The ROI of Recruiting Signal Decay: When Past Data Misleads Modern Budgets
Every recruiting analytics team has a moment of doubt: the cost-per-hire model that worked last year suddenly overruns budgets, or the source-of-hire mix that once predicted time-to-fill now misses by weeks. The culprit isn't always bad data collection—it's signal decay. The patterns embedded in your historical recruiting metrics lose predictive power over time, and the rate of decay varies by metric, market, and role type. This guide helps experienced practitioners decide how to handle that decay when building budget forecasts and ROI models. Why Signal Decay Demands a Budget Decision—and Who Must Make It Recruiting signal decay is not a theoretical risk; it is a measurable erosion of correlation between past data and future outcomes. A conversion rate from applicant to hire that held steady for two years can shift by 10–15% in a single quarter when labor market conditions change.