ABSTRACT.
Military acquisition programs have long been criticized for the exponential growth in development costs required to generate modest improvements in capability. One of the most promising reform efforts to address this trend is the open system architecture initiative, which uses modular design principles and commercial interface standards as a means to reduce the cost and complexity of upgrading systems over time. While conceptually simple, this effort has proven to be exceptionally difficult to implement in practice. This difficulty stems, in large part, from the fact that open systems trade additional cost and risk in the early phases of development for the option to infuse technology at a later date, but the benefits provided by this option are inherently uncertain. Practical implementation therefore requires a decision support framework to determine when these uncertain, future benefits are worth the cost and risk assumed in the present, but there is ample evidence to suggest that existing design methods are insufficient to address this need. The objective of this research is to develop a Military Acquisition INspired FRamework for Architecture Modeling and Evaluation that resolves this gap by providing an approach to measure the expected costs, benefits and risks associated with open systems. This work is predicated on three assumptions: (1) the purpose of future technology infusions is to keep pace with the uncertain evolution of operational requirements, (2) successful designs must justify how future upgrades will be used to satisfy these requirements, and (3) program managers retain the flexibility to adapt prior decisions as new information is made available over time. With that in mind, this methodology proposes a new technique for codifying operational requirements as a capability road map, as opposed to the “worst case” scalar values used in classical design methods. xvi A novel adaptation of existing technology forecasting techniques is then proposed as a means to determine how future technological improvements could be used to efficiently satisfy the needs expressed in this road map, and a new performance measure is proposed to quantify the relative value of alternative refresh strategies. Finally, a series of decision support heuristics inspired by methods in the field Real Options are integrated with an automated search procedure to identify strategies that facilitate flexible decision making as a hedge against uncertainty. The proposed methodology is then applied to an example scenario for an aerial Intelligence, Surveillance, and Reconnaissance platform with the potential to upgrade its sensor suite in future increments. The capability road map for this scenario is adapted from real world trade studies performed by the Department of Defense’s Information Dominance team, and the forecasting model is developed by evaluating technological progression in commercial image processing technology over the last decade. Specific questions addressed in this study are how the timing and selection of future technology infusions should be structured to best satisfy alternative preferences for cost, performance, and risk. In addition, the study demonstrates that the relative advantages and drawbacks, in terms of the performance metrics developed in this work, between open and integrated system architectures can be presented in the context of a cost-effectiveness framework that is currently used by acquisition professionals to manage complex design decisions. This experiment concludes with the observation that the proposed methodology can objectively identify and aggregate the myriad of factors impacting an arbitrary open system design problem into a single, intuitive visualization. As this capability is lacking in existing methods, it lends considerable support to the thesis that the proposed methodology is a superior approach.
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