Supply chain design: a conceptual model and tactical simulations

In current research literature, supply chain management (SCM) is a hot topic breaching the boundaries of many academic disciplines. SCM-related work can be found in the relevant literature for many disciplines. Supply chain management can be defined as effectively and efficiently managing the flows (information, financial and physical) in all stages of the supply chain to add value to end customers and gain profit for all firms in the chain. Supply chains involve multiple partners with the common goal to satisfy customer demand at a profit. While supply chains are not new, the way academics and practitioners view the need for and the means to manage these chains is relatively new. Very little literature can be found on designing supply chains from the ground up or what dimensions of supply chain management should be considered when designing a supply chain. Additionally, we have found that very few tools exist to help during the design phase of a supply chain. Moreover, very few tools exist that allow for comparing supply chain designs. We contribute to the current literature by determining which supply chain management dimensions should be considered during the design process. We employ text mining to create a supply chain design conceptual model and compare this model to existing supply chain models and reference frameworks. We continue to contribute to the current SCM literature by applying a creative application of concepts and results in the field of Stochastic Processes to build a custom simulator capable of comparing different supply chain designs and providing insights into how the different designs affect the supply chain?s total inventory cost. The simulator provides a mechanism for testing when real-time demand information is more beneficial than using first-come, first-serve (FCFS) order processing when the distributional form of lead-time demand is derived from the supply chain operating characteristics instead of using the assumption that lead-time demand distributions are known. We find that in many instances FCFS out-performs the use of real-time information in providing the lowest total inventory cost.