Chemists are often guided by incredible intuition when predicting the how and where an organic molecule will react. This is based on wisdom and a fundamental understanding of reactivity. However, while this approach drives the majority of reaction development in our field, the reality is that we rely significantly on optimizing reactions and structures for a desired outcome. While a routine process, optimization protocols can cause a considerable investment of time and do not always provide an adequate solution. Therefore, we have aimed to develop a program that facilitates more rapid analysis of structure function relationships to reveal not only better systems, but also the underlying reasons for improved performance of substrates, catalysts, or other functional materials. The lecture will outline how we have put into practice a method that combines the foundational promise of physical organic chemistry with modern “big data” analysis tools to ultimately precisely predict and understand the performance of new reaction components and energy materials.