Performance-based contracting is reshaping service support supply chains in capital intensive industries such as aerospace and defense. Known as Power by the Hour in the private sector and as Performance-Based Logistics (PBL) in defense contracting, it aims to replace traditionally used …xed-price and cost-plus contracts in order to improve product availability and reduce the cost of ownership by tying a supplier's compensation to the output value of the product generated by theTo analyze implications of performance-based relationships, we introduce a multitask principalagent model to support resource allocation and use it to analyze commonly observed contracts. In our model the customer (principal) faces a product availability requirement for the "uptime"of the end product. The customer then o¤ers contracts contingent on availability to n suppliers (agents) of the key subsystems used in the product, who in turn exert cost reduction e¤orts and set spare parts inventory investment levels. We show that the …rst-best solution can be achieved if channel members are risk-neutral. When channel members are risk-averse, we …nd that the second-best contract combines a …xed payment, a cost-sharing incentive, and a performance incentive. Furthermore, we study how these contracts evolve over the product deployment life cycle as uncertainty in support cost changes. Finally, we illustrate the application of our model to a problem based on aircraft maintenance data and show how the allocation of performance requirements and contractual terms change under various environmental assumptions.The authors are grateful to the seminar participants at the Wharton School, Cornell University, University of Texas at Dallas, University of Washington, Columbia University, UC Berkeley, and Naval Postgraduate School for helpful discussions. The authors would also like to acknowledge input from L. Gill, S. Gutierrez, M. Lebeau and M. Mendoza, who provided valuable information concerning current practices. Finally, the authors are grateful for the assistance of Ashish Achlerkar of MCA Solutions, who provided valuable assistance in testing the model and providing access to a real-world data set.

Reduction of new product development cycle time and improvements in product performance have become strategic objectives for many technology-driven firms. These goals may conflict, however, and firms must explicitly consider the tradeoff between them. In this paper we introduce a multistage model of new product development process which captures this tradeoff explicitly. We show that if product improvements are additive (over stages), it is optimal to allocate maximal time to the most productive development stage. We then indicate how optimal time-to-market and its implied product performance targets vary with exogenous factors such as the size of the potential market, the presence of existing and new products, profit margins, the length of the window of opportunity, the firm's speed of product improvement, and competitor product performance. We show that some new product development metrics employed in practice, such as minimizing break-even time, can be sub-optimal if firms are striving to maximize profits. We also determine the minimal speed of product improvement required for profitably undertaking new product development, and discuss the implications of product replacement which can occur whenever firms introduce successive generations of new products. Finally, we show that an improvement in the speed of product development does not necessarily lead to an earlier time-to-market, but always leads to enhanced products.new product development, time-to-market, new product performance

Motivated by a study of the logistics systems used to manage consumable service parts for the U.S. military, we consider a static threshold-based rationing policy that is useful when pooling inventory across two demand classes characterized by different arrival rates and shortage (stockout and delay) costs. The scheme operates as a (Q, r) policy with the following feature. Demands from both classes are filled on a first-comefirst-serve basis as long as on-hand inventory lies above a threshold level K. Once on-hand inventory falls below this level, low priority (i.e., low shortage cost) demand is backordered while high priority demand continues to be filled. We analyze this static policy first under the assumption that backorders are filled according to a special threshold clearing mechanism. Structural results for the key performance measures are established to enable an efficient solution algorithm for computing stock control and rationing parameters (i.e., Q, r, and K). Numerical results confirm that the solution under this special threshold clearing mechanism closely approximates that of the priority clearing policy. We next highlight conditions where our policy offers significant savings over traditional 'round-up' and 'separate stock' policies encountered in the military and elsewhere. Finally, we develop a lower bound on the cost of the optimal rationing policy. Numerical results show that the performance gap between our static threshold policy and the optimal policy is small in environments typical of the military and high technology industries.

In this paper, we develop a stochastic dynamic programming formulation for the valuation of global manufacturing strategy options with switching costs. Overall, we adopt a hierarchical approach. First, exchange rates are modeled as stochastic diffusion processes that exhibit intercountry correlation. Second, the firm's global manufacturing strategy determines options for alternative product designs as well as supply chain network designs. Product options introduce international supply flexibility. Supply chain network options determine the firm's manufacturing flexibility through production capacity and supply chain network linkages. Third, switching costs determine the cost of operational hedging, i.e., the costs associated with reducing downside risks. Overall, the firm maximizes its expected, discounted, global, after-tax value through the exercise of product and supply chain network options and/or through exploitation of operational flexibility contingent on exchange rate realizations. In this environment, the firm must trade off fixed operating costs, switching costs, and the economic benefits derived from exploiting differentials in factor costs and corporate tax rates. A multinomial approximation of correlated exchange rate processes is proposed that leads to a consistent and tractable lattice model for this compound option valuation problem. We then demonstrate how the global manufacturing strategy planning model framework can be utilized to analyze financial and operational hedging strategies.

This paper presents a comprehensive model framework for linking decisions and performance throughout the material-production-distribution supply chain. The purpose of the model is to support analysis of alternative manufacturing material/service strategies. A series of linked, approximate submodels and an heuristic optimization procedure are introduced. A prototype software implementation is also discussed.