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

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. DOI: 10.4018/joris.2012070104 54 International Journal of Operations Research and Information Systems, 3(3), 53-73, July-September 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. makes resource allocation decisions that affect training throughput. Several features characterize the decisionsmaking 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: 1. They expand the very limited literature on ANP application in the military training support system domain, specifically in the U.S. ARMY. This should stimulate research into the application of ANP in other complex military learning environment. In these environments, soldiers have to develop a large number of skills that are critical for their survival and performance. As complex enterprises, military organizations that organize, articulate, and perform military training are obligated to provide efficient and effective training solutions. These solutions are designed to maximize responsiveness in terms of training throughput while guarantying certain standard levels. Further, in this very constrained environment, the design and 19 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/article/using-analytical-network-processdecision/69178?camid=4v1 This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Business, Administration, and Management. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2