MicrosoftВ® Office ExcelВ® 2007: Data Analysis and Business Modeling (Bpg -- Other)

Overview

In Chapter 67, “The Economic Order Quantity Inventory Model,” we used the economic order quantity (EOQ) to determine an optimal order quantity and production batch size. We assumed that demand occurred at a constant rate. Thus, if annual demand occurred at a rate of, for example, 1200 units per year, then monthly demand would equal 100 units. As long as demand occurs at a relatively constant rate, the EOQ is a good approximation of the cost-minimizing order quantity.

In reality, demand during any time period is uncertain. When demand is uncertain, a natural question is how low to let the inventory level go before placing an order. We call the inventory level at which an order should be placed the reorder point. Clearly, a high reorder point will decrease shortage costs and increase holding costs. Similarly, a low reorder point will increase shortage costs and decrease holding costs. At some intermediate reorder point, the sum of shortage and holding costs is minimized. Our first example shows how to determine a reorder point that minimizes expected ordering, shortage, and holding costs based on the following two assumptions:

The second example shows how to determine the optimal reorder point based on a service level approach. For example, a 95 percent service level means that we set the reorder point at a level ensuring that, on average, 95 percent of all demand is met on time. It is usually difficult to determine the cost of a shortage in either the back-ordered case or the lost-sales case. For that reason, most companies set reorder points by using the service level approach.

Note 

On this book’s companion CD, for the back ordered and lost sales models, I’ve included a worksheet named Protected in which all formulas are protected for both the back-ordered and lost-sales cases. You can use these worksheets as templates.

The back-order case   See the file Reorderpoint_backorder.xlsx, shown in Figure 68-1, for the data I’m using in this example. Let’s first suppose that each shortage results in the back-ordered units. In other words, a shortage does not result in any lost demand. We assume that each unit we are short incurs a cost cB. In this case, the reorder point depends on the following quantities:

Figure 68-1: Determining reorder point when shortages are back ordered

Let’s suppose that a department store wants to determine an optimal inventory policy for ordering electric mixers. They have the following information:

After we enter K, h, and D in cells C2:C4, our spreadsheet computes the EOQ (100 mixers) in C5. After we enter SOC, annsig, meanLT, and sigmaLT in cells C7:C10, our spreadsheet computes in cell C14 the reorder point that minimizes the sum of expected annual holding and shortage costs (51.63 mixers). Thus, our department store should order 100 mixers whenever their stock decreases to 51.62 (or 52) mixers.

The safety stock level associated with a given reorder point is reorder point–mean lead time demand. The department store maintains a safety stock level of 51.62–38.46=13.16 mixers, computed in cell C15. Essentially, the safety stock is always in inventory, resulting in extra holding costs. A higher level of safety stock will, of course, reduce shortages.

The lost-sales case   Now suppose that each shortage results in a lost sale. The cost associated with a lost sale is usually estimated as the back-order penalty plus the profit associated with a unit sold. Suppose that the department store earns a $20 profit on each mixer it sells. The unit shortage cost for the lost-sales case is then $40 ($20 lost profit+$20 back-order penalty).

In the file Reorderpoint_lostsales.xlsx, shown in Figure 68-2, you can see the work I did to estimate the reorder point for the lost-sales case. After entering in cell C7 of the spreadsheet the lost-sales cost of $40, we find the optimal inventory policy is to order 100 mixers and place an order when inventory is down to 54.23 mixers. Our safety stock level is 15.77 mixers, and 2.4 percent of the store’s demand for mixers will be unmet. Notice that the assumption of a lost sale has increased our reorder point and reduced the probability of a shortage. This happens because the increased cost of a shortage (from $20 to $40) makes us more eager to avoid shortages.

Figure 68-2: Determining reorder point when sales will be lost

Increased uncertainty greatly increases the reorder point. For example, in the lost-sales case, if the standard deviation for lead time is one week (0.019 years) rather than 0, the reorder point increases to 79.50 mixers and the safety stock more than doubles from the case in which our lead time was known with certainty.

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