One-factor-at-a-time experiments and similar “common sense” design strategies continue to be prevalent in industrial experiments in spite of the strong emphasis in statistics courses that these design strategies should be avoided. In justifying the avoidance of such design strategies, technical criteria such as design efficiency and confounding are usually stressed. However, these technical criteria routinely are overlooked by experimenters in industry when the desire for rapid feedback on factor effects is given undue precedence. In this article the preference for rapid feedback over statistical considerations is discussed relative to the compelling inherent deficiencies of these designs. The practical difficulties associated with the dynamic nature of the design construction, geometric imbalance of the designs, and serious modeling inadequacies that result from the use of these design strategies are detailed.