When a new statistic, model, or learning algorithm is developed, simulation studies are often used to examine sampling behaviour or other performance measures. These studies are experimental designs. Yet the most common designs are, to put it politely, unsophisticated: either varying a single factor at a time, or a time-consuming full-factorial study. On the analysis side, basic tools like ANOVA are often forgotten. Instead, voluminous tables are presented! We demonstrate simple concepts from the design and analysis of experiments. Such tools can do for statistical simulations what statisticians promise to other scientists: save time and make efficient use of data