1. DEMAND VARIABILITY IN SUPPLY CHAINS Eren Anlar

2. Literature Review Deuermeyer and Schwarz (1981) and Svoronos and Zipkin (1988) provide techniques to approximate average costs in a continuous review model with Poisson demand. Both assume no restriction on when the retailers may order. Shapiro and Byrnes (1992) examine demand variance in the medical supply industry. Their result suggest that reducing the supplier’s demand variance may benefit a supply chain. Lee et al. (1997) identifies the four causes of the bullwhip effect, which is the common name given to the common observation that demand variance propagates up a supply chain.

3. Drezner et al. (1996) and Chen et al. (1997) studied demand updating. Cohen and Baganha (1998) consider supply chain demand variance, but do not consider strategies for reducing the variance of the retailers’ orders. Cachon (1999) shows that there are five variables that influence the supplier’s demand variance, which are: the consumer demand variability, the number of retailers, the retailers’ batch size, the retailers’ order interval length, and the alignment of the retailers’ order intervals. Literature Review

4. Axsater (1993) and Chen and Zheng (1997) provide exact methods to approximate average costs in a continuous review model with Poisson demand.They assume no restriction on when retailers may order. Cachon (1995) provides an exact algorithm for periodic review. Assumes no restriction on when retailers may order. Chen and Samroengraja (1996) obtain exact results for a model in in which retailers implement base stock policies at fixed intervals and only one retailer orders at a time.

5. Literature Review Eppen and Schrage (1981) study a two-echelon model in which the supplier receives inventory at fixed intervals Federgruen and Zipkin (1984), Jackson (1988), Jackson and Muckstadt (1989), McGavin et al. (1993), Nahmias and Smith (1994) Graves (1996) allow shipments to retailers at intermediate times between replenishments to the supplier, allowing the supplier to hold some stock. They all assume synchronized ordering and unit ordering. Song (1994) showed, for a particular definition of demand variability, that the buffer cost will increase with increasing variability.

6. Lee et al. (1996) show that the supplier’s actions do not impact the retailers, nor do the retailers’ actions influence the supplier’s demand variance. They assume synchronized ordering and retailers orders are always filled either by the supplier or an outside source. Aviv and Federgruen (1998) consider both synchronized and balanced alignments and find that balanced ordering generally has lower costs. Their model has heterogeneous retailers and a supplier capacity constraint. Literature Review

7. Kelle et al. (1999) conclude that negative effect of high variability and uncertainty can be decreased by small frequent orders. These orders are economical for the partners in the supply chain if the ordering costs are small relative to the inventory holding cost.

8. Fisher and Raman (1996) Quick Response: apparel industry initiative intended to cut manufacturing and distribution lead times through a variety of means, particularly the cost of excess inventory that must be sold below cost at the end of the season and of lost sales due to inventory stockouts. They showed that Quick Response could reduce stockout and markdown costs by reducing lead time sufficiently to allow a portion of production to be committed after some initial demand has been observed.

9. Ridder et al. (1998) Considers a Newsvendor problem Concludes that reduction of the demand uncertainty in stochastic production and inventory systems is economically favorable for most demand distributions. However, for some demand distributions a reduction of the demand uncertainty will not result in the desired cost reduction.

10. The numerical example shows that balancing the retailers’ order does reduce costs. A reduction in the supplier’s demand variance will further reduce the supplier’s average inventory. Two strategies that both reduce the supplier’s demand variance and total supply chain costs: Balancing retailer order intervals: effective in broad range of conditions. Flexible quantity strategy: the retailers’ order frequency is held relatively constant by increasing the retailers order intervals and decreasing the fixed batch size. This is effective when there are few retailers and consumer demand variability is low. In addition, effective when the supplier is required to provide a high fill rate. Cachon (1999)

11. One supplier distributes a single product to N identical retailers. Retailers implement scheduled ordering policies (i.e. Orders occur at fixed intervals and are equal to some multiple of a fixed batch size), which influences the propagation of demand variance within a supply chain. Model

12. Sequence of events at each period: 1.Demand is realized 2.Firms submit orders to their inventory sources 3.Shipments are released 4.Costs are assessed 5.Shipments are received Supplier’s demand variance is maximized then the retailers’ orders are synchronized (i.e. all retailers order in the same periods). It is minimized when the retailers’ orders are balanced (i.e. same number of retailers order each period). Cachon (1999)

13. Two benefits of low supplier demand variance: 1. For a fixed supplier fill rate, lower demand variance allows the supplier to carry less inventory on average. 2.For a fixed supplier average inventory, lower demand variance reduces the retailers’ average lead time. However, increasing the retailer order intervals raises retailer’s holding and backorder costs. Also, decreasing batch size raises ordering costs. Dampening the supplier’s demand is only reasonable if the supplier’s costs represent a significant fraction of overall supply chain costs and if this action does not substantiallly raise the retailers’ costs. Cachon (1999)

14. Conclusion Reducing a supplier’s demand variance is an objective to adopt selectively. Advantegous when inventory holding costs are high relatively to ordering costs. Whether a reduction in demand uncertainty will result in cost reduction depends on many factors, such as, the definition of uncertainty, the structure of the demand distributions, and the ratio between the overage and underage costs.

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