Modelling R&M in Performance Based Contracts - When Does Risk Equal Reward?

With the uptake of performance based contracting (PBC) and performance based logistics (PBL) arrangements becoming commonplace, especially in the long-term management of complex technical equipment such aircraft and ships, it is important for all parties to be able to quantify the level of financial risk associated with the arrangement. Here, the definition of risk is dependent on the perspective. Risk from the contracting agency refers to the inability of the contractor to deliver the level of services required under the contract. Risk from the contractor refers to a reduction in payment due to a commensurate reduction in performance against the contracted requirements. Regardless of perspective risk can be defined in terms of two dimensions: (1) the likelihood or probability of an event occurring, and (2) the severity or consequence if the event does occur. While the consequence is clear, the likelihood function is typically either ill-defined or misunderstood. Moreover, contractors frequently claim that the whole at risk margin, typically represented by the contract profit margin, is under "threat" by the PBC framework. However, it can be shown that the likelihood function is not uniform and therefore does not reflect this assertion. Using the three R&M performance measures from Richardson and Jacopino (2005) this paper formulates a Monte Carlo (MC) simulation of a PBC arrangement. This includes the simulation and necessary variation of the inputs such as airframe hours (AFHRs) which is primary method of measuring system exposure at the or whole aircraft level. Examining the results from a fictitious example for an aerospace through life support (TLS), or whole aircraft, sustainment (utilisation) contract provided confirmation that the weight performance score (WPS) likelihood function is not uniform. Specifically, the simulated WPS showed that the whole at risk margin was not under threat by the PBC framework unless the result of a major systemic failure, all of which is under the control of the contractor. It should be noted that while this paper is written around an aerospace example, the methodology and technique is equally applicable in the measurement of contract risk in a PBC/PBL. Framework in other industry sectors (e.g. manufacturing, transportation, power generation, etc)