Minimizing the Risk of Shortfall in Cash Flow for Long-Term Service Agreements Provision

Introduction

Long-term service agreements (LTSAs) for the maintenance of capital-intensive equipments, such as, gas turbines, medical equipments, aircraft and locomotive engines, have been gaining wide acceptance over the recent years. A typical LTSA contract, spanning a period of 5-20 years, makes a provider responsible for fully maintaining customers’ equipments. Effective management of LTSAs is important, since these equipments are vital to the basic infrastructure and the economy of a country. A framework which helps the provider understand and quantify the multi-dimensional risk exposures underlying the service agreements is essential (Gupta, Wallace, & Sondheimer, 2008). The strategic operations management of LTSAs is similar to three different problems addressed in the literature, the machine replacement problems, the maintenance scheduling problems, and the inventory pooling problems.

The machine replacement problem deals with replacing an old machine with a new one. As a machine gets older, it is costlier to operate it both from operational and maintenance cost perspectives. It may be more cost-effective to replace the old machine by a new one after the machine reaches a certain age. The maintenance scheduling problem addresses the trade-off between preventive maintenance and corrective maintenance in order to develop an optimal maintenance schedule that minimizes the total cost. The inventory pooling problem determines optimal inventory levels to maintain in order to have minimal back-orders, holding cost, and transportation cost. Strategic operations management for the delivery of a portfolio of LTSAs needs to combine these three problems. Parts of a product on which an LTSA is extended should be replaced as they get old, increasing their likelihood of breakdown. This is similar to the machine replacement problem. However the product, being high-cost and long-lived, are used for the entire contract duration. The products undergo inspections and maintenance, without being fully replaced, resembling the maintenance scheduling problem. A level of inventory is maintained by the provider to support the maintenance activities of the LTSAs, similar to the inventory pooling system, where a minimal level of inventory is maintained at each repair facility so that the cost of transportation, back-order and holding cost is minimized.

The framework should be capable of integrally combining strategic, operational, engineering reliability and maintenance, and financial risks of the service through the extended duration of contracts’ maturity for it to be useful. Previous research by Gupta and Lawsirirat (2006, 2010) focus on the analysis of engineering reliability and maintenance, however, they do not extend their framework to study possible financial risks of the provider. It is not enough to focus only on the engineering aspects of the strategic and operational risks, since this will not completely account for cash flow risks or financial risks which directly affect the viability of the provider.

The risk of cash flows can arise due to a mismatch between costs and revenues. The provider collects its revenue/service fees, as insurance providers collect premiums, at a regular interval, and needs to incur costs of the service as they appear, which is stochastic. The risk of shortfall in cash flows occurs when the costs exceed or are mismatched with the revenue received. As a result, the provider may experience undesirable shortfalls in cash flows for supporting the service and may not be able to maintain the necessary level of service as per the contract terms. There are several causes for shortfalls in cash flow. The provider may have underestimated its costs, and hence misprice the service, or the cost may be incurred in lump-sums when breakdowns occur or in large lump-sums due to extreme failure events. Therefore, shortfalls can occur despite the provider utilizing an optimal service delivery strategy, even though an optimal service delivery strategy will generate more accurate estimates of the total costs, and appropriately designed revenue models will attempt to minimize some financial risks. There may still be residual financial risk due to inherent multi-dimensional uncertainties in the delivery of the service and stochastic, lumpiness of costs. Too frequent shortfalls can lead to significant deterioration in service, higher penalty fees, fewer customers, and more frequent extreme losses due to failures of the equipment, which can eventually lead to bankruptcy.