AI HR Daily by OVI
There's a strange paradox sitting at the heart of modern recruiting. Ask any HR leader what their most important hiring metric is, and they'll tell you instantly: quality of hire. Nearly nine out of ten say it's their top priority. And yet only one in five companies actually measure it. That 68-point gap between what we say we care about and what we actually track is costing companies millions — and most leadership teams don't even realize it. In this episode, we dig into why quality of hire is so hard to measure despite being so clearly valued. It's not laziness or apathy. There are five structural reasons it fails: data lags, siloed systems, missing collection mechanisms, misaligned incentives, and AI tools being adopted without any outcome tracking. We break them all down. We also cover the formula teams use to actually calculate quality of hire, what good looks like (75% is the baseline, 85% means you're in the top tier), and what talent engineering — treating hiring like an engineering problem with measurable pipelines — actually means in practice. If you're spending more on hiring technology every year and wondering whether any of it is working, this episode is for you.
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