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Abstract. Effective quality control systems are the foundation for successful manufacturers and data publishers. For years, statisticians have proposed theories and findings to improve data product quality. The Economic Directorate of the U.S. Census Bureau collects various economic data with a requirement to accurately capture and analyze our data and conduct quality audits to ensure programs correctly identify problems to save time and money and ensure quality. Our primary objective is to assess our program areas' compliance with best practices, particularly in the area of dissemination, to ensure that statistically sound practices are used in the collection of data and in the presentation of results to the public. These data have gone through rigorous quality control procedures to assure the highest possible quality and consistency. In this paper, we discuss the first two rounds of quality audit processes that i) identified inspection goals and inspection plans, ii) detected data quality, iii) communicated quality expectations and provided recommendations based on the audit results. In the remainder of the paper we discuss measures to correct system challenges and introduce quality assurance measures throughout the survey life cycle.

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The Economic Directorate of the U.S. Census Bureau collects various economic data with a requirement to accurately capture and analyze our data to ensure programs identify and correct problems to save resources and ensure high quality. Effective quality control systems are the foundation for the success of data collection and must have well-defined program requirements and comply with Census Bureau quality standards. To meet these objectives, our primary goal is to build an automated quality control and quality assurance system that will identify and implement analytical methodologies which limit the introduction of error into analytical data. For data collection and data evaluation, a system is needed to ensure that all surveys conducted by the Economic Directorate produce results that are of the type and quality needed and expected for their intended use. In this paper, we discuss standard requirements for a set of automatically generated tables and applications that should be used to monitor various processes from planning through dissemination. In the remainder of the paper, we discuss the automated quality assurance checks that will be made in each survey phase to ensure that decisions will be supported by data of adequate quality and usability for their intended purpose, and further ensure that such data are authentic, appropriately documented, technically defensible, and statistically sound.