Comparison of two methods for customer differentiation

In response to customer specific time guarantee requirements, service providers can offer differentiated ser- vices. However, conventional customer differentiation methods often lead to high holding costs and may have some practical drawbacks. We compare two customer differentiation policies: stock reservation and pipeline stock priority for high priority customers. We derive exact analytical expressions of the waiting time distri- bution of both types of customers for a stock reservation policy. We then provide accurate approximation methods for a pipeline stock priority policy. By comparison, we offer insights concerning which method should be used under different service level requirements

Enabling customer satisfaction and stock reduction through service differentiation with response time guarantees

In response to customer specific service time guarantee requirements, service providers can offer differentiated services. However, conventional customer differentiation models based on fill rate constraints do not take full advantage of the stock reduction that can be achieved by differentiating customers based on agreed response times. In this paper we focus on the (S − 1, S, K) model with two customer classes, in which low priority customers are served only if the inventory level is above K. We employ lattice paths combinatorics to derive the exact distribution of the response time (within leadtime) for the lower priority class and provide a simple and accurate approximation for the response time of the high priority class. We show that the stock levels chosen based on agreed response times can be significantly lower than the ones chosen based on fillrates. This indicates that response time guarantees are an efficient tool in negotiating after-sale contracts, as they improve customer satisfaction and reduce investment costs

On the Value of Customer Information for an Independent Supplier in a Continuous Review Inventory System

We consider the inventory control problem of an independent supplier in a continuous review system. The supplier faces demand from a single customer who in turn faces Poisson demand and follows a continuous review (R, Q) policy. If no information about the inventory levels at the customer is available, reviews and ordering are usually carried out by the supplier only at points in time when a customer demand occurs. It is common to apply an installation stock reorder point policy. However, as the demand faced by the supplier is not Markovian, this policy can be improved by allowing placement of orders at any point in time. We develop a time delay policy for the supplier, wherein the supplier waits until time t after occurrence of the customer demand to place his next order. If the next customer demand occurs before this time delay, then the supplier places an order immediately. We develop an algorithm to determine the optimal time delay policy. We then evaluate the value of information about the customer’s inventory level. Our numerical study shows that if the supplier were to use the optimal time delay policy instead of the installation stock policy then the value of the customer’s inventory information is not very significant.Accepted versio

A Real-Time Decision Rule for an Inventory System with Committed Service Time and Emergency Orders

n this paper, we study the inventory system of an online retailer with compound Poisson demand. The retailer normally replenishes its inventory according to a continuous review (nQ, R) policy with a constant lead time. Usually demands that cannot be satisfied immediately are backordered. We also assume that the customers will accept a reasonable waiting time after they have placed their orders because of the purchasing convenience of the online system. This means that a sufficiently short waiting time incurs no shortage costs. We call this allowed waiting time “committed service time”. After this committed service time, if the retailer is still in shortage, the customer demand must either be satisfied with an emergency supply that takes no time (which is financially equivalent to a lost sale) or continue to be backordered with a time-dependent backorder cost. The committed service time gives an online retailer a buffer period to handle excess demands. Based on real-time information concerning the outstanding orders of an online retailer and the waiting times of its customers, we provide a decision rule for emergency orders that minimizes the expected costs under the assumption that no further emergency orders will occur. This decision rule is then used repeatedly as a heuristic. Numerical examples are presented to illustrate the model, together with a discussion of the conditions under which the real-time decision rule provides considerable cost savings compared to traditional systems