The business sector is shifting towards prioritizing the embrace of inventory management systems for corporate tenacities. Optimizing a communal through inventory system is conceivable, as the approach empowers business entities to hold onto a specific operational level that eliminates the out-of-stock circumstances (Cholowicz & Orlowski, 2016). The inventories also support low-cost operations – a fact that is an advantage to businesses. The most commonly used inventories are perpetual and periodic inventory systems.
Inventory systems, although having the same trade benefits, are practically different. These systems work in managing the demands of the customer in a customized manner. According to Cholowicz and Orlowski (2016), the perpetual system appears to be superior, considering that it upholds a continuous sales track. Additionally, this system occurs as an innovation that averts stock-outs. On the other hand, periodic inventory does not keep detailed records for every inventory item under scrutiny. The technique can determine an ending inventory by making every item count (Cholowicz & Orlowski 2016). Periodic inventory’s ability to compute cost adheres to the SECT costing method. The systems’ deliverability aptitudes are unique and specific to the function.
Perpetual inventory systems are more germane to the demands of various companies today. However, as an example, the businesses selling services are small or just starting up; therefore, the suitable inventory is the periodic system. Periotic inventory effortlessly offers starting up or small businesses, such as a factory that sells milk products, a straightforward and easy way of manipulating the sales out. As a result, even though the perpetual system is the dominant between the two, periodic is better in supporting small businesspersons by working as an asset for the category. In times of managing sales out, periotic system is the best.
Reference
Cholodowicz, E., & Orlowski, P. (2016). Comparison of a perpetual and PD inventory control system with smith predictor and different shipping delays using bicriterial optimization and SPEA2. Kwartalnik Pomiary Automatyka Robotyka, 3, 5-12. Web.