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Incorporating risk and flexibility into shipboard systems Establishing a reference class

机译：将风险和灵活性纳入船上系统建立参考等级

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Schedule performance of new ship construction and major weapon system programs remains a challenge with operational capability delivery averaging a 37.7% delay, according to the U.S. Government Accountability Office's (GAO) 2018 annual assessment. To mitigate this, future programs must de-risk design, development, and production schedules through data-driven approaches based on realized prior program histories to prevent optimism bias, which has historically contributed to cost growth and key capability delays.Previous efforts to estimate future weapon system schedules have attempted to regress schedule durations against programs' technical characteristics to develop parametric schedule estimating relationships (SERs). Despite methodical and rigorous regression analyses, the high variability in program schedules, even for similar programs, precluded the development of any statistically meaningful SERs. While no trends for schedule durations exist across programs, technical characteristics, or timelines, these past program schedules, taken as a whole, can serve as analogies for future programs to provide a more data-driven approach to schedule estimating.Using datasets of major milestone dates and schedule durations for multiple commodities produced as part of the SER development efforts, the authors will discuss how the naval engineering community can (a) identify an analogous reference class of past, similar programs;(b) establish a probability distribution from selected programs for the schedule duration being forecast; and (c) compare specific programs with analogous reference class distribution in order to establish the most likely outcome for the specific program. Ultimately, the use of comprehensive, curated datasets and descriptive statistics will provide insights to the naval engineering community regarding the implications of schedule dependencies and refine parsimonious models to more accurately forecast schedule performance for current and future programs.
机译：根据美国政府问责局（GAO）2018年度评估，新船建造和主要武器系统计划的进度性能仍然是一项挑战，其作战能力交付平均延迟37.7％。为了缓解这种情况，未来的计划必须通过基于已实现的先前计划历史的数据驱动方法来降低设计，开发和生产进度表的风险，以防止乐观主义的偏见，而这种偏见在历史上曾导致成本增长和关键能力延迟。武器系统时间表已尝试根据程序的技术特征来退回时间表的持续时间，以开发参数化的时间表估计关系（SER）。尽管进行了有条理和严格的回归分析，但是即使在类似的程序中，程序进度表的高度可变性也阻止了任何具有统计学意义的SER的开发。尽管没有跨计划，技术特征或时间表的进度计划持续时间趋势，但这些过去的计划进度表作为一个整体可以用作未来计划的类比，以提供更多以数据为依据的计划进度估算方法。作为SER开发工作的一部分，生产的多种商品的日期和时间表持续时间，作者将讨论海军工程界如何（a）识别过去类似程序的类似参考类别;（b）从选定程序中建立概率分布预计的时间表持续时间; （c）比较具有类似参考类别分布的特定程序，以便为特定程序确定最可能的结果。最终，使用全面的精选数据集和描述性统计数据将为海军工程界提供有关计划依存关系的见解，并精简简约模型以更准确地预测当前和未来计划的计划执行情况。

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