Transportation Forecasting: Strategic Planning

Summary

Logistics is an important part of the everyday activity of the armed forces. The process of transportation that involves goods, equipment, and personnel might be expensive (Xiong et al., 2017). As a part of my education course, I have researched a paper on transportation forecasting by Xavier Smith, a logistics officer from Embry-Riddle Aeronautical University. There was a necessity to overview and decrease the spending on his units. The changes were developed for Fiscal Year 18 that began on October 1, 2017 (Smith, 2017). The purpose of this paper is to understand what measures can be taken to decrease the spending and define the application area, methodology, and planning level of the work.

Knowledge/Application Area 1: Transportation Management

The research paper under analysis fits within the knowledge application area of transportation management. The ground for my assigning it to this category is that Smith’s objective of analyzing and optimizing the transportation process for his unit belongs to the area of coordination of goods flow. Besides, from a historical viewpoint, transportation management and logistics are closely connected to the military (King & Biggs, 2016). A systematic approach to the transportation of the goods needed was developed under the tight conditions of World War II.

Knowledge/Application Area 2: Financial Management

The other knowledge application area that suits the report analyzed is financial management because, among the author’s obligations, there was a task to find a way to reduce costs. In fact, the goal set by the higher command was to cut the spending on transportation by 15% (Smith, 2017). This refers to the sphere of financial management that includes directing, analyzing, and planning the utilization of finances.

Methodology 1: Other Descriptive Models (Forecasting)

The paper emulates the methodology of forecasting because Smith by analyzing historical data on a year’s average and the allocation of sources suggests a possible budget for Fiscal Year 18. In fact, during the previous 7 years, the expenditures ranged from 375,000 to 830,000 dollars (Smith, 2017). In addition to reviewing the data, Smith asked a person who had held the position of logistics officer before him about possible difficulties and perils that might prevent the officer from optimizing logistics (Smith, 2017). This descriptive model and the least cost method helped the author to calculate what the minimal transportation costs would be for the highest spending year.

Table 1: The Results of Using the Least Cost Method, 2017.

Methodology 2: Optimization Modeling and Solution Techniques

Methodology of optimization modeling and solution techniques also fits the paper on transportation forecasting by Smith. This type of methodology suggests finding better variants for business processes and improving them in accordance with the needs of a company (Tsadikovich et al., 2016). In fact, Smith’s activities of minimizing the logistics costs and implementing several changes in his units correspond to the tasks of optimization modeling and solution techniques.

Planning Level 1: Strategic

The planning level of strategy is demonstrated in the work on transportation forecasting by Smith. A part of strategic planning is analyzing the business and setting realistic objectives which Smith does in his paper. As shown above, the author has reviewed the previous topic-related data and set a goal of making the logistics costs lower. In fact, it is a realistic objective that can be achieved by implementing particular changes to the system.

Planning Level 2: Operational

In the paper under analysis, the planning level of operation is also represented. In fact, at this level, a detailed plan is prepared and the key actions are identified. It also demonstrates what the conditions for achieving the goal set are and what circumstances or disruptions might negatively affect the process (Achahchah, 2018). On the basis of the analysis of the previous data, the author has concluded that there are no possibilities to decrease the cost of equipment transportation (Smith, 2017). However, he has planned to cut the spending by 5% by making his units self-transport the personnel (Smith, 2017). Besides, to tackle the problem of disruption, it is necessary to increase the readiness for unforeseen events (Choi et al., 2016). The implementation of all these measures gives a reason to suggest that the budget needed for Fiscal Year 18 will be 15% lower (Smith, 2017). Thus, they can help reduce the spending on transportation of equipment.

References

1. Achahchah, M. (2018). Lean transportation management: Using logistics as a strategic differentiator. CRC Press.
2. Choi, T. M., Chiu, C. H., & Chan, H. K. (2016). Risk management of logistics systems. Transportation Research Part E: Logistics and Transportation Review, 100(90), 1-6.
3. King, B., & Biggs, R. C. (2016). Spearhead of logistics: A history of the United States army transportation corps. Government Printing Office.
4. Smith, X. (2017). Transportation forecasting. Embry-Riddle Aeronautical University.
5. Tsadikovich, D., Levner, E., Tell, H., & Werner, F. (2016). Integrated demand-responsive scheduling of maintenance and transportation operations in military supply chains. International Journal of Production Research, 54(19), 5798-5810.
6. Xiong, B., Li, B., Fan, R., Zhou, Q., & Li, W. (2017). Modeling and simulation for effectiveness evaluation of dynamic discrete military supply chain networks. Complexity.