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The DoD has frequently demonstrated its ability to procure phenomenal systems; however, these accomplishments are often tarnished by substantial cost and schedule overruns. While defense acquisition policies are continually being revised to address these perennial problems, many believe that a more fundamental source of these overruns is the lack of flexibility in the systems being developed, which tend to preclude effective responses to unexpected events. However, providing justification to invest in flexibility is a tough sell when the measure of value is a military capability or political outcome, as there is no extant method to demonstrate the potential return on investment. This paper introduces a decision tool for valuing the inherent ability of different systems or designs to respond to uncertainty. The proposed tool is essentially a modification of the current life cycle cost model and is premised on the notion that the need for capability changes in a system arises in a stochastic manner that can be incorpo- rated into a continually updated, expected value model presented in terms of total life cycle cost. The cost-based decision tool presented here quantifies the ability of competing designs to respond to these capability changes via a cumulative distribution function (CDF). The design with the most favorable CDF (i.e., the one that is most likely to meet the most likely set of require- ments at the lowest expected value curve of life cycle cost) is deemed to be the “best” design.


This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. CC BY-NC-ND 3.0

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Procedia Computer Science