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Suitability deficiencies have been responsible for many of the field problems with newly acquired systems and have generated concerns about the operational readiness of certain military capabilities. Concern about the department's success in fielding suitable systems was expressed in an October 1990 memorandum from the Deputy Undersecretary of Defense for Acquisition. A 1992 Logistics Management Institute review of seven recently fielded systems found that "several systems have not achieved their availability goals, and they consume significantly more logistics resources than anticipated" (Bridgman and Glass, 1992:ii). That study also found that crucial suitability issues are not adequately identified early, or addressed in operational test plans. Such concerns and findings have led to calls for improved assessment of operational suitability. In this chapter, we discuss statistical issues related to the conduct of operational suitability tests and their evaluations and related information-gathering activities.
SUITABILITY, TESTING AND EVALUATION, AND STATISTICS
In considering the role of statistical methods and principles in the assessment of operational suitability, it is important to establish first the context of suitability assessment and its relationship to operational test and evaluation. The judgment that a system is "suitable" implies confirmation that the system's use can be adequately supported in its anticipated environments. A comprehensive study of a system's suitability should include, for example, considerations such as its compatibility with other systems in current use, transportability, supportability (in terms of logistics and manpower), reliability, availability, and maintainability. A definitive suitability assessment addresses all of these matters, reporting both on the outcomes of formal tests and on informal observations and judgments made by those charged with the system's evaluation.
The suitability of a system should be assessed from early development through fielding, even though all elements of suitability may not be demonstrable at all times. The reliability of key equipment, especially critical components, can be demonstrated relatively early in a system's development, but some questions about logistics supportability can only be definitively answered after a system is fielded. Because the assessment of suitability after an operational test is performed is limited by the scope of such testing, it may be desirable to augment the test results with modeling and simulation, test and field data from other sources, and related analyses.
The challenges faced in designing and interpreting results of operational tests underscore the need for, and the potential value of, applying sound statistical methodology. For virtually every aspect of operational suitability, fundamental statistical questions arise concerning the duration and conditions of testing, the measurement and processing of suitability data, and the use of information from other sources, such as developmental tests and simulation models, in the design and subsequent analysis of operational tests. Possible test augmentation proce