Scientists typically optimize assay parameters first, then select an automated liquid handler using default parameters during transition to an automated platform. This study illustrates the importance of optimizing both the assay and any associated liquid handling steps with the goal of minimizing variability. By altering various assay development parameters on a liquid handler, as well as varying parameters specific to automation, we demonstrated that some variations affected the outcome of the assay, while others did not. This methodology suggests that the user should pinpoint which variable liquid handler parameters have the most impact on the particular assay. Also highlighted is the importance of both developing the assay and qualifying the liquid handler for the assay in a concerted process optimization approach. By minimizing variability as early as possible, method transfers have a higher likelihood of success.