Over 300 submissions were received for the 2016 HRWest Conference. Joseph P. Murphy’s session, Computer as Recruiter – Using Predictive Modeling for Hiring, was selected to address the growing need to understand the role of technology, big data, and talent analytics for improving hiring outcomes.
The recruiter as computer is here. Big data, machine learning, talent analytics, algorithms, and predictive modeling are all changing the nature of talent acquisition. As such, the nature of recruiters’ work and the way hiring decisions are made is undergoing a transformational shift. Machine learning as predictive modeling has broken into talent acquisition, creating a powerful decision making blend of human and machine.
The result of this augmented reality? The creation of Centaur Recruiters. So, what’s your other half? Learn how machine learning is changing how recruiters work, as well as the way hiring decisions are being made.
Eighty percent of Big Data is unstructured, random, and text based. Resumes are a great example of this. Thirty percent of companies participating in the Candidate Experience Awards indicate they receive over 200 applications per job posting. Finding best-fit talent in the sea of random data has created a need for structured and relevant data gathering and decision support tools for recruiters. Machine learning and predictive modeling are changing the talent acquisition landscape, and as a result today’s recruiters must be armed with evidence-based methods to capture, analyze and interpret applicant data and leverage this ongoing shift in the way hiring decisions are made.
Come to HRWest to learn, share, and walk away better prepared for using data for evidence-based hiring.