An effective Diversity Equity and Inclusion (DEI) strategy for staffing solutions requires more than just a personalized candidate experience. Employer need to evaluate the entire recruiting and talent acquisition lifecycle. An important first step is to look at talent sourcing from the perspective of skill matching.
A Harvard Business Review study revealed that 80% of business leaders experienced issues with their Applicant Tracking System. Keyword limitations and system settings, such as a missing credential or gaps in work history, were filtering out qualified candidates. It excluded good prospective hires and had a negative impact on diversity recruiting. Viable talents were overlooked because the sourcing and search tools emphasized work history, education, and location over skills, experience, industry, and core competencies.
It’s time for employers to move past traditional resume searches and grow talent pools with a skill based matching approach. Focus on the candidate’s skills, not degree requirements. This allows us to search for competency, potential, and transferable skills.
In a recent Smart Inclusion conversation with Kiko Liang, we discussed how a more flexible, skill based matching strategy is key to Building A Better Hiring Process.
A Deloitte study recently showed strong support for skill-based matching. 80% of business executives said that basing decisions about hiring, pay, promotions, and succession on people’s skills helps reduce bias. This, in turn, increases fairness.
In addition, skill matching supports successful DEI staffing solutions by helping create a culture of belonging.
The skills-first approach removes unconscious and subconscious bias from candidate selection. It provides an objective assessment of talent, and a basis for more equitable, inclusive Human Resources practices, from hiring to learning and development to promotion, career pathing, retention and succession planning. It also broadens the talent pool to engage and attract:
Accurate skill matching begins with accurate, quantifiable data. Skills data can be difficult to measure because an individual’s skills change and evolve, many ATS don’t use the same terminology,
and employer may place higher values on specific skills or soft skills pertaining to their industry.
In order to make skills-based hiring decisions and improve diversity recruiting, organizations need to establish a holistic view of skills, to connect skills to each other in the job-specific talent data assessment criteria.
This is where hiring AI tools can help recruiters and sourcers connect the dots. AI tools help set parameters that are more inclusive by evaluating the skills of all candidates using the same criteria.
A good ATS may parse viable skills from candidate resumes along with education and work history. Some ATS staffing solutions allow recruiters to inventory marketable skills, and provide search tools that help match desired skills as well as uncover skills that candidates lack but want to learn.
Artificial Intelligence goes a step further with skill matching search tools that provide an unbiased way to evaluate candidates based on what’s most important in the job requirements: What skills can they bring to the task at hand, and what is their potential for success in a specific role.
Skills assessment testing is one way for employers to validate whether the applicant has the required skills to succeed. AI driven skill matching can use the scores from assessment tests to identify top talent.
When used as part of a DEI recruiting strategy, AI skill based matching can reduce bias in hiring, and increase inclusion and retention.
It’s important to note that Artificial Intelligence systems themselves can have bias built in. Think of the AI search as a “virtual sourcing assistant” that when properly “trained” can reduce bias and achieve better diversity representation.
When applying AI and machine learning to candidate sourcing, algorithms must be “taught” to recognize the right data to find the “buried treasure” in desirable skill sets. Candidates that may be an ideal fit for a role – who may otherwise be overlooked – are “suggested” by the skills-matching technology.
The human factor is still vital to assess AI recommendations, and further “instruct” the AI tools on skill based matching – without adding their own personal bias to the search parameters. Be sure to use a “teachable” hiring AI tool with enough transparency in the search results to see how – and why – candidates were recommended.
Job descriptions must also be adjusted to weight skill sets over other search criteria such as education or keywords on a resume.
As the workplace evolves into a more inclusive environment, successful staffing solutions will adapt candidate sourcing strategies to include skills based matching.
Companies that refocus candidate sourcing with transferable skills matching for both internal and external hiring will become the employers of choice. Tools like the SmartSearch AI-Match that provide one-click candidate sourcing and AI-Smart search capabilities to match candidates to jobs and match jobs to candidates can help businesses create a more human-centric and bias-free talent acquisition strategy.
Resources:
Why A Skills-First Approach Supports Organizational Diversity
Three Ways To Invest In Skills-Based Hiring To Improve DEI
