Container Shipping Industry: A Digital Revolution
Every day, the shipping lines move mountains of goods around the world, satisfying an expansive worldwide demand. There are terminals that operate on the boxes, complex logistic processes and IT system coordinating the complex flow of transport from producer to consumer, making sure products show up in the right place, at the right time. The industry has a database of the vessels on a daily basis and a wide variety of cargo and containers. These provide factual data to measure the study variables comprising seaborne trade, freight rate, fleet size, and vessel positions. Most of the shipping lines have few analytical resources, either in the corporate center or the business units. Decisions made are only with a minimum of information, which is often borrowed from external providers that also supply their competitors (source: The hidden opportunity in container-shipping, November 2014, Mc Kinsey publications). The challenges seen of today are inaccurate positional data, usage of outdated charts that leads to serious accidents. Even the best pictorial representation of the ship’s position in a three-dimensional display is of no use, if the data source is not reliable enough. In the digital world, where everything is managed and connected via the Internet and enabling every action to leave an online trail, a humongous pile of data is processed every day that could be used to make critical business decisions. Several approaches can be made to tackle the problem of integrity in terms of accuracy and currency, like crosschecking and unifying data from different sensors. Thereby, providing accurate and reliable data for integration into online navigation systems. Watching over from space According to International Chamber of Shipping, shipping lines today transports about 90 percent of total world trade by volume (Source: Maritime transport: Shipping undergoes sea change, May 2012, Geospatial World). After analyzing the World bank database about Container Port Traffic, it can be said that there is a growing need for constant developments in the field of surveillance, with huge increase in ship traffic in the oceans, with four times as many ships at sea now than in 1992. The average number of ships have jumped more than 300 percent in the Arabian Sea and the Bay of Bengal, according to the study, published on 20th October, 2015 in the journal Geophysical Research Letters, Anthropogenic pressure on the open ocean: The growth of ship traffic revealed by altimeter data analysis, Volume 41,Issue 22. The IT teams across the Container Shipping Industries are intensifying the use of real-time data to make crucial business decisions. Thereby helping in monitoring the speed, fuel efficiency and also weather conditions. It is actions from the Global Voyage Centre, which helps impacting on the bottom line. Thus, cutting bunker bills and minimizing operational expenses could be just the tip of the iceberg in terms of data streams coming from a vessel, used to improve performances, this can be studied from the case study CargoSmart Uses Big Data to Transform Shipping by TIBCO, dated 25th February, 2015. Data, Data everywhere The ability of the shipping industry to gather and scan data today could make way for a totally new Navigation, Route Monitoring and Traffic management system. When you have real-time facts and figures flowing in, they position the company to make better decisions to bring in improved safety and security through better exchange of data between ships and the shore. The integration of existing and new navigational tools into a global system will result in increased navigational safety by monitoring vessel speed, accessing location, total transit times, routes, based on the data obtained. The system then sends alerts to Global Voyage Center. Reports on reliability of services can be measured using expected departure and arrival times, actual departure and arrival times, and transit times. Such ideas would be the beginning of how data analytics use will transform the way the Shipping Container Industry does business in the future. There is a large wealth of information, which needs to be extracted, analyzed and understood. The journey has to be made from analyzing past data after the expedition has taken place, to daily data, and then towards ‘instantaneous data’, thus receiving invaluable real-time data intelligence. The analytics team can help in with issues like vessel deployment, utilization, terminal operations, speed profiles of vessels and forecasts. The digital revolution in shipping industry will continue, which may expand to include individuals working in the logistics service industry enhancing decision-making with analytics. Currently, the data used is only a fraction of data, which is available. The industry has just begun to discover what data analytics can do. The question to be asked is, in the coming years how would we experiment with it, find the possibilities, demonstrate the value and use our knowledge and wisdom to share that expedition.
Every day, the shipping lines move mountains of goods around the world, satisfying an expansive worldwide demand. There are terminals that operate on the boxes, complex logistic processes and IT system coordinating the complex flow of transport from producer to consumer, making sure products show up in the right place, at the right time. The […]
Every day, the shipping lines move mountains of goods around the world, satisfying an expansive worldwide demand. There are terminals that operate on the
["Analytics Case Study", "supply chain analytics"]
["big data", "Go", "programming_languages:R", "AI", "programming_languages:Go", "Git", "RAG", "Seaborn", "analytics", "Analytics Case Study", "supply chain analytics", "R"]
["AI", "analytics", "Seaborn", "RAG", "R", "Go", "Git", "big data", "programming_languages:R", "programming_languages:Go"]
I am currently pursuing my MBA in Business Analytics from College of Management and Economic Studies, UPES, Dehradun. I have an experience of 22 months with leading Transportation and Logistics team in delivering Business Intelligence Projects and also closely worked with Project Managers, Clients, Subject-Matter Experts, and Data Modelers to obtain requirements, objectives, and business rules for projects. I take an active interest in Mentoring ,Social Responsibility Programs along with everything related to Data from Acquisition, Integration to Interpretation.