Advanced Supply Chain Planning Systems (APS) Today and Tomorrow

Abstract

The Supply Chain Management (SCM) paradigm is widely discussed today in virtually all industry sectors. This paradigm emerged in the late 1980s, and became widespread in the 1990s as a way to organize a set of concepts, methods and tools for promoting a holistic view of the entire supply chain. Supply chain optimization greatly depends on the planning process (Jespersen & Skjott-Larsen, 2005). This process aims to obtain a balance between supply and demand, from primary suppliers to final customers, to deliver superior goods and services through the optimization of supply chain assets. This is quite a difficult task since it involves simultaneously synchronizing a large quantity of complex decisions, and dealing with other issues that can complicate the process, for instance the existence of conflicting objectives and the presence of stochastic behaviours (Lin et al., 2007; CamarinhaMatos and Afsarmanesh, 2004; Schneeweiss and Zimmer, 2004; Terzi & Cavalieri, 2003; Min and Zhou, 2002; Simchi-Levi et al., 2000). To cope with the complexity of supply chain planning, a set of information technology (IT) tools can be used directly or indirectly. These systems are used for information integration, inventory management, order fulfilment, delivery planning and coordination, just to mention a few. Among the leading IT tools for Supply Chain Managemet, the Advanced Planning and Scheduling (APS) system is widely discussed today, which may be due to the fact that APS systems focus on a very relevant problem in supply chains, i.e. how to synchronize hundreds of real planning decisions at strategic, tactical and operational levels in a complex environment. This quite challenging objective requires an advanced solution. Basically, APS are computer supported planning systems that put forward various functions of Supply Chain Management, including procurement, production, distribution and sales, at the strategic, tactical and operational planning levels (Stadtler, 2005). These systems stand for a quantitative model-driven perspective on the use of IT in supporting Supply Chain Management, for exploiting advanced analysis and supply chain optimization methods. In fact, APS systems have represented a natural evolution of planning approaches for the