Military Jet Engine Acquisition Technology Basics and Cost-Estimating Methodology

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Military Jet Engine Acquisition Technology Basics and Cost-Estimating Methodology ( military-jet-engine-acquisition-technology-basics-and-cost-e )

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42 Military Jet Engine Acquisition estimate. Some companies have automated the process by creating sophisticated database tools, but these systems can be quite expen- sive to develop. A second drawback of the bottom-up approach is that the analyst must be an expert in the design of the technology being employed. Specific design details must be considered to apply the method correctly. The user (i.e., cost estimator) must also under- stand design tradeoffs and the current state of technology. A third disadvantage is that the system must be well defined—there is little allowance for unknown factors. For example, a component’s cost must be estimated even though that component might represent a first-of-a-kind technology. Finally, the user of the bottom-up ap- proach must have access to, or maintain an extensive and detailed database of, development, production, and operating and support costs for the particular technology. ESTIMATING BY ANALOGY A related approach to the bottom-up method is to estimate by anal- ogy. With this approach, an analyst selects a system that is similar to or related to the system undergoing the cost analysis and makes ad- justments for the differences between the two systems. This ap- proach works well for derivative or evolutionary improvements. Its main advantage over the bottom-up approach is that only the changes or differences must be estimated—thus saving time. How- ever, a good starting baseline must exist to apply the method suc- cessfully. For radical changes or new technologies, the bottom-up approach is clearly the better choice. As with the bottom-up ap- proach, the analyst must have a thorough knowledge of the applica- ble technology to employ the estimate by analogy approach. ESTIMATING BY PARAMETRIC METHOD A third approach that is quite different from the first two uses para- metric methods to forecast outcomes. Parametric methods are based on a statistical technique that attempts to explain the dependent variable (e.g., cost, development schedule) as a function of several other variables, such as intrinsic engine characteristics (e.g., size, technical characteristics, features, risk measures), which are the in- dependent (or explanatory) variables. The relationships between

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