Supply chain management principles and practices

Supply Chain Management in the 21st Century

Progressing beyond pick-pack-ship logistics and network optimization techniques to the development of concurrent, real-time supply chain networks, the field of supply chain management (SCM) continues to see the effects of disruptive technologies on its growth and efficiency gains. Supply chains are now integrated into analytics platforms making it possible for real-time optimization of demand management, forecasting and economic order quantities (EOQ) to be achieved and used for managing supplier networks (Ivanov, Sokolov, Kaeschel, 2011). Analytics have become so engrained in supplier management and logistics that the use of scorecards and benchmarks have become commonplace (Jabbour, Filho, Viana, Jabbour, 2011). These analytics have led to significant reductions in supplier risk and the streamlined the most complex processes companies contend with including new product development and introduction and the development of new channels of distribution (Manuj, Mentzer, 2008). Integrated analytics within supply chains are making it possible to manage inventory in real-time and also alleviate costly errors in shipments and original order requirements (Nasiri, Davoudpour, Karimi, 2010). All of these factors taken together are creating a more efficient and synchronized supply chain network for many companies globally (Lewis, Hornyak, Patnayakuni, Rai, 2008). This has in turn led to much greater levels of supplier collaboration and cross-supplier knowledge sharing (Dyer, Nobeoka, 2000). A study of the Toyota Production System showed that the greater the accuracy and velocity of information shared, the greater the level of cross-collaboration and ability to transform supplier information into a competitive advantage (Dyer, Nobeoka, 2000).

Analysis of Supply Chain Management in the 21st Century

Supply chain management has transformed many of the uncertainties in supplier coordination and timing into analytics, in some industries in real-time, to alleviate risk and ensure accuracy of shipments and orders (Ivanov, Sokolov, Kaeschel, 2011). This reliance on metrics and analytics have done more than bring a new level of precision to complex supply chain transactions and workflows, they have begun to transform entire organizations into demand-driven enterprises (Novack, Thomas, 2004). The long-term effects of having such a high level of accountability and accuracy of supply chain performance measured by metrics and key performance indicators (KPIs) is also leading to greater levels of shared result monitoring and evaluation (Jabbour, Filho, Viana, Jabbour, 2011). The use of analytics to create this shared ownership of outcomes has created the foundation for shared outcomes and the measuring of Return on Investment (ROI) in these programs globally (Nasiri, Davoudpour, Karimi, 2010).

This enhanced level of analytics and metrics within supply chains is leading to a redefinition of their role within organizations as well. Instead of being considered just a part of the value chain that manufacturing depended on and supplier management, procurement and quality management continually worked with to ensure successful results, supply chain management is now considered a core strategic asset in any business (Novack, Thomas, 2004). The more complex the sourcing, procurement and quality management tasks, the greater the level of reliance on the supply chain. This has become so pervasive, accelerated by the use of real-time analytics, that supply chain performance and its quantified business value is changing the cultures of many organizations as a result (Novack, Thomas, 2004). Analytics alone are not changing the cultures of many organizations based on the performance of supply chains however; it is the new level of supplier collaboration and communication, both between suppliers and manufacturers and between suppliers themselves that are changing the landscape of many industries (Dyer, Nobeoka, 2000).