An inadequate sample size, low statistical power and poor reliability in a clinical trial exposes subjects to potentially harmful treatments without advancing knowledge. An unnecessary number of subjects may be exposed to a potentially harmful treatment, or are denied a potentially beneficial one. For such an important issue, there is a surprisingly small amount of published literature. One step in determining statistical power and fidelity requires educing an effect size of scientific interest. From an industry viewpoint, it is not up to a statistician to decide this; however, it is the statistician's responsibility to try to extract this information from the industry researchers involved in planning the study. A major problem being observed is that researchers don’t recognize it as a question that they are responsible for answering. This presentation will outline a model of protocol fidelity in clinical trials. The model addresses the complexity of clinical trial research, by expanding the aspects of the research process that require attention to fidelity from more simple models focusing on delivery and performance that incorporates study design and training. This will allow a more precise understanding of the elements responsible for a treatment's success or failure, improving replicability and translation to clinical or community settings.