The Use Case Podcast · 2026-05-11 · 47 min
Most hiring teams still trust instinct over data. That works great until the “perfect” candidate flames out in 90 days. Spencer built a system that calls that bluff and replaces hiring bias with measurable outcomes. Hiring is still full of guesswork, résumé theater, and recruiter roulette. Spencer explains why companies keep making expensive hiring mistakes and how industrial psychology, assessments, and real-world data can dramatically improve quality of hire without wrecking candidate experience. In this episode… We unpack hiring science, candidate drop-off, assessment accuracy, safety-risk recruiting, and why most companies optimize for speed instead of fit. Spencer breaks down how HireScore combines ATS workflows, behavioral data, cognitive testing, and performance tracking into one system built to reduce bad hires. Key Takeaways : A bad hire can cost anywhere from 25% of first-year salary to 4x total compensation Some safety-sensitive workers are 10 - 20x more likely to cause workplace incidents based on behavioral risk scoring Most hiring managers still override assessment data because they “like” the candidate Companies often ask for the wrong fix.
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