High quality data is essential in a pavement management process for achieving the objective of accurately reporting the existing network conditions, recommending maintenance and rehabilitation activities, developing performance models, and predicting the future network condition. The Virginia Department of Transportation (VDOT) has required an independent verification and validation (IV&V) of the automated distress data collection process since the early 2000s. The IV&V process includes both quality control and quality assurance activities. The process of IV&V has been effective in identifying systematic errors, correcting those, and in taking steps to prevent further recurrence of such errors. At the same time, it insures that random errors are kept to a minimum. At this time the process has been applied to 10 data collection cycles using pavement monitoring information collected by a single vendor using automated data collection equipment and a semi-automated rating process. Results of this process are presented in this paper. Two pavement distress indices used by VDOT, the Load Distress Rating and the Non-Load Distress Rating have been closely controlled for each data collection cycle. As shown in the paper, there is an indication of data quality enhancement over time as well as a stabilization of the variability in the data from one year to the next. The paper also includes a summary of several significant issues that should be considered in any data quality effort.