The suppliers of long-life assets such as submarines and airplanes no longer simply sell these assets but provide advanced engineering services. In other words companies that traditionally designed and manufactured long-life products now compete through the provision of a service, such as asset availability.
These companies face a high level of uncertainty due to the novelty of the process and the long-term nature of services. However, regardless of these uncertainties the service provider needs to estimate the cost and expected profits for such provision. The pricing decision of these service contracts is influenced by multiple factors and considerations and as a minimum the supplying contractor needs to yield suitable profit to sustain their business. From current research it is known that the estimated company profit is often optimistic. This places pressure on both the customer and the service provider. From our research we found examples of reductions in profits for those providing services. For example a company, which moved to performance-based road maintenance contracts, only yielded less than 50% of their expected profit. So, how can providers of long-life, high-value assets estimate the costs for delivering an expected outcome and account for the uncertainties? One of the challenges is measuring such uncertainties and taking account of them in the pricing decision.
In this paper we present our research to date on the provision of a framework and a five-step process for modelling the influencing uncertainties and the impact of these uncertainties on the price bid. We will present the background need for such analysis and then provide an overview of our approach and findings to date. Finally, using an exemplar service we will demonstrate how using our approach highlights the probability of winning the contract, the probability of making a profit and the expected profit value for particular price bids
