Analysis of an Economic Order Quantity and Reorder Point Inventory Control Model for Company XYZ

As a result to today’s uncertain economy, companies are searching for alternative ways to stay competitive. In which, Company XYZ has been faced with an ineffective forecasting method that has lead to multiple product stock outs. The issue faced has caused sales loss as well as profit loss, which companies can not afford to lose if they want to stay competitive. This project goes through the process of analyzing the company’s current forecasting model and recommending an inventory control model to help them solve their current issue. As a result, an Economic Order Quantity (EOQ) and a Reorder Point was recommended along with two forecasting techniques to help them reduce their product stock outs. In addition, a cost estimate was done to compare both their current and the recommended models. As a result, Company XYZ would able to reduce their overall total cost from $13,654 to $5,366. This was a cost reduction of approximately 61%, which summed to a total saving of about $8,300 per quarter. It is highly recommended that Company XYZ implements the inventory control model provided in order to reduce stock out and back orders. By doing so, the company could also reduce the total cost associated with their inventory. If the methods are used effectively, the company could remain competitive among their industry. Introduction With today’s uncertain economy, companies are searching for alternative methods to keep ahead of their competitors by effectively driving sales and by cost reduction. Big retail companies do not stand a chance in today’s environment if they do not have an appropriate inventory control model intact. The Economic Order Quantity and a Reorder Point (EOQ/ROP) model have been used for many years, but yet some companies have not taken advantage of it. An Economic order quantity could assist in deciding what would be the best optimal order quantity at the company’s lowest price. Similar to EOQ, the reorder point will advise when to place an order for specific products based on there historical demand. The reorder point also allows sufficient stock at hand to satisfy demand while the next order arrives due to the lead time. Since retail can be unpredictable and competitive, the interest of seeing how forecasting can affect the economic order quantity (EOQ) and reorder point led to assist Company XYZ in finding alternative methods to solved their forecasting issues. Topic The topic of this project was to recommend an Analysis of an Economic Order Quantity and Reorder Point Inventory Control Model for Company XYZ. Problem The current forecasting model in placed at Company XYZs has brought problems due to ineffective forecasting that has resulted in product stock outs and loss of sales. The forecasting method used is the rolling average method, which takes previous historical demand and calculates the average for the next forecasting period. By doing this method, variability is not taken into consideration due to the historical demand which can cause inaccurate forecasting results. Essentially, the purpose of this project was to recommend alternative ways to help reduce the Company’s stock outs by providing a more effective forecasting method along with an Economic Order Quantity and Reorder Point model. In the approach of doing so, only thirteen top selling products that range from seasonal to annual sales will be analyze from their previous 2 years or 8 quarters. In addition, a cost estimate would be calculated to see the significance between both current model and recommended model. Literature Review Economic Order Quantity History “Origin of the Economic Order Quantity formula; transcription or transformation?” Bill Roach explains how the origin of the Economic Order Quantity began in his article, “Origin of the Economic Order Quantity formula; transcription or transformation?” published in 2005. Roach explains that the Economic Order Quantity (EOQ) has been a well-known formula that calculates the optimal economic order quantity. He also mentions how Ford W. Harris contribution to the EOQ formula was significant. Harris was always a self taught individual that only received formal schooling that extended throughout high school. He managed to write and publish the economic order quantity formula in 1915 as an undergraduate student. (Roach 2005) The Economic Order Quantity (EOQ) formula has been used in both engineering and business disciplines. Engineers study the EOQ formula in engineering economics and industrial engineering courses. On the other hand, business disciplines study the EOQ in both operational and financial courses. In both disciplines, EOQ formulas have practical and specific applications in illustrating concepts of cost tradeoffs; as well as specific application in inventory (Roach 2005). “Optimizing Economic Order Quantity” In the article, “Optimizing Economic Order Quantity,” published by Dave Piasecki in 2001, focused on the economic order quantity. Piasecki mentions that in today’s leading technology, many companies are not taking advantage of the fundamental inventory models. There are various software packages in aiding companies with inventory control, but if the data inputted are inaccurate, it may lead to poor results. (Piasecki 2001) In order to have suitable results for any inventory model, accurate product costs, activity costs, forecasts, history, and lead times need to be in place. (Piasecki 2001) As a result of bad data, companies have had bad experience with some inventory models, and that is one of the reasons they do not take advantage of the EOQ model. Piasecki also explains that another reason why a company does not take advantage of the EOQ model is because management does not know how it works. (Piasecki 2001) Even if a company has implemented a leading software package to help them, if they do not know how the system works it could cost more harm than good. Many times the users do not understand how the data is calculated and how the system is set up. They simply rely on the system built-in default software calculations, which in most cases, the system is “out of whack”. (Piasecki 2001) In order to prevent the system from going “out of whack,” management as well as the user, need to obtain proper knowledge of the EOQ concepts and how they are derived. The software is only design to aid and not replace the traditional way of running a business. “The EOQ Inventory Formula” At times, people in the retail business or in the manufacturing industry do not know or do not understand what EOQ stands for and how it is used? In this article, “The EOQ Inventory Formula,” written by James A. Cargal clearly explains the fundamental theory of the Economic Order Quantity. Cargal published this article from Troy State University Montgomery. The article is straight forward and easy to understand. Cargal does a great job explaining each variable and how it’s used accordingly. The formula is written as illustrated in equation 1 and described as the following,