According to a McKinsey & Company poll, CEOs think their HR organizations lack the ability to use predictive analytics to improve hiring data in a meaningful way in their day-to-day HR processes. They worry they are squandering the proven predictive power of data analytics to make better hiring decisions.
Bringing your data into focus with predictive analytics can change, not just recruiting metric outcomes but also the core of your recruiting metrics.
Traditional recruiting metrics like time to fill, interview to hire ratio, and cost to hire are essential because they provide visibility into how your process functions. Metrics allow you to spot trends and demonstrate improvement over time.
Join us to learn more about the value of using predictive analytics to improve hiring, the benefits of a scientifically valid, data-driven hiring process, and get answers to questions like:
Critical questions like these and more need to be addressed for enterprises to benefit from the power of predictive analytics to improve hiring.
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Eric oversees all research and product innovation initiatives at Modern Hire, including the data-science focused Labs team. He is passionate about applying machine learning and deep learning in particular, to candidate data to more effectively match candidates with career opportunities. Eric is highly motivated to show the power of these new AI-based technologies and guide them to ensure they benefit individuals as well as organizations. He writes extensively on and has spoken around the work on these topics.
Eric previously served as the Executive Vice President, Innovation at Shaker International, of which he was also a founder. He also was a Consultant at CEB/SHL.