Measurement error the difference between the “true value” of a concept being measured and the survey estimate that represents that concept can be very difficult to assess and reduce. While there have been great strides in the field of survey methods research in recent years, many ongoing federal surveys were initiated decades ago before testing methods were fully developed. As such, the degree and nature of measurement error associated with these surveys is often unknown. However, the longer a survey is in use, the more established the time series becomes, and any change to a questionnaire risks a break in that time series. Thus, a comprehensive survey redesign is generally approached with caution for a number of reasons. First, demonstrating that any changes actually do reduce measurement error (and do not inadvertently introduce other problems) can be elusive. Second, even if a statistic is imperfect(e.g., a point estimate contains bias), if the cause of the imperfection does not interact with time,then the trend line of that point estimate can still be valid and informative. Third, the loss of the time trend to the data user community due to a break in series is sometimes untenable. Finally,research to bridge the break in series is costly and sometimes data do not exist for the task. On balance, continuing with the status quo can be the best course of action in many cases.