A Technique for Applying EOQ Models to Retail Cycle Stock Inventories

A TECHNIQUE FOR APPLYING EOQ MODELS TO RETAIL CYCLE STOCK INVENTORIES(*) This article illustrates a practical technique for managing retail cycle stock inventories. Cycle stocks are those maintained to satisfy normal demand. Anticipation stocks, on the other hand, maintained to deal with significant seasonal variations in demand, and safety stocks (the amount of inventory needed to protect against completely running out), are assumed to be relatively small. Effective inventory management is essential in the operation of any business. As shown in the case example below, improvements in inventory management can achieve worthwhile cost savings. At the same time, small businesses require inventory management systems that are simple, easy to use, inexpensive, and keyed to current data sources and modes of operation. A basic inventory management device is the economic order quantity (EOQ). An EOQ strategy minimizes the total cost of ordering and carrying cycle stocks. While EOQ strategies are theoretically optimal, they present many practical problems of implementation, especially for small businesses. First, as Blackstone and Cox(1) suggest, EOQ strategies require continuous monitoring of inventory balances. Second, as noted by Lin,(2) keeping EOQ values current necessitates frequent updating of ordering and carrying cost information. These problems can be quite serious if EOQ values are being calculated separately for each item in the product line. Third, the computation of EOQs requires accurate knowledge of ordering costs per order and carrying costs per dollar of inventory. Some rough estimates of carrying costs exist.(3) However, ordering cost estimates are harder to come by. Silver and Peterson(4) essentially argue that this is largely because ordering is a staff activity, and it is difficult to allocate the time spent by various staff members to a given order. The technique illustrated in this article attempts to meet the needs of small businesses in the following ways: 1. Order "quantities" are calculated, not in units for each single stock item, but in dollars for each vendor. This approach simplifies the tasks of monitoring and analysis by taking advantage of existing methods of record keeping and of doing business. Also, Silver and Peterson(5) show that the approach is optimal if the incremental costs of including an extra item in an order from a vendor are small. 2. It is not necessary to make explicit determinations of or assumptions about ordering and carrying costs. Other authors, including Silver and Peterson,(6) Banks and Heikes,(7) and Eaton,(8) have advocated similar strategies, but this technique is a new adaptation, focused on the small business environment. 3. The only data required are those already available. 4. The technique is designed for easy implementation on spreadsheet software. This makes it easy to use and also takes advantage of the microcomputers now widely available. DEVELOPMENT OF THE TECHNIQUE The operation of this inventory management technique can be broken down into two steps: (1) determine if the current inventory management strategy is consistent among all vendors, and (2) if not, modify the strategy to achieve consistency. In this technique, the decision variable is [Q$.sub.i], the order quantity for vendor i expressed in dollars. It can be shown that the economic (cost minimizing) order quantity for a given vendor is [Mathematical Expression Omitted] where [D$.sub.i] = The weekly demand for goods bought from vendor i, expressed at cost, i.e., the cost-of-goods-sold accounted for by vendor i. (i=1,I) [Q$.sub.i] = The amount (in dollars) ordered from vendor i in each order. A = The administrative cost of placing and receiving an order, assumed to be the same for all vendors. r = The cost of carrying one dollar's worth of inventory for a week, assumed to be the same for all vendors. …