If you’re a hiring manager struggling to fill tech job roles, you are not alone. The global technology trade association CompTIA reports that there are more than 700,000 unfilled technology jobs in the United States alone. Further, a recent World Economic Forum report suggests 133 million new jobs will emerge by 2022 as businesses develop a “new division of labor between people and machines.”
It’s no wonder that there’s a struggle: as technology continues to evolve the skills required to succeed on tomorrow’s IT teams are evolving as well. So, what’s an IT hiring manager to do to attract top talent and fill the pipeline?
What you may not realize is that the hiring practices used by your organization to identify the best talent may actually exclude swaths of qualified candidates. Tech companies continue to have profoundly low numbers of women and underrepresented minorities within their ranks and must adapt their hiring practices to tap into this new and much-needed talent pipeline. This will require IT hiring managers to broaden their perspective on what top talent looks like, conduct searches in new territory and even evaluate wages and benefits.
Study after study has proven that organizations with diverse workforces are more successful and innovative than those that do not have diversity throughout the ranks. One of the best (and perhaps most efficient) ways to start acquiring this talent begins with the job description. Many employers unwittingly shut their front door to qualified applicants at the very beginning of the application process due to biased language contained in the job description. Unconscious bias (we all have it) has a way of creeping into the language of even the most well-intentioned hiring managers. Here are a few ways to mitigate unconscious bias and swing your door wide open to a more robust talent pool.
- Unconscious Bias Training
Increase awareness of your personal biases and those of other interviewers through unconscious bias training or start small with an online implicit bias test. Harvard Implicit Association Test is the most popular. Once identified, make a conscious effort to manage accordingly. For example, biases that are motivated by unconscious negativity toward women in tech roles, can be mitigated by focusing on similarities or shared goals. Avoid the trap of excluding the best person for the job when they don’t look, act, and operate like you do.
- Blind Resume Reviews
If you don’t think you can objectively filter resumes, do so blindly. Remove the candidate’s name and other potentially discriminating information from the resume before assessing it. This will remove any unconscious bias you may hold when you rank the resumes according to the number of relevant skills the candidate possesses, rather than where they live or where they were educated.
- Watch Your Language
Check the language in your job descriptions. Studies have found that the language used in job descriptions can dissuade a qualified candidate from applying, rather than making the job sound appealing. Prevent bias by removing gender-themed words and other restrictive terms from your posting. Don’t make the job title and description so prescriptive that only a select few individuals would apply—make it as inclusive as possible. You may want to consider purchasing special software to assist you with this task.
- Remove Barriers to Entry
Eliminating obstacles needed for entry level tech jobs can you help you fill those roles. Many organizations in their quest for top talent require unnecessary credentials or job experience that marginalized groups may not possess. For example, a 4-year degree or 3+ years’ experience when a tech certification or 2-year degree will suffice. Top tech firms like Google and Netflix are foregoing the 4-year degree for some positions and placing more emphasis on skills over schools. Here are 10 tech jobs to consider.
- Understand Bias in Hiring Algorithms.
The expectation is that algorithms will help decision makers avoid their own prejudices by adding consistency to the hiring process. However, algorithms introduce new risks of their own. They can replicate institutional and historical biases. Hiring managers must monitor whether algorithms actually produce more equitable hiring outcomes and examine their pipeline from start to finish to detect places where latent bias lurks or emerges.
Would you like to learn more about diverse talent acquisition and retention strategies? Download CompTIA ‘s Guide to Hiring in Information Technology or visit https://www.comptia.org/resources/it-workforce.