Know, predict, control: A case study in services management

In today's volatile environment, controlling the cost of ownership and maximizing operational capability are both critical to the sustainability of systems. In the long history of services management delivered by Rolls-Royce, RAMS (Reliability, Availability, Maintainability, and Safety) has remained a key principle for service delivery and we have worked to evolve a services infrastructure tailored to deliver both the responsiveness and foresight demanded by today's customers. Contracts for Rolls-Royce services like TotalCare®, CorporateCare® and MissionCare™ are essentially performance based contracts for in-service systems delivered through the theory of `know, predict, control'. Where `know', involves understanding the current fleet status and maintaining the data management structure required to respond to that status. `Predict', involves forecasting the future fleet status and proactively identifying future potential threats and opportunities. Finally, `control', involves the actual management of the future fleet status with a team focused on both tactical and strategic objectives. This three-core theory is directly supported by a three-core organizational infrastructure - based around data, business, and fleet-support management - which in turn drive customer satisfaction and deliver on customer commitments. Hence, this paper will elaborate on this theory of `know, predict, control', relate it to the Rolls-Royce Services organizational infrastructure, and explain how a RAMS-centric forecast capability is leveraged as the decision-support heart of services management using the method of `forecast, analyze, validate, optimize, and recommend'. Note, that whilst many of the examples in this paper are Aerospace related, the principals, tools, and methods described are applicable for all systems, across all sectors, and in support of all customers.