- Account for the fact that supply chain demand is lumpy. In practice, a manufacturer or distributor does not order one unit at a time but instead often orders in a large lot. Thus, demand observed by different stages of the supply chain tends to be lumpy. Lumpiness adds to the variability of demand. For example, when using a continuous review policy, lumpiness may lead to inventory dropping far below the ROP before a replenishment order is placed. On average, inventory will drop below the ROP by half the average size of an order. The lumpiness can be accounted for in practice by raising the safety inventory suggested by the models discussed earlier by half the average size of an order.
- Adjust inventory policies if demand is seasonal. In practice, demand is often seasonal, with the mean and the standard deviation of demand varying by the time of year. Thus, a given ROP or OUL may correspond to ten days of demand during the low-demand season and only two days of demand during the peak demand season. If the lead time is one week, stockouts are certain to occur during the peak season. In the presence of seasonality, it is not appropriate to select an average demand and standard deviation over the year to evaluate fixed ROPs and OULs. Both the mean and the standard deviation of demand must be adjusted by the time of year to reflect changing demand. Corresponding adjustments in the ROPs, OULs, and safety inventories must be made over the year. It is best to evaluate all inventory parameters such as ROPs and OULs in terms of days of demand. A simple heuristic that keeps days of demand constant over time helps account for seasonality by automatically adjusting the ROP and OUL.
- Use simulation to test inventory policies. Given that demand is most likely not normally distributed and may be seasonal, it is a good idea to use a computer simulation to test and adjust inventory policies before they are implemented. The simulation should use a demand pattern that truly reflects actual demand, including any lumpiness as well as seasonality. The inventory policies obtained using the models discussed in the chapter can then be tested and adjusted if needed to obtain the desired service levels. Surprisingly powerful simulations can be built using Excel, as we discuss in Chapter 13. Identifying problems in a simulation can save a lot of time and money compared to facing these problems once the inventory policy is in place.
- Start with a pilot. Even a simulation cannot identify all problems that may arise when using an inventory policy. Once an inventory policy has been selected and tested using simulation, it is often a good idea to start implementation with a pilot program of products that are representative of the entire set of products in inventory. By starting with a pilot, many of the problems (both in the inventory policies themselves and in the process of applying the policies) can be solved. Getting these problems solved before the policy is rolled out to all the products can save a lot of time and money.
- Monitor service levels. Once an inventory policy has been implemented, it is important that its performance be tracked and monitored. Monitoring is crucial because it allows a supply chain to identify when a policy is not working well and make adjustments before supply chain performance is affected significantly. Monitoring requires not just tracking the inventory levels but also tracking any stockouts that may result. Historically, firms have not tracked stockouts very well, partly because they are difficult to track and partly because of the perception that stockouts affect the customer but not the firm itself. Stockouts can be difficult to measure in a situation such as a supermarket, where the customer simply does not buy the product when it is not on the shelf. However, there are simple ways to estimate stockouts. At a supermarket, the fraction of time that a shelf does not contain a product may be used to estimate the fill rate. Stockouts are in fact easier to estimate online, where the number of clicks on an out-of-stock product can be measured. Given the fraction of clicks that turn into orders and the average size of an order, demand during a stockout can be estimated.
- Focus on reducing safety inventories. Given that safety inventory is often a large fraction of the total inventory in a supply chain, the ability to reduce safety inventory without hurting product availability can significantly increase supply chain profitability. This is particularly important in the high-tech industry, in which product life cycles are short. In this chapter, we discussed a variety of managerial levers that can help reduce safety inventories without hurting availability. Supply chain managers must focus continuously on using these levers to reduce safety inventories.
Source: Chopra Sunil, Meindl Peter (2014), Supply Chain Management: Strategy, Planning, and Operation, Pearson; 6th edition.
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