With the recent advancement in information technology, the internet of things, and the recent increase in global data sources, data is getting generated every day and its impact on several industries cannot be overlooked.
This massive generation of data with the new opportunities it provides for discovering new values, and the challenges it raises in terms of management and analysis, has given rise to a new concept, commonly referred to as Big Data.
However, in today’s interconnected and instrumented world, every industry including the transportation segment uses an extraordinary amount of data. In fact, Transport and Logistics sectors are actually among the most ideally placed to benefit from the methodological advancements and analytical capabilities of Big Data technologies.
To get the best data analysis, companies including the logistics and transportation industry need to use dedicated tools called big data analytics. These tools allow managing and analyzing the huge data coming from roads and vehicles sensors, GPS devices, customer‘s applications, and websites, etc.
In fact, it’s not limited to only logistics and transportations sectors; other branches of transportation sectors which includes, airlines, airports, freight, hospitality, railways, can benefit from the impact of big data analytics which will help in decision making, operational management, brand management, and customer relationship services.
Below, therefore, are the impacts of big data analytics on transport and logistics.
1. Big data in the transportation industries reduces errors in delivery and pickups
We’ll all agree that Courier service companies are normally large operational organizations that deal with large amounts of cargo, hub terminals, general information systems, and a wide range of transportation vehicles and consist of a complicated network of labor and equipment.
This means there are large transactions to be carried out from deliveries to product pickup. However, errors in deliveries or pickups and shipping processes can result in additional expenses for the company. While these expenses can look like something small or minimal, imagine the amount of loss if a single error occurs once a day. This could cost more than it should and customers may even request replacements or refunds, and the public image of the company may be tarnished.
However, with big data in place, errors in deliveries and pickups can be reduced. Logistics companies have embedded sensors in all of their delivery vehicles, with GPS-enabled smartphones covering any gaps.
A third party validates these sensors for accuracy, and then the reliability and timeliness data from these sensors is used when logistics companies are bidding for new contracts. Instead of having errors that could attract loss to the company, big data can help the company to bring in more profits.
2. Big data will improve operational efficiency
Improving operational efficiency is one of the first and most important values that can be driven by adopting Big Data in transport and logistics. Usually, automated data processing provides better decision-making capabilities, improves process quality and performance, and optimizes resource consumption. In fact, the benefit can extend through the following ways.
-
Better visibility for future orders and demand forecasts
-
Ability to monitor and predict low in-stock items in advance
-
Signiï¬cantly reduce the impact of late and incomplete shipments
-
Evaluate the combined risk of combined situations that may arise
-
Forecast the optimal inventory needed for promotions and what the best times are to ship the inventory
-
Provide retailers with the ability to suggest pricing and allocation strategies where no historical data are available
In fact, with big data, it is possible to provide real-time visibility across the supply chain and in addition to improve forecasting, demand planning, sourcing, transportation, and distribution processes. Companies will be able to model supply chain data with higher precision, alter decisions in real-time, and utilize predictive and prescriptive analytics to solve problems before they occur.
3. Big data provides better shipping options with a higher quality of goods
When it comes to shipping sensitive goods, selecting the appropriate route must be the top priority to avoid late delivery and to make sure that the goods still maintain good quality when it gets to the customer.
To achieve this, shippers must tap into the advantage of big data to review different models, ranging from rail to truck, and they must go further by finding the most economical way to get the right product to the consumer at the right time, at the appropriate rate.
In fact, big data with the use of the Internet of Things could give delivery drivers and managers a much better idea of how they can prevent costs due to perished goods. For example, a truck is transporting a shipment of fruits and vegetables. You could install a temperature sensor inside the truck to monitor the state of the goods inside, and give this data along with traffic and road work data to a central routing computer.
The computer could then alert the driver if the originally chosen route would result in the damage of the fruit and the vegetable, and suggest alternate routes instead.
4. Strategic network planning
Why are logistics and auto transport companies so interested in big data optimization? For two reasons: it helps them save money and avoid late shipments. When you’re managing a delivery system or supply chain, you have to understand the line between overcommitting resources and vehicles and under-committing them.
Using a combination of real-time information, historical trends, and clever algorithms, big data is translating car speeds, weather conditions, community events, and sources of acceleration and deceleration for road operators. In Fact, a lot of cheap car shipping companies have been able to use sensors built on transport networks and fleet vehicles to collect data streams from local transport authorities for cheap and easy delivery.
Conclusion
In conclusion, big data can be used to reduce errors and unnecessary spending. It can be used to find the problems associated with delays and downtimes for transport upkeep.
Every organization needs to understand forces in their marketplace better and respond faster to changes in their environment in order to remain competitive. The proper use of any tools and methodology will help to remain at the top.
