Summary
One of the critical enablers of effective transportation and logistics include the internet of things (IoT). The technology has immense benefits in the industry and is revolutionizing supply chain management. The innovation is comprised of multiple components that are categorized into communication, infrastructure, application, sensing, and service layers. Even though the technology has numerous benefits, it also presents a number of challenges in the transportation sector depending on the company nature that is deploying the system in its operations. This paper provides feedback on the artifact and assures that it fits well within the respective column and row of the BOK Matrix M9 and why it best fits within the cell that it has been assigned.
Knowledge/Application Area: Enterprise Integration
IoT is one of the significant developments in the realm of information technology and involves devices that correspond to each other and with multiple gadgets over the Internet. In the transportation and logistics sector, the technology enhances the visibility, responsiveness as well as compliance of a supply chain (Dhumale et al., 2017). The system enables firms and customers within the industry to locate their products at any time and monitor the condition of the goods in transit. The gadgets that make up the system efficiently gather information which is then analyzed and provided as precise helpful information which helps in informed decision-making. Therefore, the IoT falls within enterprise integration since it involves the technologies, processes as well as structures that link data, and applications from gadgets from all locations in an information technology setup.
Methodology: Optimization Modeling and Solution Techniques
IoT enables real-time geographical positioning (GPS) tracking of goods and provides automatic notification to the cargo owners. Further, the systems allow both companies and their customers to monitor the condition of their goods, including aspects such as humidity, temperature, and vibrations. The information allows firms to intervene right away should the system relay information that the goods are not in their desired state. The system can identify the undesirable traffic conditions in real-time and offer an alternative route to the driver of a track moving goods from one point to another. Therefore, based on this capability and looking at the BOK Matrix, IoT squarely lies within the optimization modeling and solution techniques. The technology involves the creation and use of a decision tool that can be applied in finding the best feasible solution to a challenge.
Methodology: Simulation Modelling and Analysis
The paper further emulates the methodology of simulation and modeling and analysis since IoT helps businesses to optimize their operations. The system can create a digital prototype that allows one to predict the performance in the real world. The simulation and analysis enable companies to understand the conditions under which a system could fail and what levels it can withstand. Sensors are used as part of the IoT platform and facilitate the exchange and analysis of information (Kumar & Dash, 2017). Based on the simulation and analysis, firms can improve their efficiency by reducing energy consumption and time, which in turn results in increased profitability.
Methodology: Risk Management
Further, IoT matches the methodology of risk management for companies operating within the transportation and logistics sector. For instance, the technology can identify the possible failures within a company’s system and relay real-time information that can help managers to take quick actions to avoid pitfalls. IoT can predict a possible mechanical failure of an automobile and alert the driver and further suggest the possible options that can be taken to avert the impending danger. Risk management includes the identification, analysis as well as response to the various risk factors that make up the life of a business. Since 1996, onboard diagnostic ports (OBDs) have been integrated into automobiles to help manufacturers and mechanics to establish information regarding the health of a car (Cosgrove, 2018). The ability of an IoT to forecast risky conditions means that the application of the innovation within the logistics and transportation industry fits into risk management within the body of the knowledge matrix.
Planning Level: Operational and Tactical
Two levels of planning are represented in this paper. They include operational and tactical ones. The former is focused on certain specific procedures and processes that happen within the lower levels of a business. However, managers need a high level of detail in outlining the routine tasks of the sectors that are involved in executing the operational plans of an organization. IoT can help to oversee the activities of a transportation and logistics company, including management of its fleet and issuing reports to the firm’s managers. In terms of tactical planning, IoT supports strategic plans by making them more explicit in a way that they are relevant to a given area of a company. Various companies can adopt IoT to suit their needs, for instance, maritime companies can tailor the system to match their operations. This could be different for a firm that also relies on IoT with all typical components of the technology but offers rail or road transportation to its clients.
References
Cosgrove, C. (2018). IoT applications in transportation. IoT for all. Web.
Dhumale, R. B., Thombare, N. D., & Bangare, P. M. (2017). Supply chain management using the internet of things. International Research Journal of Engineering and Technology, 4, 787–91. Web.
Kumar, N. M., & Dash, A. (Eds). (2017). Proceedings of the international conference on inventive computing and informatics. Researchgate. Web.