For many National Statistical Organizations, imputation is the preferred treatment for item non-response. Consequently, the choice of imputation strategy can have a significant impact on resulting statistical estimates. Recently, a generalized framework to evaluate and improve imputation strategies at Statistics Canada was proposed and used to examine the choice of imputation strategies within the confines of the Canadian Census Edit and Imputation System (CANCEIS). The goal now is to develop a generalized, user-friendly tool for survey methodologists, managers and statisticians, allowing them to assess and compare imputation strategies on existing datasets. The focus of this paper is on the development of the tool itself, in particular the choice of simulation parameters and output measures. Finally, we explore how best to present results, including data visualization, to facilitate data-driven decision-making in survey design.