Modelling the Bullwhip Effect under the Implementation of Supply Chain Management Software
Read this article on using software to model the bullwhip effect.
Introduction
From material requirements planning (MRP), manufacturing resource planning (MRP II) to enterprise resource planning (ERP), the manufacturing industry has developed sound operations management techniques for lateral business functions management within entire enterprise. However, it is equally important to manage the vertical relationships with outside supply chain members, and this is part of the reasons why supply chain management (SCM) software is developed: to collaborating with other supply chain members effectively.
One of the greatest challenge for the supply chain management is to overcome the bullwhip effect. The bullwhip effect, also known as whiplash or Forrester effect, refers to "the process of amplification of order in upward direction of a supply chain". It means that in a supply chain system, the upstream members tend to have larger and larger variations of inventory level in response to uncertainty of real demand. Consequently, the high inventory level not only increases total costs of supply chain, but also makes the members of supply chain unable to meet customer demand in a timely manner. For these reasons, accessing to accurate and reliable information as well as minimising bullwhip effect becomes critical for the members of supply chain management. Therefore, the implementation of SCM software for all members of the supply chain is becoming necessary.
The use of SCM software has attracted a growing interest in the academic field. However, there is a lack of numerically analysed with regard to the effect of implementing SCM software in the exiting literatures. This study thus aims to formulate the relationship between SCM software implementation and changes of the bullwhip effect. In the following sections, the status quo of supply chain management and the bullwhip effect are discussed, followed by a discussion of research methodology, and finally a numerically simulated study based on the empirical data in Taiwan is presented. Furthermore, the conclusion and the findings of this study are also given.