Individuals maintain a dynamic regulatory system that may confer the flexibility to reversibly match their phenotype(s) to fluctuating environmental conditions. This process often involves dramatic modification across multiple subordinate traits. However, the relative influence of these component traits on whole-organism performance is poorly understood in natural systems. As a case study, we explore the contribution of subordinate phenotypes to a complex, multi-level trait related to cold tolerance in a wild avian system by combining assays of gene expression, tissue-level- and whole-animal physiology in a novel network analytic framework. Our work indicates that organismal performance is disproportionally influenced by few subordinate traits. We use these findings to guide suggestions for a purpose-driven approach to studying the mechanistic basis of dynamic phenotypes more generally. We discuss the pros and cons of alternative analytical techniques for use with these multifaceted datasets and the interpretation of the results. Our results shed light on the mechanisms underlying seasonal phenotypic flexibility, and provide a general analytical framework for other evolutionary studies of similarly complex physiological traits.