12 September 2023
How to use Big Data in logistics? Application and benefits
Like other technologies, such as cloud computing and Internet of Things (IoT), Big Data is also used in logistics. When applied to routing, for example, companies have access to data about the location of modals, the type of cargo transported, the responsible employees and even the vehicle used.
With Big Data, cargo transportation can be monitored in real time throughout the entire journey: from the factory to the customer’s home. And this is only one of the applications of technology in logistics.
According to data from the 21st Annual Third Party Logistics Study, 98% of respondents said the data-driven decision-making is essential for the future success of supply chain activities and processes.
In addition, 70% of respondents stated that “improving logistics optimization” is the main objective of using Big Data in the sector. Certainly, this trend is here to stay. In this article, we present the concept of Big Data and the main applications of this technology in supply chain processes.
Do you want to know more? Keep reading the article!
What’s Big Data?
The increasing volume and detail of information generated by organizations, social media and Internet of Things (IoT) has exponentially the amount of data captured. This explosion of information has required extensive data processing capacity. In this context, the concept of Big Data arises.
In practice, the technology is capable of capturing, storing, managing and analyzing large sets of data, surpassing the capacity of typical database software tools. Big Data has four main attributes:
- Volume: the scale of data;
- Speed: agility in processing time and data analysis of transmitted data;
- Variety: it has different forms of data. They’re structured and unstructured;
- Veracity: consists of confirming the quality or reliability of data.
Big Data has changed the traditional view of how information is generated and processed, enabling innovation from advanced predictive analytics.
In logistics, much of the data collected presents information that makes business management easier. It’s possible, for example, to have precise control of the volume of products in stock; measure the value of losses in storage, transportation and handling of merchandise and manage, in real time, the movement of the fleet.
4 applications of Big Data in logistics
In logistics, the use of data processing and analysis has become noteworthy, mainly, for providing agility in operations and greater control of processes. See below 4 applications of Big Data in the supply chain!
Last mile delivery acceleration
This step is strategic for companies and, unfortunately, registers many logistical faults and losses. Last mile delivery can represent up to 28% of the total cost of delivering a package.
With IoT, sensors, real-time data and Big Data in logistics, companies now have access to important data: cargo location, traffic and risk areas are some of them.
Thus, it’s possible to accelerate last mile delivery, monitoring the entire delivery process from beginning to end, and offering a more positive customer experience.
Optimized routes
With sensors in delivery trucks, weather data, road maintenance data and fleet maintenance schedules, logistics can use this and other information to define more efficient routes.
So, routing becomes more assertive with the application of Big Data in logistics, impacting cost reduction and the quality of the delivery service.
Reliability will be more transparent
As sensors become more predominant in transportation vehicles, orders and throughout the supply chain, they can provide valuable data. Thus, logistical management gains more transparency.
In practice, shippers, carriers and customers will benefit. For example, if a shipment is late, carriers can identify the delay and avoid bottlenecks in the supply chain. In addition, they can use this data to negotiate with partners, showing how often delivery is made on time.
Data also allows continuous improvement! It’s possible to quickly identify gaps and bottlenecks in the operation, correcting them as soon as possible.
Automation of warehouses and supply chain
Soon, Big Data combined with automation technology and Internet of Things can make logistics a totally automated operation.
That’s because Big Data allows automated systems to work through intelligent routing of many different data sets and flows. For example, Amazon already has automation present in their distribution centers since 2012. In California alone, the company has about 3 thousand mobile robots in operation. With their support, employees save an average of 40 minutes per order.
In addition, the company has automated drones. They deliver products to customers that live within 30 minutes of an Amazon hub.
Big Data: main benefits of this technology for logistics
As we’ve seen so far, Big Data is revolutionizing logistics. But, after all, what are the benefits of using this disruptive technology? See below 6 advantages of incorporating Big Data in logistics:
- Collection and analysis of valuable data about suppliers, customers and products;
- Execution of the supply chain in real time, enabling the monitoring of each order;
- End-to-end visibility of the logistics operation, facilitating decision-making;
- Inventory planning and development. After all, Big Data allows users to plan, foresee and really optimize their inventory so they don’t waste space or money on items not demanded;
- Agility in solving complex distribution network problems, modeling results in more detailed scenarios than ever before. Possibility of maintaining a smarter and more efficient inventory;
- Improvement of customer experience, based on, for example, the analysis of customer feedback regarding delivery and returns.
Logistics management is really challenging. But, thanks to technology, opportunities to innovate are plenty. Keep reading ASIA SHIPPING’s blog and find out how new tools can boost logistical results!
