Big data is not the same as ‘lots of data’. The traditional technology has served the analytics needs of organizations for decades allowing big corporations to make decisions based on the warehousing and distribution of data in the systems. However, ‘Big Data’ is taking everything to a whole new level.

Big data is allowing companies to harness enormous data volumes in different formats such as photos, audio, audio, text, and video and from various media profiles. Big data systems can process information both in batch and in real time modes. Companies of today have been faced with an extremely significant volume of data, and big data is deciding on the problem they want to be solved.

Why big data is important for the shipping systems

Traditional data is mainly look-back data using the ordinary business elements such as the transit times and insurance cost. The data is primarily accounting data used to determine the profitability of the voyage.

However, non-traditional data is time-sensitive data such as traffic, delays, weather, port strikes and unexpected happenings. The data is mainly generated from RFID tags, sensors, traffic management systems, and GPS devices. With big data helping to forecast some of these issues, money is saved to increase profitability.

It is not all non-traditional data that is quantifiable, but it is for sure related to issues that can be avoided or resolved. Preventive technology such as big data is vital for businesses such as shipping and transportation.

The sort of information needed during shipment

Shipping involves a lot of things such as tracking the products and routing management to determine the best and most cost-effective route to use. Whether you are shipping the goods as the vendor or receiving them as the customer, there is a lot of information that has to be acquired to ensure the particular product reaches the final destination on time, the method is cost efficient, and the item is safe. The data acquired may have come from a carrier and sent through RFID. Such data can be used by the carrier to carry out improvement and to quantify the amount of items in shipment.

Think about tracking as used by most companies today to track goods from one company branch to another or from one subsidiary branch of the enterprise in a country shipped to another subsidiary office in another country. Such shipment is made through big shipping companies such as UPS and FedEx because they have advanced systems to track items. These companies have a barcode scanning systembecause the packages have barcode label fixed well recorded into the system.

To determine whether a particular package has been received, the barcode scanner is used to scan and verify delivery from one office to another. The package is then delivered to the recipient, and the signature is scanned and captured as a proof of delivery.

Warehouse management system

Big data has indeed been proven to be essential for supply chain management. Apart from verification of items during shipment, it is very essential for warehouse management. The most common are the Automated Data Collection (ADC) using radio-frequency (RF) and bar-code scanners as applied to portable terminals.
Through ADC, the warehouse manager understands the number of items or materials in the warehouse, making it easier to handle them and arrange for shipment or transportation. Think about the reliability of data. Instead of just disqualifying those who missed their delivery, evaluating the reliability of the system used to track and record warehouse items should be the first thing to do.

Big data helps to bring information together from the various relevant sources to help decision makers make real-time decisions that will keep logistics pipeline flowing. Big Data is the key to quantifying what the customer, and you have determined priorities for the business.

Big Data contributes to the achievement of the business objectives whether it is improving efficiency or reducing cost. Big data is vital to save time, deliver information in real-time and quantifying data to make it work for decision makers.



By: Dennis Hung