program are supported by an expert mentor and work closely with other students to solve real-world problems. In addition to receiving educational training, students also have access to career coaching so they can pursue their goals immediately after completing the program.
To learn more about Purdue’s Data Analytics Certificate Program, please visit the program website.
