Development of the Army Facility Mission Dependency Index for Infrastructure Asset Management

Abstract

This report describes a Mission Dependency Index (MDI) developed for U.S. Army facility asset management. The MDI is an indicator of mission-related importance of Army infrastructure elements to be used for the purpose of providing more effective local prioritization of facilities for sustainment, restoration, and modernization (SRM) actions. It does this by evaluating the mission impact of interrupting a function or relocating where it is provided. The index is reported on a scale of 0-100, and is analogous in that respect with existing Corps of Engineers Sustainment Management System (SMS) indices. As part of this work, an MDI methodology directly fit to Army-specific missions, facility resource capabilities, and organizational structure was developed. This was accomplished through a pilot implementation at White Sands Missile Range. The objectives of the demonstration were to identify Army-specific MDI criteria, develop a standardized implementation process, determine the steps for integrating MDI information into garrison-level and Army-level facility management business processes, and identify considerations and requirements for incorporating Army MDI criteria into the BUILDER ® SMS. The results of an MDI analysis, as facilitated using the implementation and integration procedures recommended here, will enable facility decision makers to focus on infrastructure most critical to mission effectiveness.

Energy Resilience Impact of Supply Chain Network Disruption to Military Microgrids

“…Instead, the DoD uses Mission Dependency Index (MDI) to distinguish between critical and non-critical facilities aboard military installations [82]:…”

Prioritizing facilities linked to corporate strategic objectives using a fuzzy model

“…Large, multi-location and multi-objective organizations such as the Department of Defense (DoD) and NASA have prioritized large project portfolios using traditional riskbased metrics to link facilities to strategic organizational objectives (Amekudzi and McNeil, 2008). Each has chosen to implement semi-quantitative traditional risk matrices with discrete categories as a means of simplifying the complexity of consistently evaluating a large number of facilities across multiple operating locations with unique missions (Antelman and Miller, 2002;Grussing et al, 2010;Savatgy et al, 2019). Semi-quantitative risk matrices produce ordinal numbers, which the DoD and NASA have arithmetically transformed to understand vulnerable facilities on their campuses and prioritize facility projects at multiple organizational levels (Amekudzi and McNeil, 2008;Kujawski and Miller, 2009).…”

“…The fuzzy logic system used the consequence of failure as the output category. The output category was divided into five membership functions to match the commonly classified MDI risk categories established by the Navy and Army (Amekudzi and McNeil, 2008;Grussing et al, 2010). The risk levels determined each category's boundaries and the range of values was set from [0,100] to match the existing TMDI score range.…”

Articulating the Effects of Infrastructure Resourcing on Air Force Missions: Competing Approaches to Inform the Planning, Programming, Budgeting, and Execution System

“…), and can the mission be moved elsewhere (is it impossible or easy)? The Navy 18 and Army (Grussing et al, 2010a) use extremely detailed MDI assessments, populated by structured interviews with stakeholders, including weights assigned to the various elements of the metric (NRC, 2012).…”