This paper aims to provide my reflection while conducting simulations on the replenishment of rock salt and adjustable wrench spanner to exemplify actual determinations. To ensure the essentiality of my simulation framework, I employed an inventory model for a 12-week timeframe with the urge of finding order and reordering aims for two crucial schemes of decreasing the entire cost when holding inventories. The direct cost that determines inventories are ordering costs, lost opportunity cost, and, eventually, the holding costs (Stamatopoulos, 2019). Therefore, for a business entity to achieve significant profits in their business strategies, they should utilize the three types of costs to heighten their profits.
I employed the Economies of scale strategy to expatiate on the simulation model on the inventory basics. Following the contemplations that I ascertained from the simulation of the adjustable wrench spanner, the average demand is closely related to the predicted price and still with the consideration of the minimum standard deviation of one model. To delineate the simulation model, I established my schemes by rendering three costs: the holding costs, ordering costs, and the lost opportunity costs which I will employ centered on the expectations of the customer requirements as exemplified (Buil, 2018). Regarding the expected presumptions of demand by describing the archival information, I decided to employ the reorder level because the ordering cost was $6.3.To reduce the order of quantity, the employment of an economy of quantity scale was viable because the holding costs were about $0.04, which can be translated to $3.2 for 80 units in the 3 weeks.
On reflecting the rock salt replenishment, the average demand, which was $20, had a higher standard deviation of 9. However, the holding cost of the rock salt was slightly at $0.07; thus, reordering point would be delayed for a while since the ordering cost is at $6.3 per unit. While examining the rock salt and its essentiality to the customer requirements, it is clear that historical information significantly impacts making significant decisions. The bulk buying was supported with a low holding cost of $0.04. From the economies of scale strategy employed in the simulation. It aided in reducing order cost, which was at $6.30 per order for the adjustable wrench and rock salt.
From the two strategies (EOQ) employed in the simulation model of both adjustable wrench spanner and the rock salt, there has been no divergence on the consumer demand since both scenarios have an ordering of $6.3 per unit. Furthermore, the average demand and the cost of stock out for the two product is constant since they are employing constant ordering cost while the holding costs are varying with $0.03 per unit every week. From the results also, the varying ordering cost is constant, while the standard deviation of an adjustable wrench is slightly higher due to low EOQ.
The two challenges drawn from the simulation of rock salt and the wrench did not change the idea of inventory management. The simulation aided in the decision-making process because the resulting simulation figures help in predicting the holding cost and ordering cost. Also, it projects customer demand, inventory level at the end of the week, total cost, including stock out penalties, and the cumulative costs. One of the challenges of simulation is that the results do not imitate the real-life situations hence living a room for criticisms. However, simulation in this scenario helps in predicting future costs, and the inventory levels that help predict the future patterns ordering, holding, and the resultant costs due to these activities.
The determinants of the order size include demand, the cost of holding, cost of ordering, cost of running out of stock, and cost of economies of scale. Customer demand affects the number of units to be ordered. When the demand is high, the order per unit increases, while whenever the demand is low, the number of orders per unit reduces. When the orders per unit exceed the Economic Order Quantity, the cost of holding inventory, and ordering inventory increases, the holding costs include warehousing costs, insurance, among others. In contrast, the ordering costs include freight charges, customs duties, and taxes. When the order quantity exceeds the Economic Order Quantity (EOQ), the holding cost increases because the goods will remain in the warehouse for a long time before they are sold. When the orders per unit are below the Economic Order Quantity (EOQ), the business will face high cost due to stock out (Buil, 2019). According to the scenario simulation rock salt simulation above, the order cost remains constant for the 12 weeks because the order quantity did not the Economic Order Quantity (EOQ). The holding cost is varying over the 12 weeks because the order surpasses the demand severally.
Buil, I., Catalán, S., & Martínez, E. (2018). Exploring students' flow experiences in business simulation games. Journal of Computer Assisted Learning, 34(2), 183-192.
Buil, I., Catalán, S., & Martínez, E. (2019). Encouraging intrinsic motivation in management training: The use of business simulation games. The International Journal of Management Education, 17(2), 162-171.
Stamatopoulos, I., Chehrazi, N., & Bassamboo, A. (2019). Welfare implications of inventory-driven dynamic pricing. Management Science, 65(12), 5741-5765.
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