Women in Technology: It’s Time We Stand Up for What’s Right

At Data Ideology, we have made a concerted effort to recognize and achieve high levels of gender equity in both leadership and employee level positions.

We truly believe that having a diverse, equitable, and inclusive workforce leads to increased productivity, collaboration, and creative thinking. Data Ideology was built on a foundation of women in leadership positions, and we work daily to increase fairness and female representation in Data Ideology and in the technology space in Pittsburgh.

As the second employee, and first woman in an executive role at Data Ideology, I immediately recognized both the responsibility and opportunity I had to shape the policy and perspective in ways that could increase diversity, equity, and inclusion (DEI). I started by involving myself and the team in local events focused on women in technology. RedChairPGH1 was one of the first organizations I found that focuses on gender balance in Pittsburgh technology professionals. I attended all their events and encouraged other team members to go as well. I learned several ways to intentionally approach gender equality as a woman in technology leadership. These are a few that stuck with me, and I have worked to implement them at Data Ideology:

Recruit more women. A common excuse for not having more women in technology roles is that they don’t apply to open positions. We know that women are 16% less likely to apply for jobs that they view on LinkedIn and they report feeling like they need to be 100% qualified to apply for an open position 2. At Data Ideology we have purposely simplified job requirements to encourage more women to apply. We pull all applicants into our digital interview platform where it is easier to assess potential in addition to work experience. We also hire junior consultants from industries outside of technology giving women another opportunity to enter the tech workforce. We match these junior consultants with a mentor that helps them transition into the technology space while also providing opportunities for more formal types of training and certification. Finally, we recruit for new roles in non-traditional ways, whether that be through Women in Tech (WIT) networking events, women focused recruiters, or reaching out personally to perspective candidates. We still see less women applicants than men, but this just reinforces the need to keep working toward equity.

Keep the women you hire. Did you know that more than 50% of women leave the technology industry by the mid-point of their career 3. Among women who stay in tech 78% were happy with their work 3. At Data Ideology, we work to remain cognizant of employee needs and actively solve for ways to keep our employees happy. We provide opportunities for growth within the team with clear and consistent metrics and goals for climbing the career ladder. We have regular check-ins with employees to discuss their career aspirations and goals. We also do quarterly employee Net Promoter Score (NPS) evaluations and Rose-Bud-Thorn exercises to keep a pulse on the employee experience. We also offer Employee Assistance Program (EAP) benefits including 24/7 access and online resources for mental health, emotional wellbeing, elder care, and other topics.

In addition to engaging employees and understanding what makes them enjoy working for Data Ideology, we also focus on female representation in our workforce. 75% of women who continue in technology had a female role model 3. Data Ideology has women in 33% of the executive and 33% of the managerial positions. Not only does it help to have women in leadership, but 45% of women who stay in tech report having a peer group of other women3, and Data Ideology is comprised of 27% women overall, which is 2% more than the average for Pittsburgh and 4% more than the national average3.

A huge factor in keeping women in tech is their level of confidence in their own ability to find a solution to a difficult tech problem, 94% of women who stayed in tech report being confident in their skills and 56% of women who stay in tech fields say that they had superior opportunities for training3. At Data Ideology, we have annual training opportunities for employees with an annual stipend attached. We encourage all employees to continue to learn and build confidence in their skills, so much so that we require annual continuing education.

Another huge issue leading to women leaving tech fields is a lack of work-life balance; 22% of women site this as a reason for leaving tech mid-career3. At Data Ideology we understand that everyone has competing priorities, and we have a focus on family. To address these needs, Data Ideology has an unlimited PTO policy, flexible working hours, and no plans to go back to the office full time, ever.

Be intentional about equity in compensation. One of the top reasons that women stay in technology roles is fair and good compensation (41%)4. In 2021, Pittsburgh was rated the 51st best city for women in tech largely because there is a 79% gender pay gap. At Data Ideology, we are committed to 0% gender pay gap, and we are succeeding. There is no significant difference in total salary between men and women at Data Ideology (z = -.0014, p = .999). There is also no significant difference in raise percent (z = 0.345, p = 0.74) or raise dollar amount (z = -0.0027, p = 0.96) between men and women. Finally, there is also no significant difference in bonus amount (z = -0.0027, p = 0.998) between men and women at Data Ideology.

Do we consider ourselves 100% successful in achieving gender equity, no of course not, but we are always intentional and working to do better. We are currently focused on increasing women applicants in recruiting and hiring efforts and increasing the number of women employees at Data Ideology. Are you a woman in technology or another industry that is looking for a new role? Let’s talk! Add me on LinkedIn and reach out today.

Written by Rebecca Gazda

Managing Director at Data Ideology

Rebecca Gazda is the Managing Director with 15+ years of experience in Data and Analytics, Statistics, and Data Team Management.

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