InsureCo*, a major U.S. health insurance company serving millions of customers, wanted to harness its vast data warehouse containing hundreds of billions of processed medical claims and patient outcomes records to gain actionable insights into various opportunities. In particular, they wanted to reduce costs, identify new protocols to improve patient care results, identify fraud, and improve performance. Internal IT resources were fully dedicated to other major projects underway and competency in big data analytics did not exist within the organization. Several large technology and consulting firms were approached about this opportunity; however, their responses required massive financial commitments with multi-year project durations. This outcome would have been contradictory to the company’s stated objectives for a rapid proof-of-concept (POC) project and a roadmap to productize the platform across the company when fully completed. The company sought P&C’s recommendations and an action plan to meet its objectives.
P&C worked closely with the company’s project stakeholders–C-level leaders, Medical Management, Underwriting, Risk, Technology, Operations, and Finance–to gather, synthesize, and prioritize the expected outcomes using a value versus ease and capabilities analysis.
With project outcomes clearly defined and internal expertise and resource availability gaps in mind, together we agreed to an 18-month timeline to fully develop and implement the project. An initial forecasted target was set with an expectation of a $20-30M/year cost savings opportunity, net of all operating costs, that would support a fully productized solution.
P&C recommended five major project components:
InsureCo is now one of the top industry leaders in big data analytics and its business outcomes are frequently showcased as industry best practices. The 18-month, rapidly paced project delivered $115M in annual savings, net of all associated costs—approximately 50 times P&C fees.
Proof of Concept
*We take our clients’ confidentiality seriously. While we’ve changed their names, the results are real.