Class of 2005 Abstract / Objectives: To determine the impact of tightly controlled inventory reduction on customer satisfaction and partial fill costs. Methods: The project was a cross-sectional study employing two survey instruments and a time in motion analysis to determine the number of “we-owes” filled by pharmacies due to inventory reduction, the costs that arise from such reductions, and the impact on customer satisfaction. The first survey instrument was sent to four pharmacies in the Fry’s Food and Drug chain. The survey assessed number of “we-owes” per pharmacy and reasons for having them. The second survey consisted of several statements concerning customer satisfaction. The participants were asked to rate their agreement with each statement using a response scale from 1 (strongly disagree) to 5 (strongly agree). A time-in-motion analysis was performed at two pharmacies averaging 350 prescriptions per day to record the amount of labor involved in filling “we-owes". Results: Medium to high volume Fry’s pharmacy fills an average of forty “we owes” each week. The average yearly costs for filling the “we owes” ranges from $171,579 to $568,796 per year depending on the job status of people filling the “we owes.” The main reason for these partially filled prescriptions was the minimum order point was incorrect accounted for 53.8% of the “we owes Almost half of customers owed medication felt it was not inconvenient them to pick the remainder of their prescription and that over half have had this happen more than once. Implications: The costs of tight inventory control need to be compared with the savings obtained from maintaining marginal inventories.

Organisations are constantly expected to be more competitive while working in an environment in which time and cost are limited, thereby preventing such organisations from taking the time required to be responsive. The supply chain provides a critical linkage between various organisations which should seek collective opportunities to improve performance. It is, therefore, important that organisations understand that conventional knowledge and methods will not serve unless there is a concerted focus on improvement of organisational performance toward fulfilling increased expectations, not just maintaining that which is comfortable. A more sustainable approach may be the introduction of supply chain best practice. An optimal supply chain is one that continuously strives to reduce unnecessary cost and eliminate waste, thereby increasing the percentage of time that may be devoted to value-adding activities. Supply chain technology principles were assessed and the application thereof, sought to understand its efficiency and effectiveness. This study was intended to identify supply chain cost dimensions with a focus on the optimal use of supply chain technology. Within the current supply chain context, the use of Information and Communication Technology (ICT) was explored to identify opportunities. A supply chain audit tool (SCAT) was developed which had proven to be an effective tool to analyse it’s logistics functions. Implementation of remedial tools through the SCAT could result in a leaner, cost optimal and more value-adding process. The result of conducting individual organisational improvements is expected to result in an overall improvement in the total supply chain. These supply chain cost drivers were rooted in cost, quality, safety and product performance. Recommendations on further improvements were also offered.

The purpose of this thesis is to test, via a GPSS simulation, a heuristic developed by B.A. Rosenbaum. The heuristic determines the level of service a customer receives in a multi-echelon inventory system. The system consists of one central Distribution Centre (DC) which is the source of supply for eight Regional Distribution Centres (RDC's), which themselves are the source of supply for customer demand. Service is defined to be the fraction of demand met from on-hand stock at the location where the order is placed. Two distinct sets of tests on the heuristic are performed in this thesis. First, a wide range of parameter values are used in the simulations to test the sensitivity of the assumptions essential in the development of the heuristic. Second, the robustness of the heuristic is examined when different assumptions are substituted in the inventory system analysed. The analysis indicates the heuristic performs fairly well under various conditions. In particular, increasing the order size or reducing the number of warehouses in the system yield calculated values predictive of the simulated results. / Business, Sauder School of / Graduate

In this thesis, we study the statistical issues in lost sales inventory systems, focusing on the complexity arising from the stochastic demand. We model the demand by the Zero Inflated Poisson (ZIP) distribution. The maximum likelihood estimator of the ZIP parameters taking censoring into account are derived separately for the newsvendor and the (s, S) inventory systems. We also investigate the effect of the estimation errors on the optimal policies and their costs. We observe from a simulation study that the MLE taking censoring into account performed the best in terms of cost as well as policy among various estimates. We then proceed to develop a Bayesian dynamic updating scheme of the ZIP parameters. It is applied to the newsvendor system. We perform a simulation study to investigate the advantage of the Bayesian updating approach over the traditional MLE approach. We conclude that the Bayesian pproach offers a better learning technique when one lacks of good understanding of the demand pattern in the first few periods. Since inventory policy affects the information acquisition and-the demand distribution updating process, how to determine the optimal inventory policy when the demand distribution is yet to be learned is the focus of the latter part of the thesis. We investigate the effect of demand censoring on the optimal policy in newsvendor inventory models with general parametric demand distribution and unknown parameter values. We provide theoretical proof of the conjecture that it is better off to adopt a higher than the myopic optimal policy in the initial periods when demand is learned in a censoring system. We show that the newsvendor problem with observable lost sales reduces to a sequence of single-period problems while the newsvendor problem with unobservable lost sales requires a dynamic analysis. We explore the economic rationality for this observation and illustrate it with numerical examples. / Business, Sauder School of / Graduate

A decision maker who is facing a random demand for a perishable product, such as newspapers, decides how many units to order for a single selling period. This single-period inventory problem is often referred to as the \classic newsvendor problem", in which the selling price is ¯xed, the order must be made before the selling period, and the decision maker is risk-neutral. If the decision maker orders too many (overage), the inventory cost will be too high. If the decision maker orders too few (underage), the potential pro¯t will be lost. The optimal order quantity is a balance between the expected costs of overage and underage. This thesis investigates an extension of the classic newsvendor problem. In this extension the demand depends on the selling price, the decision maker may obtain an additional order at a higher price during the selling period, and the decision maker is risk-averse (not risk-neutral). The problem is to ¯nd optimal order quantity and selling price so that the expected utility of the risk-averse decision maker is maximized. This thesis examines the relationship between the order quantity and the sell- ing price for di®erent risk-averse decision makers in this extended newsvendor problem de¯ned above. The result shows that the relationships are consistent for some decision makers but not for others. For example, if the decision maker exhibits a constant absolute risk aversion (CARA), the optimal order quantity will decline when the selling price increases. If the decision maker has constant relative risk aversion (CRRA), the relationship is complex. This thesis ¯nds that if it is just known that the decision maker is risk-averse, the optimal order quantity placed is less than that made by a risk-neutral decision maker. Further more, the risk-averse decision maker's optimal order quantity falls when her/his risk aversion increases. However, the relationship between order quantity and selling price is still indeterminate in this case. This extension of the classic newsvendor problem provides a more realistic dy- namic setting than before, therefore providing an excellent framework for exam- ining how the inventory problem interacting with the marketing issue (selling price) will in°uence decision makers at the ¯rm level. It also provides an inte- grated framework for investigating di®erent variations of newsvendor problems. Thus, this thesis will motivate and encourage more applications of the newsven- dor problem which is a foundation of many supply chain management problems.

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