Purpose

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

Design/methodology/approach

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Findings

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

Originality/value

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

中文翻译：

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使用模糊模型优先考虑与企业战略目标相关的设施

目的

有限的设施运营和现代化预算要求组织仔细识别、优先考虑和授权项目，以确保分配的资源与战略目标保持一致。可以改进使用风险矩阵的传统设施优先级排序方法，以增加分类的粒度并避免数学错误或人类认知偏差。这些限制限制了优先排序的效用，如果错误地用于选择资助项目，它们可能会导致资源浪费。本文旨在提出一种新的设施优先排序方法，以纠正这些评估设计和实施问题。

设计/方法/方法

Mamdani 模糊逻辑推理系统与传统的分类风险评估框架相结合，以了解设施故障的后果及其对组织战略目标的影响。模型性能是使用美国空军的设施组合进行评估的，该组合先前已被评估，将设施可复制性和可中断性视为最小化目标。建立模糊逻辑推理系统以考虑这些目标，但作为易于适应的证明，添加了设施依赖性作为额外的风险评估标准。

发现

基于模糊逻辑的方法的结果显示出与传统方法的高度一致性，尽管此处开发的框架提供的信息的价值要高得多，因为它创建了一组连续的、无偏见的设施优先级。模糊逻辑框架可能适合由不同的、空间分布的组织实施，在这些组织中，决策者寻求平衡风险评估的复杂性和输出值。

原创性/价值

本文满足了对项目组合管理策略的确定需求，这些策略侧重于根据组织运营或目标的风险对项目进行优先排序。