Hiring decisions are often based on the extrinsic, observable characteristics, and not based on “fit for role” measures. This increases the risk of overlooking top talent, failing to find suitable candidates, and being unable to execute corporate strategy.
Goals and Objectives
Identify and eliminate unconscious bias in recruiting and hiring processes to identify characteristics of quality and culture fit to create more effective and inclusive strategies for prospecting, assessing, and hiring diverse talent.
This use case is supported by tools powered by machine learning and natural language processing, and modern applicant tracking systems, to provide identify possible unconscious bias in sourcing, hiring, and onboarding. This will also require system integration, IT consulting and business consulting services to properly design and implement these systems.
Use Case Summary
The organization develops and deploys best practices actively identify viable candidates from all demographics and implements sourcing and interview practices that include data-driven insights along with human decision making to make hiring decisions.