The Total Survey Error (TSE) paradigm provides a framework that supports the effective planning of research, guides decision making about data collection and contextualises the interpretation and dissemination of findings. TSE also allows researchers to systematically evaluate and improve the design and execution of ongoing survey programs and future investigations. As one of the key aims of a TSE approach is to find a balance between achieving a survey with minimal error and a survey that is affordable, it is unlikely that a considerable number of enhancements to regular programs of research can be made in a single cycle. From an operational perspective, significant alterations to data collection processes and procedures have the potential to create more problems than they solve, particularly for large-scale, longitudinal or complex projects. Similarly, substantial changes to the research approach can have an undesired effect on time series data where it can become difficult to disentangle actual change from change due to methodological refinements. The University Experience Survey (UES) collects feedback from approximately 100,000 undergraduate students at Australian universities each year. Based on previous reviews of the UES, errors of measurement appeared to make less of a contribution to TSE than the errors of representation that were associated with the survey. As part of the 2013 and 2014 collections, the research design was modified to directly address coverage errors, sampling errors and non-response errors. The conceptual and operational approach to mitigating the errors of representation, the cost effectiveness of the modifications to the research design and the outcomes for reporting will be discussed with practical examples from the UES. A bibliography is included.