So, here’s a couple boring notions in statistics- Alpha and Beta Errors.
Applied to Recruiting Decisions:
Beta Error: Occurs whenever we hire a candidate who fails. Not so good. Everyone loses. Definitely want to make sure we hire someone who makes us all look good by succeeding. Reducing that risk with today’s emerging technologies continues to be a priority. Screening and assessments that incorporate Machine Learning seem to be reducing the risk of human decision making without the benefit of lots and lots of data. Fair enough. Evidence based on concurrent analysis has much to be said for