Centralize vs. Decentralize Supply Chain Analysis

Centralize vs. Decentralize Supply Chain Analysis

Eftychia Kostarelou (University of Thessaly, Greece) and Georgios K. D. Saharidis (University of Thessaly, Greece)
Copyright: © 2014 |Pages: 11
DOI: 10.4018/978-1-4666-5202-6.ch039

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In supply chain systems the aim is to optimize some performance measure, which typically comprises revenue from sales less the costs of inventory. These measures concern either different partners in a supply chain or a combination of supply chains. Supply chain management can be defined as the efficient integration of suppliers, manufactures, warehouses, and stores, so that a production and a distribution planning are determined. Production planning, in supply chain management, is a complex process and defines which products should be produced and which products should be consumed in each time instant over a given time horizon.

For manufacturers worldwide, the business environment is complex and increasingly competitive, mainly due to outsourcing the manufacturing part and the diversification of customers’ demand. Consequently, extended and complex supply chains emerge very often. In a new age of big data and ever-evolving environment, managers and researchers need access to the most current information about the trends in Supply chain management. Powerful data analytics are needed in Supply chain management to provide the business intelligence and strategic insights for the supply chain network.

Business analytics and optimization are a group of approaches that help organizations understand and develop new insights of business performance, based on different methods and data. They make extensive use of data, statistical and qualitative analysis, and fact-based management to drive decision making. They have been increasingly recognized by organizations as an important tool for Supply chain management.

In practice, each company tends to optimize its own production unit with no attention to the whole chain. It has been more difficult the last decades to achieve a minimization of the total costs in terms of reduction in chain-wide inventory, as the environment becomes more competitive and the massive data between work-areas may be difficult to share. For these reasons, organizations will need to transfer the control of planning and management to local system levels. For example, if a factory of a supply chain purchases raw items regularly from another supply chain participant, then, during stockout periods, the company which owns that factory may occasionally find it more profitable to purchase a quantity immediately from some subcontractor outside the supply chain, rather than wait for the delivery of the same quantity from its regular supplier. Policies of this kind, namely decentralized, can be individually optimal at each stage of the supply chain, but not necessarily optimal for the entire supply chain. On the other hand, there are policies where the suppliers cooperate and coordinate to obtain optimal strategy for the entire system, whereas it may be more profitable for some of them to act individually. It has been demonstrated that under these polices, namely centralized, the maximum profit the whole supply chain could make can be much higher than the sum of the profits collected individually.

Key Terms in this Chapter

Bi-Level Programming Problem: Hierarchical optimization problems having two stage of hierarchy.

Business Analytics: A set of approaches that help organizations understand and improve business performance, based on different methods and data.

Big/Massive Data: A collection of data sets, collected over time that exceeds the capacity of existing database systems. Their complexity requires a large amount of time and cost to be analyzed.

Production Planning: The process of determining the production amount, the expected inventory levels and all the resources needed for a production plan during a long horizon.

Decentralized Optimization: A no-coordinated policy to solve a problem which considers the system under study as a number of sub-systems which are optimized separately.

Centralized Optimization: A coordinated policy to solve a problem which considers the system under study as a whole one system.

Supply Chain Management: The management of a network of interconnected businesses, the oversight of materials and information, as they move in a supply chain from a supplier to customer.

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