When 'more data' stops helping your model

Platforms often assume that marginal data always improves ranking quality. In practice, measurement noise, redundant signals, and shifting user intent create plateaus. Start by plotting error rates against cohort size for a fixed model, then against time for a fixed cohort — you will usually see two different stories. Policy discussions confuse stocks and flows: additional data collected this quarter may not change competitive dynamics if rivals can replicate the same signal cheaply. That matters for portability debates and for internal ROI conversations alike. Finally, document what you would not know even with perfect data — ethics and uncertainty are not the same thing, but both belong in the same paragraph of an honest executive summary.