With the emergence of big data capabilities, as well as legislation leading to the implementation of electronic health records, we find analytics have become a natural extension to our understanding of how organizations can leverage information. Often times, it is the case that a hospital or care provider is capturing more data than it knows what to do with; the market has answered this opportunity with specialty firms that take a provider’s information, and build custom analytics for that provider, based on the provider’s processes, as well as government mandated processes. In this paper, we examine the interposition of the healthcare provider’s data and the opportunity of an analytics firm’s model to gain insights as to how healthcare costs can be lowered from a data-driven process analytics perspective. This research presents the initial findings from case study conducted with a large healthcare provider to define their needs, and an analytics firm to define their offerings. The results will serve as a baseline towards building an understanding of generalizable process analytics that will serve two purposes: 1. Healthcare cost reductions. 2. Patient Suffering reductions.