Enabling Innovation by Putting Statistical Products First

Federal statistical systems are undergoing rapid transformation due to declining survey response rates, expanding data ecosystems, and increasing demand for timely, actionable information. These pressures challenge traditional survey-centric models of statistical production and existing approaches to data quality. This article introduces a statistical product–first framework that prioritizes user-defined purposes and uses, supported by an iterative innovation cycle that enables the development of more relevant, integrated, and timely statistics. Conventional data quality frameworks are insufficient for this new paradigm. This article presents a revised statistical quality framework that treats quality as both an outcome and a continuous process. Together, these ideas provide a pathway for addressing the “last statistical mile”—the challenge of delivering meaningful and actionable statistical products.

Recommended citation: Keller, S., Becker-Medina, E., Dorius, C., Hawes, M., & Jarmin, R. (2026). Enabling Innovation by Putting Statistical Products First. CHANCE, 39(2), 12–23. https://doi.org/10.1080/09332480.2026.2673774
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