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The Benefits of Integrated, Quantitative Risk Management

机译:集成的量化风险管理的好处

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There is no question that risk management (RM) has a value much greater than its financial cost for implementation. Hall reports return on investments (ROIs) on the order of 20-1. While our experience supports this finding, we believe that the return would be much higher given comprehensive metrics. To date, we have been unable to compile metrics as Hall has done because of the collateral effects that occur in application. Thus, we cannot calculate the true cost avoidance based solely on the application of risk management. This occurs because our approach is intense, focused on quantitative analysis, and designed to produce risk-based decision support information for decision-makers. We have dubbed the process risk-based decision support, (RBDS). A particular characteristic of RBDS is the requirement that an 'integrated' result be presented to the decision-maker. That is, the decision-maker must have a result that integrates the various risk factors (i.e., cost, schedule, technical, mission, etc.) into a single, consistent, parameter for decision-making -usually cost.rnThe execution of such a risk management process means stringent demands for quality information are levied on projects. In fact, the coincidental discovery of deficient information during the process has yielded the greatest benefit to programs we have supported with RBDS.rnQualitative techniques typically result in subjective risk estimates of likelihood and consequence such as high, medium, and low. Our intent is not to be critical of qualititative techniques; as a matter of fact, we use them. Furthermore, we find great value in qualitative processes, as they yield quick and efficient communication of risk issues across the program/project.rnHowever, we always go one step further. We implement a triage procedure to discriminate the 'high' risks that require further analysis using quantitative techniques. These quantitative techniques demand quality information from within the program. Typically, examples of deficient information discovered in our application of RBDS include low-quality program plans, poor cost estimation, missing project elements, inconsistent integrated master plans and integrated master schedules, poor system-level requirements, and unstable requirements. Each of these deficienciesrnthemselves constitutes a risk to the program.rnIn the following pages, we present a discussion of these management risks and how their identification has contributed to the success of numerous programs and projects. For some of our cases, we will provide semi-quantitative judgments about the ROIs for RM.
机译:毫无疑问,风险管理(RM)的价值远远大于其实施的财务成本。 Hall报告的投资回报率(ROI)为20-1。尽管我们的经验支持这一发现,但我们认为,如果采用综合指标,回报率将会更高。迄今为止,由于应用程序中发生的附带影响,我们无法像Hall一样编译度量标准。因此,我们不能仅基于风险管理的应用来计算避免实际成本。发生这种情况的原因是我们的方法非常严格,专注于定量分析,旨在为决策者提供基于风险的决策支持信息。我们将其称为基于过程风险的决策支持(RBDS)。 RBDS的一个特殊特征是要求将“综合”结果提供给决策者。也就是说,决策者必须具有将各种风险因素(即成本,进度,技术,任务等)整合到一个单一,一致的决策参数(通常是成本)中的结果。风险管理过程意味着对项目征收严格的质量信息要求。实际上,在过程中偶然发现不足的信息为我们使用RBDS支持的程序带来了最大的好处。定性技术通常会导致对可能性和后果(如高,中和低)的主观风险估计。我们的意图不是批评定性技术。事实上,我们使用它们。此外,我们在定性过程中发现了巨大的价值,因为它们可以在整个计划/项目中快速有效地传达风险问题。但是,我们始终走得更远。我们执行分类程序以区分需要使用定量技术进行进一步分析的“高”风险。这些定量技术需要程序内部提供质量信息。通常,在我们的RBDS应用程序中发现的信息不足的示例包括质量低劣的计划计划,糟糕的成本估算,丢失的项目元素,集成的总体计划和集成的总体计划不一致,系统级别的需求不佳以及需求不稳定。这些缺陷本身都会给该计划带来风险。在接下来的几页中,我们将讨论这些管理风险以及如何识别这些风险如何促进众多计划和项目的成功。对于我们的某些情况,我们将提供有关RM的ROI的半定量判断。

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