Saturday , June 23 2018

Service Performance of Some Supply Chain Inventory Policies Under Demand Impulses

Subhash WADHWA
Professor, Department of Mechanical Engineering Indian Institute of Technology
Delhi, INDIA

Bibhushan & A. PRAKASH
Research Scholars, Department of Mechanical Engineering
Indian Institute of Technology Delhi, INDIA

Abstract:

This paper attempts to study the impact of impulsive demand disturbances on the service performance of some inventory control policies. The supply chain is modeled as a network of autonomous supply chain nodes. The customer places a constant demand except for a brief period of sudden and steep change in demand (called demand impulse). The service performance of some inventory control policies is studied under increasing number of demand impulses. It is found that the independent decision making by each node leads to bullwhip effect in the supply chain whereby demand information is amplified and distorted (as reflected by poor service performance). However, under a scenario where retailer places a constant order irrespective of the end customer demand, the service performance does not deteriorate along the supply chain. The service performance of all the supply chain nodes remains same when only the actual demands are transmitted by each node. The results also showed that the inventory policy which is best for one supply chain node is generally less efficient from a supply chain perspective. Moreover, the policy which performs poorly for one node can be most efficient for the supply chain. In a way, our results also provide a case for coordinated inventory management in the supply chain where all members prepare a joint inventory management policy that is beneficial for all the supply chain nodes.

Keywords:

Inventory Management, Supply Chain, Simulation, Impulse Demands.

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CITE THIS PAPER AS:
Subhash WADHWA, Bibhushan & A. PRAKASH, Service Performance of Some Supply Chain Inventory Policies Under Demand Impulses, Studies in Informatics and Control, ISSN 1220-1766, vol. 17 (1), pp. 43-54, 2008.

1. Introduction

Supply chains can be structurally considered as network of independent and autonomous entities which work in unison towards some common objective. Each entity or member of the supply chain can be represented as a node on the supply network. Since each node of the supply chain is an autonomous member, each node takes decisions in accordance with what it perceives is best for it. There are numerous examples in supply chain literature that demonstrate that this autonomous decision making by each node leads to overall poor performance of the supply chain. They also lead to the phenomenon of Bullwhip Effect whereby the demand information is delayed, distorted and amplified at each supply chain node (see Lee et. al. 1997a and 1997b).

From a service performance (or service quality) point of view, this autonomous decision making leads poor performance of the supply chain as demonstrated by simultaneous occurrence of poor service levels and very high inventory carrying costs. In other words, the inventory policy followed by a supply chain node affects the inventory related performance of the supply chain to a very large extent. The impact of various inventory policies on the supply chain performance is widely studied (Atkins and Iyogun 1988, Viswanathan 1997, Nielson and Larsen 2005). However, the performance of these policies under different degrees of variability has not been studied well.

Demand impulse is a unique kind to demand disturbance where the demand remains constant except for a short period of very large demand fluctuation. Hence, impulse can be considered as the smallest disturbance that can occur in a demand pattern. As this disturbance does not change the mean demand substantially, the impact of this impulse stabilizes automatically over time. However, this small disturbance can have unexpected effects on the entire supply chain depending on the inventory policies followed by different supply chain nodes. More number of impulses can be added to the demand pattern to simulate different degrees of demand variability.

This paper attempts to study the impact of impulse demand disturbances on service performance delivered by different supply chain inventory policies through simulation. Each member of the supply chain is modeled as an independent entity, who takes its decisions autonomously. The impact of these policies on each member of the supply chain and the entire supply chain is then studied by simulating the decision making process at each node working with some pre-defined inventory policy under different degrees of impulse demands. The rest of the paper is presented as follows. The next section provides brief review of inventory management literature to highlight the scope for our research. This is followed by the presentation of a conceptual supply chain model and its definition in context of the study. The experimental results are presented in next two sections: one showing the impact of demand impulses in individual supply chain nodes and the other highlighting the overall impact of these disturbances on the supply chain. The implications of these findings on managers are discussed in the subsequent section. The last section concludes the paper by presenting the key research findings.

6. Conclusion

This paper attempted to study the impact of impulsive demand fluctuations on different inventory policies used in supply chain. A generic object-oriented framework was used to model the autonomous decision making process at different supply chain nodes. This generic framework was used to replicate the behavior of a four node single-product linear supply chain. A comparison of different inventory policies revealed that simpler inventory policies are better prepared to dampen or even reduce the impulsive demand fluctuations. In particular, ordering a fixed order quantity rather than the quantity determined by inventory position or demand history was found to be more efficient under impulsive demand fluctuations. Another important finding was that the inventory policy that was most beneficial for one node resulted in overall poor performance of the supply chain. Moreover, the inventory policies that take previous demand information tend to magnify and distort the actual demand variations.

For instance, the Average Demand policy was found to perform poorly under impulse demand fluctuations. The findings from this research are significant for the supply chains facing stable but fluctuating demand. We have shown that, under this demand pattern, the best policy is not to transmit these fluctuations along the supply chain. This is possible by ordering a fixed order quantity in each period. Although this leads to somewhat poor performance of the retailer, it proves to be most effective for all other supply chain nodes. These finding also provide an additional motivation for coordinated inventory management in supply chain by demonstrating that the inventory policies that are best for one supply chain node are more often than not poor from the supply chain perspective.

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