Big Data can have a profound impact on the way ship operators and owners monitor the safety, sustainability and performance of their vessels. At the moment however, obtaining and extracting the maximum potential from this vast amount of data can be difficult for individual ship operators. Comprehensive access to Big Data sources and a range of expertise enables DNV GL to collect, analyse and interpret Big Data and unlock its potential for customers.
DNV GL’s new AIS Business Intelligence Service uses Big Data to gain valuable insight into a range of different areas. Maritime Experts from the Advisory Division at DNV GL feed case-relevant data into advanced models and analytics schemes, in order to analyse information about voyage management, port and bunker operations as well as benchmarking data from other market players. This enables DNV GL to tailor the analysis to each customer’s needs – providing advice on reducing operational costs, voyage management optimisation and the best retrofit solutions.
These insights can be valuable to companies throughout the maritime value chain – including ship operators and owners, port operators and authorities, insurance companies as well as commodity traders and maritime service providers. AIS Business Intelligence has a wide range of applications, from helping to determine the cause of vessel delays, advising on a switch to ports with shorter anchorage times or finding the right dry dock.
The maritime industry could be making much more extensive use of data from a wide range of sources, including information collected on board ships, data from the Automatic Identification System (AIS) as well as environmental, geographical, technical and commercial information. In reality however, Big Data is still proving to be a phenomenon that individual operators find difficult to use to their advantage. Information sources often have to be purchased and are challenging to interpret.
DNV GL is working to implement Big Data approaches throughout its advisory services. Maritime experts interlink previously unrelated data, such as information about ship positions with OPEX models or geographical port information and ship schedules – focusing the information to create a holistic view of a vessel’s performance.