High entropy alloys possess various superior functional and structural properties based on the complexity of their compositional landscape. Much research has been dedicated to the fingerprinting of specific aspects of this landscape, from short range order phenomena to unique phase evolution and stability. While marked advancements in both theory and experiment have been made toward these property-determining factors, characterization of these alloys has been fraught with challenges. In this talk, the motivating factors for understanding atomic-scale “fingerprints” in the quest for new alloys, the critical nature of multiscale characterization, and the progress toward these efforts across the HEA community will be discussed. An outlook on how characterization tools can be linked to theory and the role of machine learning will be reviewed in the context of future opportunities for tackling this exciting area of metallurgy and materials innovation..