Defense Transportation System and Supply Chain Management Reform

Introduction

Distribution managers need to appreciate that management of defense supply chains is a rapidly growing global phenomenon, with overlap existing across management levels — from strategic national-level stakeholders to lower sustainment units at the activity level. Strategic distribution changes have the potential to immensely impact tactical operations. This paper aims to convey a few important precepts required for globally responsive logistics decisions. Distribution and material managers ought to review and internalize defense supply chains early in their careers.

The process of distribution is complex. Thus, material distribution management must include electronically sustainable supply-chain information systems for achieving true synchronization. Defense transport systems are complex adaptive systems (CASs) — they integrate comprehensive, dynamic components and encompass complex supply-network systems together with their co-evolutionary, dynamic processes. The CAS approach can provide insight for understanding the co-evolution of supply networks and their dynamic nature, as the approach incorporates built-in systems and their inherent complexity. The overall contribution of this paper is toward strengthening the theoretical argument of research works that have dealt with CAS and related supply chain subjects.

Analyzing broader levels such as supply chain systems can be useful, since supply networks' evolutionarily active nature may be considered analogous to CASs. It is necessary for practitioners to consider the complicated logic surrounding the management of supply networks. In this context, System Dynamics, reverse logistics, and feedback mechanisms may prove quite useful. The deployment of such tools has become easier due to advances in computer-aided simulation, which can now explore the interactions and outcomes of each system on the other. This would not only help organizations adapt to dynamic forces affecting logistics globally, but also aid swifter decision-making to support smoother operations at the execution level.

Currently, the security policy environment is threatened by political upheavals and regime changes in several nations, giving rise to novel institutional, ethical, and political challenges. States therefore face external threats necessitating the production and preservation of national security (SIPRI, 2012). Subsequent tasks include war fighting, noncombatant evacuation plans, peacekeeping and peace enforcement, as well as humanitarian tasks such as disaster relief and humanitarian aid. According to German constitutional law (Article 87a Grundgesetz (GG)), this complex range of responsibilities is mandatory upon militaries and may be considered a service obligation within the purview of defense portfolios (Essig, Mohr & Tandler, 2014). Since armed forces fall under public-sector organizations, national governments finance them.

The European Defense Agency estimated that, in 2009, the EU's 26 member nations spent a combined 194 billion Euros on defense — a large share of EU national budgets. Of this total, 16.77% (approximately 32.53 billion Euros) was devoted to defense procurement. In view of this colossal expenditure on national security, national armies have for many years faced increased pressure to reduce expenses (SIPRI, 2011; Essig et al., 2014) while utilizing resources efficiently.

Toward simultaneously safeguarding operational effectiveness and ensuring efficiency, defense forces must focus on their respective core competencies while employing contemporary forms of financing and cooperation. This trend is manifested through the realization of a number of public-private partnerships (PPPs) or Public Finance programs, which have grown in number in recent years (Hartley, 2002). The market for defense equipment has considerable potential. Despite the relevant cost-cutting opportunity, militaries lack suitable management tools to guide the long-term links that traditionally characterize the defense equipment market.

An analysis of literature pertaining to traditional supply chain management (SCM) indicates a few steering tools, offered chiefly for private-sector organizations. However, considering militaries' specific characteristics, one cannot assume unreflective application of existing management tools designed for business supply chains (Essig et al., 2014). This paper's key aim is to bridge this theoretical gap by creating a suitable management tool for use in defense transport supply chains, thereby enabling militaries to successfully guide the long-term links dominant in the defense equipment marketplace. To serve this purpose, an exposure-capacity-portfolio is selected, which permits thorough defense supply chain analysis and offers suitable recommendations regarding strategic action.

Literature Review

Melnyk and colleagues (2010) argue that a successful SCM system ought to comprise at least one of the following strategic outcomes: cost, responsiveness, resilience, security, innovation, and sustainability. Investments made by companies are initiated by the outcomes desired, and these outcomes are employed across multiple levels in a majority of supply chains. Supply chains of defense organizations are unique compared to general organizations; their primary outcomes are generally centered on responsiveness — the supply chain's ability and capacity to effectively react to alterations in customer location, product mix, and demand. This effectively maps to defense units' main objective: readiness.

Van Wassenhove and Guide (2009) write that analysis in closed-loop supply chain systems employs one of two critical techniques: waste-stream compliance reduction costs, or market-driven profit maximization. These views reflect the economic and regulatory realities of a majority of European nations and the United States, respectively. It has also been noted that companies emphasizing solely profits develop different supply relationships and sourcing patterns (Fleischmann et al., 2001) — distinct from companies that also abide by environmental regulatory limitations.

This paper introduces and examines a third goal of closed-loop supply chain systems, defined by military organizations. This goal demonstrates how concentrating on readiness affects the supply chain's final design. From the military perspective, readiness denotes an ability to satisfy national military strategy demands and fight efficiently (U.S. Department of Defense, 2010). This necessitates improved manpower capabilities, training, weapon systems, and sustainable equipment.

Considerable data on closed-loop supply chains arises from military practices involving aircraft-related parts inventory. Some parts are repairable in the field, whereas others must be forwarded to a central military depot for disposal or repair (Guide & Srivastava, 1997). Sherbrooke (1968) developed a system — METRIC — for maintaining an air force repair-parts inventory. Subsequent research refined the calculations for a multiple-level echelon system enabling transshipments. Brennan and Fisher's (1986) research considered equipment cannibalization for limited spare parts acceptable under particular conditions, though total cannibalization is not acceptable.

Presutti and Demmy's (1981) analysis of a multiple-echelon inventory model with limited repair finances was notably inspired by Air Force Logistical Command. Additionally, such research has steered closed-loop supply chain issues in private marketplaces. Bjorkman, Ostlin, and Sundin (2008) performed broader research on policies, returns, and their effect on overall performance. Vandaele and Lieckens (2012) studied complex supply-chain planning elements with regard to collection, production, uncertain supply, and transportation. Unspecified, unclear, or unexpected process times result in quality decline. Issues pertaining to sourcing of manufactured parts and related investments in repair capacity appear to receive comparatively less attention.

By utilizing Van Wassenhove and Guide's (2009) guidelines, this paper proposes an economic methodology for establishing the strategic significance of supply chain designs and the incentives accompanying defense supply chains. No market competition exists in the military domain; thus, market-based incentives are irrelevant in this context. Furthermore, the armed forces are responsible for return processes — spent costs return to base and only then are directed to production units. Moreover, armed forces form part of manufacturing processes.

Radio Frequency Identification (RFID) technology has now become a reality for numerous sectors, including the public sector, retail, and production. RFID data warehouses need to possess enough data to influence the decision-making process. Any supply chain is a dynamic business unit. Historical information is useful for learning, but typically does not represent optimum current information. Environments characteristically display variables in product demand, product characteristics, machine characteristics, production plans, and supply levels (Velasquez et al., 2015). Development of suitable business rules constitutes a central element in ensuring this type of system is implemented effectively. RFID provides data-input automation options in existing business processes, as well as options for creating innovative business models. Common supply chain activities combined with the capacity to establish location, time, and reading data from unique items will offer opportunities for pinpointing obstacles and flaws.

This kind of information is especially valuable in guiding delivery priorities when resources are limited. If one is able to establish a product's exact location at a particular time, numerous issues can be resolved, including shortening product recall time and retracting outdated items. The ability to locate product inventories also aids in shortening transit time between conveyance points — from the factory floor to the warehousing unit and showroom. RFID proves valuable in clustering small consignment data from multiple sources guided along the same path in the initial distribution stages, or even automating rerouting when travel-condition data changes (Liqin, 2014).

A clear challenge is managing system changes. Planning and organizing RFID messaging while simultaneously reviewing IT support systems and business processes is no easy task. Balancing innovation and effort while seeking strategies for attaining a competitive edge is, from management's viewpoint, a central issue. The costs linked to handling RFID-generated information will be substantial, whereas gains depend on data collection quality. These gains will mostly be intangible but are later recovered within the defense business cycle. Additionally, organizations focused aggressively on business process analysis find that intended improvements are extremely difficult to attain or even nearly impossible to execute (Liqin, 2014).

Discussion of the Problem: CAS and Supply Networks

A logical framework centered on a complex and comprehensive perspective can aid the goal of supply chain improvement (Dagnino et al., 2008). The CAS approach gathers aspects useful for understanding the tension between supply network emergence and control (Choi et al., 2001). This paper therefore addresses supply networks in the form of CASs, through a thorough reflection of these approaches.

CAS is a complex system theory. A complex system comprises multiple interactions between agents or entities (Humphrey & Schmitz, 2001). Several issues — including anticipating global trade changes, understanding markets, preserving ecosystems, and stimulating economic innovation — may be tackled using CAS. For example, McCarthy (2003) applied CAS to explain a theory of technology management, while Wilfing, Rammel, and Stagl (2007) employed it for developing a natural resources management plan.

As defense organizations deliver goods, services, or armaments that successively influence public goods (i.e., national security) production, their supply chains may be categorized as public-sector supply chains of a special kind. One can generally differentiate between defense and military supply chains in terms of how many tiers are involved. Military supply chains concentrate exclusively on delivering goods or armaments to an army unit deployed on a specific mission, sometimes supported by private logistics agents. In contrast, defense supply chains extend beyond military missions to encompass private industries. Following Mentzer and colleagues' (2001) differentiation, three kinds of defense supply chains may be identified: basic, ultimate, and extended.

Agents, interaction, learning, and autonomous actions are the core components of a CAS, and all four components can be found within supply networks. Agents refer to companies or collections of companies collaborating through alliances or partnerships in which they share economic advantages and rules (Choi et al., 2001). Companies may be suppliers, retailers, manufacturers, or clients, each having a distinctive role within the system. These companies create an atmosphere of deep interaction inspired by exchange of information, knowledge, material, and funds — exchanges that emerge from the pursuit of individual companies' goals (Wycisk, McKelvey, & Hulsmann, 2008).

Firms represent entities with relative autonomy of operation in markets and sectors. In supply networks, firms and their sub-entities have independent levels via decentralization and delegation in the areas of planning and decision-making (Wycisk et al., 2008). Complete autonomy is not enjoyed, however, as these organizations are bound by legal and contractual obligations as well as sectorial forces — for instance, the unequal power existing in a buyer-supplier relationship.

Within the inter-organizational interaction context, supply networks' learning capacity can enable exchange of existing capacities and valuable knowledge, as well as co-production of novel capabilities and knowledge (Dagnino et al., 2008). The concept of learning within supply networks has not been extensively explored; however, it has the potential to increase organizational competitive advantage and durability.

CAS activities of co-evolution, self-organization, and complexity are all perceptible within supply networks. Powerful organizations such as Toyota run a few supply networks; however, a majority of supply networks lack control organs (Wycisk et al., 2008) that exercise governance and coordinate network activities. Such networks self-organize based on interactions, motivated by individual firms' interests. In supply networks, self-organization occurs as certain companies accept parameters established by other parties in the network. Institutional mechanisms and inter-organizational relationships also exist through which non-market-centered coordination of chain activities is achieved.

According to Wycisk and co-workers (2008), a self-organized process occurring within a logistical system would have a boundary between chaos and order — what is called the "edge of chaos." Supply networks' activities operate within this dynamic space between chaos and order. Networks represent organizational forms situated between hierarchy and markets. "Chaos" represents evolving coordination through market forces and dynamics, whereas "order" denotes complete asset internalization. These extremes are unattractive to supply chain agents, but in the chaos/order space, supply chain agents can lower transaction costs, learn from one another, and thus complement co-evolution.

In management, "creative space" is another term used for the "edge of chaos." This concept deals with the levels of control and rigidity. If a supply network's parameters, rules, and forms of acting and thinking are quite rigid or, conversely, overly flexible, creative space will be limited through either stagnation or collapse. This creative space forms the locus for inventive ideas regarding products, services, and processes.

Co-evolution transpires as a form of behavior within supply networks located in this creative space, wherein firms, environments, and networks are recursively modified through continuous evolution. For example, if an acquiring firm develops a parts supplier as one supplier system, this action will successively generate a new group of second-level suppliers delivering parts to the new supplier system (Choi et al., 2001). Co-evolution results from agents' progressive interaction and learning; for instance, buyers aid suppliers in directly implementing quality standards, or do so through the introduction of service providers.

With regard to emergent effects, supply networks themselves correspond to an emerging result, since a network's structure relies on the corresponding choices of companies (Choi et al., 2001). One possible supply network goal is understanding how choices can be matched for achieving efficient emerging activities (Wycisk et al., 2008). The emergent effects reviewed here include the butterfly effect, adaptation, path dependence, nonlinearity, holism, and systemic hierarchy.

The component of adaptation in a dynamic system changes over time with the objective of self-conformance and conforming to the environment. Two fundamental problems exist: (1) identifying the actions and rules that work well, so as to sustain them; and (2) determining which actions and rules give rise to problems, enabling their elimination. Adaptation results from a complex series of interactions occurring within a specified space and time (Hartley, 2002).

Supply networks have typically adjusted to their corresponding environments over long periods — molding their structures, excluding or adding inter-agent relationships (for example, associating with novel supplier firms and becoming their new customers), changing their physical capabilities (such as implementing new technologies), and effecting strategic changes by modifying behavioral processes (Wycisk et al., 2008). In this way, supply networks interact with demands in their environments and modify the environment to suit themselves, their member firms, and their rivals (Choi et al., 2001).

Non-linear effects can occur in the adaptation context. Facing constant adaptations, CASs can present unpredictable nonlinear effects whose outcomes are irreversible — one cannot erase them after their production, nor can one return constituents to their initial state. Cost reduction endeavors by a large supply chain buyer might therefore bring about random results. In supply chains that exhibit nonlinearity, one cannot control the network's operations through deterministic methods. A management objective can, however, potentially mix agents' autonomy and control to bring about improvements (Choi et al., 2001). This combination increases the likelihood of a network's reaching the creative space between chaos and order.

Supply chain butterfly effect is a type of nonlinear effect. CASs may display butterfly effects incorporating extreme occurrences instigated by small behaviors. The effect may stem from nonlinear behaviors and numerous interactions involving negative or positive feedbacks among chain agents (Wycisk et al., 2008), making prediction difficult. The related bullwhip effect in supply networks may be explained as follows: the actions of some organizations within a given supply chain may affect other firms owing to the interdependency between them. "Bullwhip" defines how small initial changes — such as market demand variations — can lead to extreme and chaotic events along a supply network via nonlinear processes (Wycisk et al., 2008). Rungtusanatham, Choi, and Dooley (2001) suggest that a minimal downstream supply network change is capable of causing amplified effects upstream. Supply chain bullwhip effects are linked to four key causes: bulk purchases spurred by discounts; fluctuations in price due to promotions and similar events; demand forecast updates; and scarcity, whereby when supply is less than demand, vendors ration products downstream.

Systemic hierarchy encompasses the creation of operations at different levels adhering to similar rules. A system's adaptive capability will expand if its subsystems are quasi-decomposable. Different aggregated levels can emerge from independent agents within the system; though temporarily stable, these levels are adaptive and can recombine to enable increased adaptability at superior levels. Supply networks, observed vertically, are multi-level by definition, constituting suppliers, manufacturers, distributors, retailers, and consumers (Wycisk et al., 2008). These subsystems can be unstable or stable based on their contract type (short-term or long-term), and informal agreements — such as unique partnerships — may also exist. For example, small company aggregates may self-organize for a specific purpose, such as the development of a new product or material, with the structure easily dissolved upon completion of activities.

Holism is linked to the principle of the holograph, which implies that a sub-system is reflected in the whole, whilst the whole is simultaneously reflected in the parts. In the context of supply chains, holism relates to the rules of the game. For instance, Schmitz and Humphrey (2001) state that the main rules guiding international supply chain companies include: what must be manufactured, how production must be carried out, when it must be produced, what quantity must be manufactured, and what price must be quoted. Surana, Greaves, Raghavan, and Kumara (2005) offer another example: evidence of holism in supply chain contexts may be perceived when the same concerns exist at all levels of the system — for example, lower-priced goods, better quality, swifter delivery, and storage. A similar, shared logic guides actions at multiple levels toward one common end. For companies involved in any supply network, this logic is usually articulated as the creation of customer value. All agents belonging to a chain follow these rules, with non-conformance penalized by exclusion from the chain. The rules apply to individual agents and, concurrently, to the whole supply chain.

Since each component of logistics is in a state of constant evolution — through either internal or external factors — they constitute the System Dynamics (SD) framework, a vital tool for authenticating the reverse logistics methods adopted by the military. Employing SD simulation in supply chain management can prove decisive in improving its balance in logistics, according to Georgiadis and Vlachos (2004).

The adaptation and interaction process develops, over time, an overlapping series of decisions constituting path dependence and history. The concept of path dependence originates in Arthur's (1999) thinking on increasing returns. According to his ideas, economic systems may have two or more equilibrium points approachable by means of positive feedbacks, whereby one point leads to the next in sequence.