John E. Boylan

Intermittent Demand Forecasting


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rate of 0.40 yields a unit fill rate of 1 minus left-parenthesis left-parenthesis 1 minus 0.4 right-parenthesis times 0.466 right-parenthesis equals 1 minus 0.28 equals 0.72, agreeing with our original calculation.

      3.3.4 Summary

      In this section, we have stressed that aggregate service and financial targets both need to be attained. Aggregate service level measures may be recorded at order, order line, or unit level and monitored accordingly. It may be beneficial to use more than one measure, so that service can be assessed from a variety of perspectives. If there is a need to convert from one measure to another, then relationships are available for this purpose. In all situations, it is important to gauge the financial implications of hitting service targets, to ensure that the targets are set at an appropriate level.

      Financial and service performance at the aggregate level are ultimately determined by the performance at SKU level. In this section, we begin with a brief discussion of financial measures, before moving on to potential service measures, at the level of the individual SKU, and when they may be most appropriately applied.

      3.4.1 Cost Factors

      Inventory holding costs can be assessed at SKU level based on the opportunity cost of capital, warehousing space costs, costs of potential pilferage and spoilage, and costs of stock obsolescence. Of these components, the opportunity cost of capital is generally the largest. Gardner (1980, p. 43) remarked on the difficulty of assessing the cost of capital, describing it as: ‘…a highly subjective measure, which depends on the risk environment of the firm and management goals for rates of return on investment’. The difficulty of measuring inventory holding costs is well recognised, although there may be benefits of organisations thinking through these costs as thoroughly as they can.

      The costs of stockouts can be assessed at SKU level, based on a penalty cost for backordering and the delay of fulfilment of an order line for a period of time. As mentioned in Chapter 2, there are two ways of estimating these costs. There can be a fractional charge of the unit cost per unit short (regardless of the duration of the stockout), or there can be a fractional charge per unit short per unit time. Both approaches suffer from the difficulty of making the charge reflect loss of customer goodwill, which is just as hard to quantify at SKU level as at an aggregate level.

      For some decisions, such as to stock or not to stock an item, it is common to use an approach based on holding and backordering costs, notwithstanding the difficulty in measuring them. To set OUT levels, we suggest that it is more straightforward to adopt a service‐driven approach, which will be the focus for the remainder of this chapter.

      3.4.2 Understanding of Service Level Measures

      There are various reasons for this. The measurement of inventory service may appear to be self evident, leading managers to take it for granted, not realising that there are numerous ways of measuring it. Moreover, the measure employed at an aggregate level may not be the same as the measure used at SKU level to determine OUT levels. Again, managers may not appreciate that there is such a difference and assume that it is measured in the same way at all levels. This is just one example of the need for training and development of staff involved in inventory management and demand forecasting. We return to this important issue in the final chapter of the book.

      3.4.3 Potential Service Level Measures

      There are three main service level measures that are employed at SKU level:

      1 Cycle service level: The fraction of replenishment cycles in which all of the demand can be satisfied directly from stock (denoted as ).

      2 Unit fill rate: The fraction of the total volume of demand that can be satisfied directly from stock (denoted as ).

      3 Ready rate: The fraction of time during which the net stock (stock on hand (SOH) minus backorders) is positive (denoted as ).

      In the definition of the cycle service level (CSL), a ‘replenishment cycle’ is the interval between two consecutive replenishment decisions (see, for example, Çetinkaya and Lee 2000). For a periodic review system, the replenishment cycle is the same as the review interval (R) because a replenishment decision is made every R periods.

      The unit fill rate measure translates naturally from the aggregate level to the level of the individual SKU. It is defined in the same way, as the fraction of the total volume of demand that can be satisfied directly from stock. It is an intuitive measure and allows all the necessary calculations to be made to inform the setting of OUT levels.

      The ready rate and the cycle service level assess conditions for order‐line and order fulfilment but they do not measure them directly. Starting with the ready rate, if the net stock is positive for 90% of the time, then there is the possibility of fulfilling all order lines during this portion of time. However, there is no guarantee that there will be sufficient stock to satisfy the entire quantity requested for every order line. For example, if the net stock is at two units, but four units are requested by a customer, then their order line cannot be fully satisfied.

      Turning now to the cycle service level, suppose that in 10% of the review intervals, not all demand can be met from stock. This does not mean that all of the order lines will be unfulfilled in these review intervals; it is possible that some, at least, may be filled completely.

      In considering the selection of an SKU service level measure, it is helpful to distinguish between wholesaling and retailing environments. A wholesaler is in a business‐to‐business relationship, and should have reliable records of well‐defined orders for specific volumes of specific SKUs. In this case, the cycle service level (upper P 1) and the unit fill rate (upper P 2) are measurable. These measures can also be calculated by retailers if their customers submit orders, for example through an online platform. However, the situation is not the same for ‘walk‐in’ customers to a retail store. When customers enter the store, they may have only a rough idea of what they intend to buy. When the customers leave the store, the retailer knows what was bought, but not what was not bought because of stockouts, unless specific requests