Supply Chain Complexity

Supply Chain Complexity

DOI: 10.4018/978-1-5225-8298-4.ch002
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Abstract

This chapter focusses on the concept, drivers, and perspectives of supply chain complexity of a firm. It discusses the impact of number of tiers, number of nodes in each tier, its links and flows on complexity of a firms' supply chain. This chapter tries to bring out the dynamic interactions between tiers and nodes. This chapter suggests that the levels of supply chain and its dynamic complexity are influenced by the products, processes, relationships, and the environment of the firm and its suppliers and distribution partners. Here the drivers, namely, the 5Vs (value, volume, variety, volatility, and visibility), 3Ps (process, people, and planet), and the global market (as a driver) that lead to complexity have been discussed. The complexity of supply chain has been explained from different perspectives. These are the system and process perspectives. This chapter introduces the concept of systems thinking proposed by Forrester and Senge. It illustrates the need to apply a holistic approach in reduction of supply chain complexity. The causality doctrine, proposed in this chapter, enables a supply chain manager to carry out policy experimentation. Supply chain structure varies across organisations. This suggests that a process framework along with application of systems thinking will aid supply chain managers to make supply chain less complex and lean. That is, the supply chain has the desired properties, namely, repeatability, testability, serviceability, flexibility, and cost efficiency. The next section talks about the importance of production processes in reducing complexity. Finally, the chapter discusses about the optimal number of suppliers a firm may have to meet its objectives. It argues that if past do not extend in future, the number of suppliers will add redundancy to the upstream supply chain, and at the same time, if future exceeds past, the supply chain fails. There are different options available to meet these challenges. These could be “buy-back” or “pay-back” or “rate contract” options. This chapter introduces the computational framework for assessing complexity of a firm based on its structure. This framework will help supply chain managers to carryout experimentation on the design of a supply chain network.
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Introduction

A firm whether it decides to make or buy or do both, sources different inputs from its suppliers. This comprises the upstream supply chain of the firm. Similarly, the firm may decide to sell its products directly to the end customers or through a distribution channel, comprising, distributors or dealers and /or wholesalers and retailers. This constitutes the firms’ downstream supply chain. Besides a firm may have its warehouses, production or assembly plants located at same or different places. This is firms’ internal supply chain. This forms a network as shown in figure 1.

Figure 1.

An illustration of a supply chain network

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A firm can have multiple tiers of suppliers, production centres and distributors. Each tier can comprise multiple supplier, internal operations and distributor respectively. Figure 2 represents a simple supply chain, where the firm has one supplier and one customer. The complexity increases with increase in suppliers, internal setups and distribution partners

Figure 2.

A simple supply chain

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The flow amongst the nodes representing suppliers, production centres and distributors can be multi-directional. There could be a situation where a supplier, say S1, supplies material to the production centres, say, WIP1 and WIP3. Similarly there could more than one flow originating from any of these nodes to more than one node. Even there could be a direct flow from the supplier (of the firm) to the customer. For example, a battery manufacturer can supply to a mobile manufacturer and also supply directly the same to the distributor or end customer who wish to replace worn out batteries of used mobile phones. Figure 3 represents such as case.

Figure 3.

Multiple flows from a particular node in a supply chain

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Figure 3 shows that supplier S1 supplies not only to the firm but also to its customer. However, the flows, represented by a, b and c may not be under the control of the firm. Say the supplier supplies battery to the firm and sells directly to the customer. In that case, the flow “c” is not under the control of the firm. Whereas, if the firm on receipt of order for battery replacement directs its supplier to directly supply to the customer, has some responsibility for the flow ”c”; as any deviation in customers’ expectation will cause the customer to lodge a complaint to the firm and / or the affect the goodwill of the firm.

Supply chain complexity need to be studied from different perspectives. Some authors (Bozarth et al, 2009; Serdarsan, 2012) described complexity arising out of internal sources i.e., decisions on product and processes design; supply and demand interface. Complexity also arises out of flow of materials and information between the firm and its supplier and customers; and due to the external drivers such as market volatility, government regulations and other environmental factors. Some authors (Vachon and Klassen, 2002) explain complexity in terms of the number of nodes / components and stages or tiers in the system; while Sivadasan et al., (2006) suggest that the complexity arises out of dynamic interactions between stages. The definition of complexity was well drafted by Bozarth et al. (2009), as – “the unpredictability of system’s response to a given set of inputs”. Complexity can be categorized as detail and dynamic complexity (Bozarth et al 2009); or static and dynamic complexity (SerdarAsan, 2013). Modrak, et al. (2015) provided an architectural framework suggesting supply chain complexity indicators based on Axiomatic Design theory and Boltzmann entropy.

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