Using Analytical Network Process Decision Methodology to Analyze and Allocate Resources in the U.S. Army Training Support System

Using Analytical Network Process Decision Methodology to Analyze and Allocate Resources in the U.S. Army Training Support System

Rafael Diaz, Barry Charles Ezell
DOI: 10.4018/joris.2012070104
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Deciding on an appropriate training solution mix at the strategic level of U.S. Army training support system enterprise to support warfighter preparation is a complex matter. One of the most important problems is integrating qualitative and quantitative multiple sources of influential information. There are many goals to accomplish while they are constantly changing. However, the best training solution mix option that both minimizes resource impact and maximizes training throughput must be selected. The objective of this paper is to introduce a decision-making methodology based on the Analytical Network Process (ANP) for the U.S. Army Training Support System (ATSS). The methodology assists in the evaluation of training alternatives to help strategic decision makers to select the best mix of training components and strategies. An application of the proposed methodological framework is performed in real world example. The problem involves deciding the right mix of training solutions for urban operation training among a group of selected options.
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The U.S. Army Training Support System (ATSS) is an enterprise that provides networked, integrated, interoperable training support necessary to enable an operationally relevant training environment for warfighters. The training support system (TSS) is the platform that organizes and configures the different components and activities that provide and enable training support. It provides the means for the development, delivery, management, and resource allocation necessary for training support capabilities (TSS, 2007). As the enterprise that provides such training support, in regular basis, the TSS makes resource allocation decisions that affect training throughput.

Several features characterize the decisions-making environment at this strategic level of this enterprise. As indicated by Dryer and Chalkley(2005), this environment is characterized for permanent changes in operations, acquisition of new equipment and supplies capabilities, herein called materiel as in the military context, personnel requirements and skill sets, and in land and facilities characteristics. The dynamics of this setting requires effective and flexible solution design methods that consider new training capabilities as well as the development of new opponent abilities. These methods must include mechanisms that examine the effects of training strategies, plans, and resource allocation on Doctrine, Organization, Training, Materiel, Leadership and Education, Personnel and Facilities (DOTMLPF), the so-called DOTMLPF Analysis.

In general, enterprises viewed from the strategic perspective are complex systems that have a large number of parts, with significant interactions, nonlinearities, interdependent, and are asymmetric in nature. Many problems arise from making decisions in these contexts. In most cases, decisions are affected by critical factors that include the degree of the relationships among system components, the number and level of interactions among components, and the relationships with exogenous environments. These factors drastically influence the performance of the enterprise when deciding the best course of actions given a pool of competing options.

Designing and selecting training solutions in the ATSS environment is a difficult task. The number of components and relationships involved in this process as well as the resource required to design, choose, and implement different training solutions has a substantial effect on the performance of this enterprise. To address the complexities associated to performing this task, a methodological framework that considers these factors is required.

This paper suggests using the Analytic Network Process (Saaty, 2001) as the center of a suggested methodological framework to assist in the strategic decision-making process that takes place in the ATSS environment. ANP is defined as a non-linear network relationship approach that allows modeling complex environments that characterize the organizational level of the enterprise (Meade & Sarkis, 1998). It considers the complexities associated to dealing with multiple actors, in view of numerous and conflicting criteria, and component interdependency that are permanently present in the ATSS decision environment.

Given the impact of designing and selecting training solutions task on ATSS performance, the application of ANP in this paper is focused on evaluating a set of potential training configurations that satisfy a collection of constrained criteria. This study adapts the case of Urban Operations (UO) training referenced by Dryer and Chalkley (2005) to demonstrate how the ANP can improve the decision-making process in selecting the best training solution on a military setting. In particular, this paper presents how ANP may be used to evaluate a discrete number of competing alternatives while considering and capturing the complexities associated to the training planning process.

This study and its results are important for the following reasons:

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