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Explaining The Big Data Revolution in Shipping and Maritime Industry

by blindertech

For the shippers and receivers, now you have the data and tracker related to your consignment at your fingertips at any point. Even when you are not using it, this can build confidence and peace of mind with your shipments. For the retailers who sell through marketplaces, each of their mouse clicks or user emails and every item added to shopping carts can help them sell more and also ensure improved customer service.

For those in the maritime shipping sector, do you use the relevant maritime data for analytics and better plan your best routes and optimized cost of operations? If you are already using this information to cut down the business costs and increase sales, it will be giving you great results and savings. For those who are not, it is time to join the big data club.

It is an amusing fact that about 99% of the entire data collected in the shipping sector is not analyzed or used for benefits. This may be a bit overwhelming, but effective usage of shipping data and analytics can surely improve the financials and save a lot of time for businesses of all kinds. This will also help to audit the invoices and also to optimize the contract terms.

Why is big data needed?

Big data is capable of handling data in both structured and unstructured forms. Usually, this gigantic volume of data is stored in the cloud. Data can be divided into traditional as well as nontraditional data for the purpose of classification. Those enthusiastic about data science may collect the traditional data set, also known as look-back or historical data. For the e-com stores, the supply chain data may be the source of data like order management records, payroll, warehouses, inventory systems, carrier data, etc. For maritime industries, traditional data may be sourced from ships, dockyards, warehouses, vessels, etc. This traditional data can be effectively used to analyze financial info like profit and loss, gross revenue, etc.

Nontraditional Data

On the other hand, nontraditional data is another set of time-sensitive data that is not quantifiable. This information comes through various sources in both structured and unstructured formats like images, video, audio, and inputs for IoT sensors, etc. Some real-time examples of these nontraditional data include traffic, location, weather, freight movement data in the transportation sector, etc.

The nontraditional data will be helpful in predicting changes and forecasting etc. With this, the decision-makers can foresee things and make changes before any issues happen. Some examples of nontraditional sources of data are IoT systems data, which comes from any random node in the supply chain. So, it is an important way to gather the analytical data for shipping. Nearly about 20% of shippers use IoT-based mechanisms. A study had shown that about 60% of respondents are still not using any logistic-based technology for analytical purposes. For them, it is not too late to adopt it, and this can be set as an ideal company goal for the year 2021 and beyond. For remote database administration services, RemoteDBA.com can be a trustable partner.

Adopting big data technologies will help to look into patterns from data, which will help derive actionable insights. In big data streams, data will flow inconsistently. Add-on technologies like machine learning and AI will help find patterns from the data, which will reveal the market trends to make predictions and help enhance operational efficiency. Your company may already be using the data for analytical purposes and business intelligence. Using big data in shipping will help logistic businesses to gain really valuable insights for timely decision-making.

Different ways of using big data in shipping

Big data will help enable the e-com companies and also make shipping more effective. The maritime industry will help improve the overall performance by optimizing the routes, making better decisions, predicting problems, and addressing them in a timely manner, etc. Big data analytics will also help to optimize the marketing and pricing approaches and prevent any scope of fraudulence. Further, we will discuss some big ways to use big data to gain a competitive advantage in shipping.

Fraud detection

Retailers in the e-com sector can set up fraud alerts if they detect multiple payment methods from the given IP address. As a real-time example of such fraudulence, we can see that a sequence of maritime bookings is different from the usual pattern.

Predictive analysis

Small e-com companies can make use of predictive analytics and data analytics for better results. With this, customer data and buying journey can be tracked, and this info can be effectively used to understand their interests and likes. This can be used to plan personalized ads and customer offers. The sellers may anticipate what eh customer demand is and supply the same in front of them.

Targets ads and marketing

Big data provides many innovative marketing approaches too, which the retailers can leverage to ensure a personalized experience to the users. The sellers can segment the consumers to send more customized and personalized recommendations and offers. This may also include personal particulars like size preference and style etc. It is proven that personalization can positively influence customer buying decisions. A sturdy related to customer retention shows that about 86% of the customers said that personalization is very important in making purchasing decisions.

All these points to the fact that retailers and maritime shippers must effectively use big data analysis to enhance their performance standards and optimize customer satisfaction and revenues.

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