Increasingly fast introduction of new products, shortening product life cycles, volatile demand of customers, increasing customisation offers to clients, and geographical spread of supply chain partners in a competitive global market, have driven companies and businesses to create more complex structures (Wilding, 1998b; Blecker et al., 2005; Bozarth et al., 2009). Therefore managing these complicated chains is becoming more challenging for managers.
Different studies develop different approaches to investigating this complexity. One of the early studies to do so was Wilding (1998a). By using the complexity theory, the contention was that a combination of the effects of three independent variables is the cause of
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uncertainty – thus complexity – in supply chains. Deterministic chaos, parallel interactions and demand amplification were the mentioned effects. Chaos is defined as “Aperiodic, bounded dynamic in a deterministic system with sensitivity dependence on initial conditions” (Wilding, 1998a, p. 600) which will occur because of over-reactions, unnecessary interventions, second-guessing, lack of trust, and distorted information across a supply chain. The “Beer Game” is a famous example of chaos in supply chains (Lee et al., 1997).
Parallel interactions are those actions that are interdependent through the supply chains. These parallel interactions will increase the uncertainty if one of the suppliers fails to supply the demand, and they will consequently affect other tiers of the supply chain (Wilding, 1998a). The last variable is demand amplification. Demand amplification is the situation in which small changes in customers’ demands result in a large variation when transferred upstream through the value chain (Taylor, 1999). Wilding (1998a) contended that analysing the three mentioned variables as antecedents of uncertainty will help managers choose the right supply chain strategies.
Another study (Choi et al., 2001) argued that supply chain complexity should be examined from the CAS perspective. They define CAS as a series of firms that are willing to exchange information, product and services with each other, in order to maximise the profitability of each company. They argue that the successful application of control-oriented schemes can lead to improved efficiency. At the same time it might also have a detrimental impact on performance improvement and innovative actions of suppliers. They imply that the level of control is a serious managerial issue, and the decision of how much to control and how much to allow to emerge is an important factor so “managers not only have to control the daily activities but also remain vigilant, patiently observe what emerges, and make decisions appropriately” (Choi et al., 2001, p. 365).
In another study, Belcker et al. (2005) argued that according to the origin of complexity, complexity of supply chains should be divided into external and internal categories. Internal complexity can be taken care of by the company and results from structures, elements, and processes of the manufacturing area (Blecker et al., 2005). There is also a fixed external complexity from external sources (e.g. consumer demands, technological innovativeness or economic development). The study also offered another categorisation between structural and
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dynamic (or operative) complexity (Frizelle & Woodcock, 1995) in order to analyse and re- design the complexity.
The study claimed that the nature of the product, structures and processes are drivers of structural complexity. The complexity arising from external and internal sources within the operation (for example, variations in dates and amounts due to material shortness, machine breakdowns, or insufficient supplier reliability), is dynamic (operative complexity). In this study, a detailed illustration of different supply chain complexity drivers (e.g. product complexity, technological innovations and shortened product life cycles) was also offered.
Another study by Perona and Miragliotta (2004) classified supply chain complexity into inbound and outbound logistics (volumes; networks; distributive modes), sales processes (product range; services; time to order; customers), production engineering (production resources; technology; plan layout), production process (volumes; organisation; planning) and new product development (structure; design; product life cycle). Perona and Miragliotta confirmed that the way companies handle their complexity management system has a major effect on their operational performance. They also stated that the ability to manage complexity counts as a core competency for companies, one that can improve efficiency and effectiveness throughout the whole supply chain. Sivadasan et al. (2004) emphasised that the operational complexity of supply chains depends on product demand volatility, reliability of goods supply, consistency of internal performance and the effectiveness of operational policies. They offered four operational supply chain complexity policies: exporting operational complexity to other organisations; charge for the services of imported complexity; investment in precautionary systems that work to avoid complexity; and investing in resources to absorb complexity (Sivadasan et al., 2004).
Other studies that mainly discussed the complexity factors of supply chains. Bozarth et al. (2009) indicate that both internal and external complexities have a negative influence on supply chain complexity. They offer: different downstream complexity factors (number of customers; heterogeneity in customer needs; shorter product life cycles; demand variability), internal manufacturing (number of products; number of parts; one-of-a-kind/low volume batch production; manufacturing schedule instability) and upstream (number of suppliers; long and/or unreliable supplier lead times; globalisation of the supply base) of supply chains.
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They also emphasised that dynamic complexity drivers have a more significant impact on supply chain performance compared to structural complexity drivers.
From a holistic and conceptual perspective, Christopher (2012) identified seven types of supply chain complexities. They are, in fact, the complexities supply chains commonly experience. These are: Network complexity (e.g. too many connections in the network), Process complexity (e.g. too many steps), Range complexity (e.g. a wide range), Product complexity (e.g. too many unique items), Customer complexity (e.g. too many service options), Supplier complexity (e.g. too many suppliers) and Organisational complexity (e.g. too many levels and players within levels). In order to overcome or manage such complexities, this study suggests aligning the supply chain processes with customer demand and avoiding inefficient complexities.
Table 2.1 below summarises studies on supply chain complexity and its drivers. Most of these studies investigate the drivers of supply chain complexity and then offer recommendations to manage these complexities. These studies suggest aligning the internal complexities (e.g. organisational structure, supply chain collaboration) with external complexity drivers such as product characteristics. Although some studies have identified these product demand and design characteristics, no single empirical has attempted to model an alignment framework considering the simultaneous impact of product demand and product design on supply chain. Hence, we aim to propose a framework that can assist practitioners on aligning their supply chain complexity with product demand and design characteristics. The next section will discuss supply chain complexity from a trans-corporate logistics view.
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Table 2.1: Key Studies on Supply Chain Complexity
Author Approach Theory Key focus
Wilding (1998a,b) Conceptual Chaos Theory Manage Complexity
Matching supply chain with demand and supply uncertainties
Choi et al. (2001) Conceptual Complex adaptive system (CAS)
Manage
Complexity Matching supply chain with innovativeness Milgate (2001) Conceptual Complexity Theory - Organisational Theory Develop a conceptual model
Aligning supply chain organisational structure to avoid and minimise uncertainty
Perona & Miragliotta (2004) Empirical (Case Study) N/A Manage complexity
Minimising complexity dimensions through supply chain control levers
Blecker et al.
(2005) Conceptual N/A
Manage complexity
Adapting the organisational complexity or indirect design of dynamic complexity
Hoole (2005) Conceptual Multiple Reducing
Complexity
Simplifying supply chain processes aligned with customer demand Turner & Williams (2005) Conceptual (Simulation) N/A Minimise
Complexity Simplifying supply chain configuration Masson et al. (2007) Empirical (Case Study) N/A Minimise Complexity
Postponement and Collaborative information sharing as Agile strategy
Pathak et al. (2007) Conceptual Complex adaptive system (CAS) Adapting supply chains to complexity
Matching supply and demand by increasing supply chain collaboration and flexibility Hu et al. (2008)
Conceptual (Mathematical
Modeling)
Entropy Theory Manage Complexity
Align supply chain and manufacturing with product variety Bozarth et al. (2009) Empirical N/A Impact of Complexity on Performance
linking operations strategy to organisation design Huatuco et al. (2009) Conceptual (Mathematical Modeling - Case Study) Entropy Theory Measure - Manage Complexity
Business Process Reengineering in accordance with customer demand
Isik (2009) Conceptual (Mathematical Modeling) Shannon’s information entropy Measure
Complexity Matching supply chain with demand Gerschberger et
al. (2010) Conceptual System theory
Identifying Parameters of
complexity
Number of elements and variety in system is the critical factor - interdependencies amongst the identified parameters of complexity have to be quantified Li et al. (2010) Conceptual - Empirical (case study) Complex adaptive system (CAS) & Evolution Theory
Identifying supply chain complexity evolution drivers
Align external environment such as market demand and market structure with internal factors, for example the firm’s strategies, product structure
Yang & Yang
(2010) Conceptual Accident theory
Manage Complexity
Using postponement to manage supply chain complexity
Manuj & Sahin
(2011) Conceptual Grounded theory
Define & Manage Complexity
Matching supply chain with customer demand and increase flexibility across the supply chain Christopher
(2012) Conceptual N/A
Define & Manage Complexity
Aligning supply chain with market and customer demand
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2.7