Survey quality encompasses more than just the accuracy of estimates, although that is an important part. It also includes timeliness, accessibility and clarity of information, and completeness. A total survey error framework considers errors from nonresponse, selection bias, measurement methods, and data processing, as well as errors that result from taking a sample instead of measuring the entire population. Total survey design calls for an interdisciplinary approach, requiring expertise about the theory of survey sampling, design of experiments, statistical process control, mixed models, cognitive psychology, management, and ethnography. This chapter discusses how to assess total survey quality and how to design a survey to reduce all sources of error.