Poor data quality has been shown to have a serious impact on organization performance including increased operational cost and ineffective decision-making. In response to poor data, many organizations take on data cleansing projects as part of ERP and data warehouse implementations. These projects can be extremely difficult and produce less than desired results. This study will examine the data cleanup efforts taken on by an organization specializing in implementing and maintaining benefits modules for an ERP system. In particular this study will build on research in traditional software development and examine the impact of the conversion and cleansing team’s experience with the source systems, the target system and systems within a similar domain on the accuracy of data following the conversion and cleanup effort.