Organizations know diversity drives business success. According to a McKinsey report, organizations in the top quartile of gender diversity on their executive teams were 25 percent more likely to have above-average profitability. The returns for ethnic diversity were even more significant. Those organizations were 35 percent more likely to have above-average profitability.
Many organizations are also placing big bets in data transformations. Unfortunately, women and people of color are underrepresented in data roles. According to one study, only 15 percent of data scientists are women. And this has dramatic consequences.
For example, facial recognition detection software is less effective at matching black women than white men. Many police departments use facial-recognition software to compare photos of wanted suspects with a database of mugshots and government-issued photos. A false match could result in arresting an innocent person. When developing data products, organizations have to be careful not to create software with bias baked into the source code. Having a diverse data team allows teams to develop products that anticipate the needs of all users.
Minority groups are underrepresented in STEM degrees. For example, women make up 55 percent of college grads, but only 35 percent of STEM grads. STEM degrees signal value to organizations, but many more candidates have the skills for a job than have degrees. By emphasizing skills over degrees and seeking talent in new places, you can expand your hiring pool.
Our current educational system was designed for learning to occur in our 20s and 30s. With rapid technology change, the best employees will gain skills throughout their life. Empower your workforce by providing ongoing education to those with the passion and drive to learn new skills. Continuous training opportunities can open new pathways for highly-skilled employees who didn’t have access to university education in their 20s while also growing the organization’s capabilities.
MVPs (minimum viable products) have become popular in product management. The idea is to build the smallest product that creates value for a customer and get rapid feedback to improve it. HR can adopt the same approach for talent. We recommend developing minimum viable jobs, small roles that create value for the organization. You can then grow that talent based on managers’ feedback.
According to a study from the Boston Consulting Group, unconscious bias in job descriptions, roles, and recruiting events can deter minority groups from applying. Job descriptions that emphasize community, expanding the pie, and ongoing personal development can attract more women and people of color.
BCG also found women were less likely to apply for data science roles than men when computation was emphasized over mathematical problem-solving. Before assessing computational ability, we recommend discussing how your company uses data analysis, data engineering, or data science to impact your users. After all, how your team identifies important features and selects the right models as essential as computational ability or degrees.
Sourcing talent is only one step in the process. To grow your data talent, you also have to invest in developing and retaining talent. Many minority groups are “onlys” - the only person of color or woman at their level or team. According to research, “onlys” are more likely to contemplate leaving their job and experience burn out. By giving your people of color and women stretch assignments, publicly praising them, and developing training programs that promote them, you can improve retention throughout your organization.
The good news is no matter where you are in your data transformation, it’s possible to develop high-quality, diverse talent, so long as you invest in talent development and retention as much as you invest in sourcing. If your organization wants to increase diversity in data roles, LaunchCode is happy to help.