The well-known Economic Order Quantity (EOQ) model assumes that the demand and ordering cost is constant over time, and there is no lead-time for each order delivered. (Harris, 1913) The purpose of the EOQ model is to help the manufacturer determine the best order size that could minimize the total inventory holding cost and ordering cost. However, in reality, the demand and production lead-time both are not constant.
This implies that the manufacturer cannot predict the exact order size to meet the future demands; besides, there is uncertainty about the date on which the manufacturer will receive its orders. In order to prevent the high cost of loss in goodwill, the manufacturer is incented to place larger size orders. Therefore, the actual optimal order size will be larger than the economic order quantity in reality. A higher inventory level provides higher levels of product availability and better customer service; however, it raises the average inventory level and increases the inventory holding costs. This leads to problems in terms of loss in value, since certain products such as food with shorter shelf life cycles are prone to more rapid spoilage and obsolescence. Therefore, the EOQ model is inadequate and should not be used as a one-stop solution for inventory management.
Woolsey (1988) has already criticized the traditional EOQ model as unrealistic, since the assumptions of this model are not logical in today’s digital world. The model was created and taught by the academics who according to Woolsey have little actual business experience. Moreover, the model is also too easy to explain and manipulate. Because of the unrealistic assumptions, Woolsey also claimed that the model is too easy to use and calculate. Take the parameter “C” as in the cost of the item in dollars per unit as an example. Woolsey argued that an actual company would usually take the cost accounting system into consideration when calculating the ordering cost per unit since the value of cost (lot sizes) would be different when adopting a different cost accounting method. Besides, he also argued that the cost value should be used as its present value with adjusting for inflation; otherwise, the value of the cost will not be accurate in some countries where the inflation rate is high.
To my point of view, it is a common problem in reality, since it usually brings more complexity for the companies to define their cost per order and carrying cost per unit precisely, and it usually involves much more detailed costs such as time, order process handling costs, transportation costs, etc., the value of which could be substantial. In addition, according to Tanel (2012), the EOQ model is very insensitive to the errors generated from such parameters, because they are muted in the square root function of the EOQ formula. Therefore, the order quantity obtained from the EOQ model could be far from the real optimized order quantity.
Although each parameter in the EOQ model might contain errors in reality, the model is still applicable for some industries, such as products that have more steady demand throughout the year, large volume of stock, as well as the constant and repetitive ordering pattern of stock. It is especially applicable for buy-to-stock distribution centers and make-to-stock manufacturers where lead-time is a relatively less sensitive factor. Further, it helps the company (especially the small-scale ones) maintain a sufficient inventory level to match the customers’ demands. All in all, the model provides a base line of the order quantity and where the re-order point is, which assists the company to balance the re-stocking process and to offer better customer services by ensuring the availability of inventory.
Harris, F. W. (1913). How Many Parts to Make at Once. Factory, The Magazine of Management , 10 (2), 135-136.
Tanel, T. (2012, June 20). How to Make EOQ Relevant Again. Retrieved September 24, 2013, from Supply and Demand Chain Executive: http://www.sdcexec.com/article/10732246/how-to-make-eoq-relevant-again
Woolsey, G. (1988). A requiem for the EOQ: an editorial. Production and Inventory Management Journal , 68-72.