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Quantitative Risk Management - Risk Informed Decision Making on High-Risk Waste Remediation Projects-19022

机译:定量风险管理 - 高风险废物修复项目的风险信息 - 19022

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For every $1 billion invested in projects, $97 million is wasted due to poor project performance. That means 9.7% of money spent on projects is wasted due to poor risk and uncertainty management. Highrisk projects, similar to those in waste remediation, have the most to lose. A solid quantitative risk management program is one of the keys to increasing the likelihood that a project will succeed. A quantitative risk program solves two major problems that challenge the effective management of risk and uncertainty: 1. Risks arise at all levels of an organization; however, not all organizational levels have an effective way to identify and resolve them. This can lead to risks that, even if identified, are not, reported. 2. Decision-makers are often forced to operate solely on intuition when implementing mitigation. strategies, not fully understanding the effects that certain decisions have on the program's cost and schedule. A quantitative risk program uses a risk register and builds it into the project/program integrated schedule to assess the impact of these risks, typically at the 80% confidence contingency level for specific milestones and/or project completion. Implementing a quantitative risk program drives a forward-thinking, proactive mentality to problem solving into all levels of the organization. A healthy risk program for regular reporting and communication ensures that all members of an organization are thinking about risks and using their communication channels to resolve them. It gives a method of communication and incentive for all levels in the organization and helps to ensure that risks will be reported and resolved. Pacific Northwest National Laboratory (PNNL) has developed tools and methods that provide a level of realism for analyzing different scenarios and estimating contingency that does not exist in the standard industry risk toolkit. These tools and methods provide decision-makers with actionable, quantitatively based information to guide their decision making. The first tool is a probabilistic branching risk model for mitigation strategies. Current quantitative risk analysis tools in the industry simulate two cases: fully mitigated and un-mitigated. In the fully mitigated case, the user assumes that every planned mitigation activity is successful. In the un-mitigated case, the user assumes that none are successful. The truth lies between these two extremes. The PNNL team has developed a probabilistic risk model for mitigation scenarios that includes a probability that a mitigation activity will succeed and a probability that a mitigation action will be funded. These probabilities are elicited from subject matter experts and ensure that the contingency calculations at the specified confidence are approaching reality. The second tool developed at PNNL is the Risk Box, which is a tool that integrates with different scenarios in the risk register. For example, say the user is faced with two different and mutually exclusive mitigation actions to reduce a risk. The Risk Box methodology performs the contingency calculations and then displays them on a time-phased graph that shows how each scenario reduces the risk contingency needed on the project/program. This graph then provides quantitative information to show decision-makers which mitigation action provides the greatest reduction (cost and schedule) in risk contingency for the program. Implementing these and other tools within a structured risk program increases the likelihood that a project will come in on schedule and budget, ensures that all personnel are proactively thinking about problems and resolutions, creates communication channels for all members to submit and resolve potential problems, produces a prioritized list of risk rankings to focus leadership on issues that may cause the biggest problems, and implements processes that drive updates to the risk program as the risk profile changes. PNNL has been developing these methods and using them on pr
机译:对于投资的每10亿美元投资,由于项目绩效较差,浪费了9700万美元。由于风险差和不确定性管理,这意味着在项目上花费的资金的9.7%。 HighRisk项目类似于废物修复的项目,最重要的是失去。纯粹的定量风险管理计划是增加项目将成功的可能性的钥匙之一。定量风险计划解决了挑战风险和不确定性的有效管理的两个主要问题:1。在组织各级出现风险;但是,并非所有组织级别都有有效的方法来识别和解决它们。报告,这导致风险,即使识别,也没有报告。 2.在实施缓解时,决策者通常被迫单独运作直觉。策略,并不完全了解某些决策对计划的成本和时间表的影响。定量风险计划使用风险登记册并将其建立在项目/方案综合计划中,以评估这些风险的影响,通常在特定里程碑和/或项目完成的80%置信抵情水平上。实施量化风险计划推动前瞻性思维,积极的心态来解决组织各级的问题。定期报告和沟通的健康风险计划可确保组织的所有成员正在考虑风险并使用其沟通渠道来解决它们。它为组织中的各个层面提供了一种沟通和激励的方法,并有助于确保将报告和解决风险。太平洋西北国家实验室(PNNL)开发了制定的工具和方法,为分析不同情景和估算标准行业风险工具包中不存在的估算应急提供了一种现实主义的工具和方法。这些工具和方法为决策者提供了可操作,总基的信息,以指导其决策。第一个工具是缓解策略的概率分支风险模型。行业的当前定量风险分析工具模拟两种情况:完全减轻和不缓解。在完全缓解的情况下,用户假定每种计划缓解活动都是成功的。在不缓解的情况下,用户假定没有成功。真相位于这两个极端之间。 PNNL团队制定了一个概率的风险模型,用于缓解场景,包括减缓活动将成功的概率,并且减缓行动将被资助的可能性。这些概率由主题专家引发,并确保指定信心的应急计算正在接近现实。在PNNL开发的第二个工具是风险框,它是一个与风险寄存器中不同场景集成的工具。例如,假设用户面临两种不同和相互排除的缓解动作,以降低风险。风险框方法执行了应急计算,然后在时间相控的图表上显示它们,该图显示了每个场景如何降低项目/程序所需的风险应急情况。然后,该图提供了定量信息,以显示减缓行动的决策者提供了该计划风险应急的最大减少(成本和计划)。在结构化风险计划中实施这些和其他工具增加了项目将在计划和预算中进入的可能性,确保所有人员都积极思考问题和决议,为所有成员提交和解决潜在问题的沟通渠道创造了沟通渠道,产生优先考虑的风险排名列表,以缩影可能导致最大问题的问题的领导,并实现在风险配置文件变更作为风险计划的更新的过程。 PNNL一直在开发这些方法并在PR上使用它们

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