Burlington Northern Santa Fe’s Inventory Management Essay (Article)

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Burlington Northern Santa Fe (BNSF) is a railroad company in North America that produces the highest customer satisfaction by transporting assets quickly and safely. The company recognizes the importance of the best quality inventory management, guaranteeing a trustworthy flow of goods from manufacturers to storage facilities and outlets. While the benefits of organized inventory management include increased automation, efficiency, and productivity, the disadvantages of poor manual inventory management are long operational time, human errors, and outdated systems.

Since BNSF aims to improve safety and increase efficiency, having well-organized inventory management is necessary. There are several potential benefits of introducing automated management with drones, cameras, and optional character recognition technologies. They are justified by “a 25% increase in productivity and a 30% improvement in stock use efficiency” and a balanced supply and demand chain (Package X, 2021). Most important is that it eliminates human errors as the scans help to monitor the transported assets and those that enter warehouses easily. Although investing in computerized systems is expensive, it compensates for all risks of losing sales and goods.

While traditional inventory management systems use human resources for operations, an automated inventory system relies on technologies. It, in turn, saves 95% of the time, which can be allocated to other tasks (Package X, 2021). Moreover, the cameras and drones used by BNSF provide real-time insights and updates on inventory. Such records identify the early problems and save the company money. For example, if BNSF sees the loss of inventory items or problems with the chain supply, it checks the camera records to find the exact time and place of the incident. This benefit is also facilitated by the convenience of easily tracking the chain of custody from anywhere and anytime.

If automated inventory management is vital and beneficial, the manual inventory system needs to improve. The reason is that it has many restrictions during data analysis, which sometimes delays critical tasks. Similarly, the fact that such systems use labor and human resources makes the management even slower in reordering, forecasting, and planning (Package X, 2021). While strong automated inventory management can monitor several inventory levels at once and integrate them into their calculations, poor manual inventory sorts assets through outdated inventory sheets. Thus, companies that do not receive real-time inventory data can quickly lose sales or make unavoidable mistakes.

Like many other companies, BNSF selects multiple product lines to transport by its railways during each business period. However, if the company had poor inventory management, it would not realize how many assets it has, which results in overstock or understock. Additionally, storing inventory for extended periods requires a lot of money due to high maintenance costs and much storage space, limiting restocking simultaneously. Considering that BNSF focuses on customer satisfaction, it should avoid delivery delays, which poor inventory systems could cause (Package X, 2021). Consequently, when the customers do not receive their items on time, the transporting company loses its clients and source of revenue.

To conclude, incorporating drones, fixed camera systems, and optical character recognition is pivotal for a railroad company like BNSF that focuses on customer satisfaction and safe delivery. It results in efficient and fast data monitoring, productivity, and fewer human errors. On the contrary, a poor inventory management system limits the company’s awareness of the business stocks, inventory, and delivery problems. Hence, the BNSF would operate slowly and inefficiently, losing money and clients.

Reference

Package X. (2021). . Web.

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