More Women In Tech: The Smart Way To Overcome Skills Gaps
Technical skills are in high demand. Beyond the tech industry, businesses in all sectors require technological skills in order to innovate faster, serve customers better and support a hybrid workforce, amongst other challenges.
The World Economic Forum estimates that 150 million new technology jobs will be created globally over the next five years, with 77% of all jobs requiring digital skills by 2030. Currently, only 33% of technology jobs worldwide are being filled by the skilled labor needed.
One of the things forward-thinking companies are considering is how their Diversity, Equity & Inclusion initiatives can also play a role in closing these critical skills gaps. Many are considering how women, as one key group that is under-represented in tech roles, could be encouraged, redeployed and perhaps reskilled into all-important technology roles. Of course, to do this successfully requires thoughtful strategies around redressing bias, retention, flexibility, and L&D.
Reduce bias in talent management
It’s no secret that diversity leads to creativity, innovation and improved business outcomes. It’s also likely that subconscious (or conscious) bias is playing a role in the fact that there are so few women in STEM roles (28% of these roles are held by women). One way to combat this bias is to change the way you look at talent: through the lens of skills, and potential, rather than experience and education.
With a skills-first approach, companies can ensure they have a more objective assessment of talent, reducing much of the human bias that inevitably gets in the way of making good decisions (whether in hiring, development, redeployment, workforce planning and promotions). A skills-first approach lays the foundation for more equitable processes, across the whole talent lifecycle.
In a study by Deloitte, 80% of business executives said that making decisions about hiring, pay, promotions, succession, and deployment based on people’s skills (rather than their job history, tenure in the job, or network) would reduce bias and improve fairness.
And it’s not just about helping recruiters or hiring managers surface quality candidates. With explainable AI powering recommendations, candidates themselves (internal or external) are more likely to put themselves forward. Rather than facing a long list of open roles, they see tailored suggestions aligned with the skills they have, and skills the AI has inferred they have – thus boosting their confidence in applying for a role they might not have otherwise.
VMware is one good example of a company seeing better DE&I results from nurturing their talent community and unlocking new talent pools with targeted communications. They use Beamery to build email campaigns with a focus on underrepresented communities, along with event landing pages and sign-up forms for DE&I focused programs and events (including student scholarships, coding events, and networking events).
Learn more about applying explainable AI to skills data to reduce human bias in talent management.
Retain & reskill with smart technology
Your organization may already have lots of women working there: but are they engaged, and likely to stay? And could they be encouraged to move into those more critical roles, to fill the growing ‘digital skills gap’?
In our recent Talent Index research, women (and non-binary respondents) were less likely than men to say that their employer is set up to, and willing to, support them in moving into a new role within the organization. Meanwhile, tech sector employees in general were more likely than average to say that a lack of development opportunities was making them consider leaving their existing employer: so a decent internal mobility strategy, offering clear visibility of available and relevant opportunities, is a worthwhile investment if you want to attract and retain tech talent.
How do you make it clear how employees can develop and progress within your organization?
Once again, skills data and AI can help. With a clear understanding of the skills in your employee base, and AI inferring the adjacent skills, the context around skills, and the skills someone could learn, you can recommend new roles – or suitable upskilling programs – for all talent in your organization. You can even ensure new skills are added to people’s profiles automatically when new training is completed.
Meanwhile, an AI-powered Talent Marketplace can empower your internal talent with visibility, options, and (ultimately) confidence. Employees can see opportunities – perhaps short technical projects, which provide on-the-job training – that help move them to the next step in their career.
Learn more about how organizations can boost representation of underserved talent communities through technology.