A Fuzzy Inference-Based Facility Prioritization Decision Support System for Complex Hierarchical Organizations

Abstract

ABSTRACT Safeguarding limited resources for an organization's most critical assets can be difficult when decision-makers at different corporate hierarchy levels have different objectives and needs. Prioritizing resources in a manner that aligns with the organization's strategic goals requires expertise and knowledge at all corporation levels. DePalmer et al. (2021) explored the opportunity to quantify the relationship between facilities and the operations they support using a Mamdani fuzzy inference system. This research extends the previous work by incorporating multi-level perspectives of the facilities and the operations they support outside of the tactical campus. Additionally, the authors simulated various risk attitudes to investigate how subjective inputs at the tactical level can affect strategic-level outputs. This research produces a framework that aggregates junior-level facility knowledge depth with the breadth of senior-level operational and strategic knowledge to support decision-making for facility project prioritization. An additional prediction boundary is created from the risk attitude variance and can give portfolio managers data-driven tools for quality control of risk profiles at individual campus locations.