Recruiting practices need to expand it to reach suitable customer-centric candidates from nontraditional sources. By opening up the candidate pool and eliminating bias in the hiring stages, organizations will avail themselves of greater pools of talent for competitive advantage.
Goals and Objectives
Success is achieved by leveraging a multichannel approach to candidate identification along with identification and elimination of unconscious bias in both the recruiting and hiring stages of the process.
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 systems integration, IT consulting, and business consulting services to properly design and implement these systems.
Use Case Summary
The organization develops and deploys best practices to actively identify viable customer-centric candidates from all demographics and implements sourcing and interview practices that include data-driven insights along with human decision making to make hiring decisions that match the population.