Bottom Line: The most urgent talent management issue every business is facing today is how to improve Diversity and Inclusion (DI) by reducing the potential of bias and evaluating candidates on capabilities first.
Organizations need to focus more on using AI and machine learning techniques to identify, recruit, and hire candidates based on their capabilities while removing as many potential bias triggers as possible. Businesses that are making DI an integral part of their companies are experiencing an 83% improvement in their ability to innovate, a 42% increase in team collaboration effectiveness, and a 31% improvement in customer responsiveness, according to Deloitte. A study by the American Sociological Association found that companies with the highest levels of racial diversity attain 15 times the sales revenues of those organizations with the lowest levels. McKinsey found that excelling at DI is directly related to higher profitability and value creation. Their recent study, Delivering Through Diversity, provides a base of tangible benefits that are useful in creating a compelling business case. A copy of their study is available for download here (PDF, 42 pp., no opt-in). Companies in the top-quartile for ethnic/cultural diversity on executive teams were 33% more likely to have industry-leading profitability according to the study. The following graphic from the McKinsey study, Delivering Through Diversity, quantifies how greater ethnic diversity correlates to profitability:
AI Can Help Match The Most Qualified Candidates And Reduce Bias
Many CEOs are prioritizing DI today, dominating the discussions of senior management teams on how they can improve talent management. What’s slowing down their progress is the fact that existing talent management systems are designed first for compliance, not candidate capabilities. Legacy talent management systems rely mainly on manual and siloed processes that have HR, not the candidate, at the center of the system’s workflows. Applicant Tracking Systems (ATS) prioritize resumes based on keyword SEO performance, not the capabilities of the candidates. Designed to scale for millions of resumes that, in turn, are evaluated by recruiters and hiring managers using the same biases and decision-making process that has led to at best a 30% success rate of hires, current ATS, and hiring systems engrain biases into companies over time.
One of the most interesting companies taking on this challenge is Eightfold.ai, whose Talent Intelligence Platform uses machine learning algorithms and models to continually learn and provide prescriptive guidance on how to best match an applicant or employee with a specific role based on matching capabilities. Eightfold.ai’s platform continuously learns, creating new contextual intelligence about every aspect of talent management. The following is a diagram of the Eightfold Talent Intelligence Platform:
System Integration Is Key To Improving Diversity And Inclusion
Eightfold AI’s mission is there is a “Right career for everyone in the world,” which is why they immediately stepped up to help flatten the unemployment curve post the health crises created by COVID-19. Within a matter of weeks, Eightfold AIs’ engineers created the Eightfold Talent Exchange, working with the FMI – The Food Industry Association and supporting partner McKinsey. The Talent Exchange fills an urgent need in the market for a platform that matches people to the right jobs in companies that are hiring. Associated Wholesale Grocers, C&S Wholesale Grocers, CircleCI, Giovanni Foods, Ingles, Instacart, Lowe’s, Macy’s, Mondelez International Postmaster, Stop & Shop, and United Airlines are all partnering with Eightfold and participating in the Talent Exchange. For additional details on the Talent Exchange, please see the post, How To Reduce The Unemployment Gap With AI. At the same time, the Talent Exchange was being developed and launched a new Virtual Event Recruiting solution.
As organizations look to increase HRMS and HRIS integrations with data sources across the business, an interesting area framework to consider is BMC’s Autonomous Digital Enterprise (ADE). The framework uses AI and automation to deliver custom workflows that could serve the needs of recruiting managers, recruiters, and CHROs that capitalize on the economies of scale in a centralized IT architecture. The ADE framework gives fast moving organizations the agility and insights to manage HR needs and requirements. As an example, financial services organizations are realizing the benefits of an ADE framework in their ability to deliver an exceptional employee experience from anywhere to ensure that talent is retained and supported.
Conscious and unconscious biases influence every hiring decision made, and it’s up to Chief Human Resources Officers (CHRO) to take a strong leadership role to reduce its negative effects. AI models can provide models that allow companies to hire for potential, without taking any personal information like age, sex, ethnicity, name, etc. that could trigger bias. This can now be done at scale for every employee and every candidate. This self-service capability, and transparent AI builds trust and confidence. Candidate or employee and the hiring managers or recruiters see their capabilities in the context of a particular job. If you are a good fit – you can see why. This allows the recruiter and hiring manager to make a much more informed decision – and with consistency. In addition, dashboards across every step in the process and every person in the process enables CHROs to easily identify opportunities to improve compliance to company’s D&I policies.
AI by itself isn’t capable of removing hiring biases on its own; it can, however, guide recruiters and hiring managers to the candidates with the best capability for a given job, matching capabilities that increase the probability of a new hire succeeding. Resumes only show a small part of a person’s skills, denying companies the potential to achieve greater personalization at scale across every aspect of talent management.