Big data in logistics and supply chain management

B2B companies require faster shipments for less cost and with more transparency. The customers continue to go digital, also demanding more speed and responsiveness. At the same time, online sales and high-tech sensors provide colossal amounts of data.

That’s why using Big Data in logistics is transforming from a “nice-to-have” into a “must-have” feature.

Data-driven decisions are the focus of attention for C-level executives in all industries. Big Data technologies allow them to make such decisions quicker. As a result, the implementation of Big Data in global logistics is booming. According to The Research and Markets, the supply chain big data analytics market was valued at $3.55B in 2020. By 2026 it is expected to become several times larger and reach $9.28B.

Collecting data is of prime importance for the logistics company. For instance, you need info about the vehicle’s condition, the road it travels, fuel consumption. Data about the number of drivers, their well-being, the time it takes them to leave the warehouse will also come in handy. All this information can help decide on the areas and means of optimization”, says Oleksii Glib, CEO at Acropolium.

This article dives deeper into the topic of how logistics & supply chain can benefit from Big Data.

There are several examples of this innovative technology revolutionizing logistics. The right logistics management software should help your company to handle Big Data correctly. You find out how to choose such software and why this task is so challenging.

How Is Logistics Using Big Data?

An enormous flow of goods around the globe generates vast data sets. Origin and destination, weight, content, size, and location are tracked for millions of shipments. On top of it, transportation companies get data about traffic, weather, vehicle diagnostics, driving patterns, location, etc. It lays a foundation for the application of Big Data in logistics.

On the other hand, punctuality and transparency are especially important in the transportation sector. Besides, the customers pressure providers to offer shorter lead times at lower costs. That’s why implementing Big Data in logistics to foresee and prevent bottlenecks in the supply chain is crucial.

Most transportation companies already employ a data-driven approach to decision-making. According to the 2021 Third-Party Logistics Study, the majority of shippers use some technology to plan supply (89%), demand (83%), sales and operations (78%), and capacity (61%).

Big Data is combined with IoT and AI to boost the efficiency of supply chain & logistics

The full potential of Big Data in the logistics industry is yet to be harnessed. Firstly, it can help to utilize maximum resources and improve transparency, thus enhancing operational efficiency. For instance, automated transportation management systems use intelligent software which controls the fleet, schedules shipments, and automates routine tasks.

Secondly, this innovation can assist businesses in improving customer experience by maintaining customers’ loyalty and retaining them. On top of it, implementing an effective data-driven business model results in increased revenue.

Fulfillment and supply chain as a whole is both extremely data-driven, but at the same time are far behind technologically compared to other industries. In order to adapt to incredibly dynamic supply chains, our customers are demanding cutting edge tech, and thus, we are demanding cutting edge tech to serve them properly,” says Frazer Kinsley, CEO of Hook Logistics.

How to Choose the Right Logistics Management Software?

Transportation companies get data from a wide variety of sources, from GPS trackers to advertising response stats. However, huge unstructured datasets can impede decision-making. Businesses need technology, structuring the information and converting it into actionable insights. Therefore, having the right logistics management software is very important.

A really powerful tool should handle all aspects of transport operations. That includes inventory tracking, supply chain mapping, route optimization, warehousing improvement, etc. The characteristics of the top-notch logistics management software include:

  • Real-time logistics tracking, which helps to establish transparency, improve accuracy, and exchange information
  • Multi-client architecture, which can be deployed quickly and easily
  • Invoicing functionality to apply and process partnership policies, manage invoices on time, etc.
  • Comprehensive reporting system with access to all necessary records

The ideal instrument embraces all the functions to make your logistics and supply chain management really “smart.” Alternatively, it should seamlessly integrate with other tools and solutions. Give preference to cloud-based software to ensure its scalability and adjustability.

Note that many businesses may partner with 3PLs, cooperating with cargo carriers. Therefore, several different companies are involved in the transportation pipeline. That’s why important all partners need to be able to exchange data with each other smoothly. It contributes to the seamless coordination of their actions.

At the same time, many logistics companies have a unique set of metrics important for them. Each of those businesses may accumulate data from a different set of sensors on their vehicles. Therefore, it’s almost impossible to find a one-size-fits-all off-the-shelf Big Data software for logistics. Acropolium offers custom software development services in many areas, including transportation. We can help you with a project requiring Big Data development for logistics. Read on to learn more about our expertise.

The Impact of Big Data in Logistics

Implementing this new technology in your business processes may be a costly, time-consuming, and complex process. However, the use of big data in logistics has significant advantages. In particular, it results in improved data accuracy, more precise forecasting, increased transparency, profound insights, and reduced costs. Let’s have a closer look at how Big Data impacts logistics.

Enhanced Transparency

Big Data analytics systems, together with GPS devices and other tracking tools, allow logistics companies to monitor the movement of goods in real-time. That information is combined with traffic data, fleet data, and on-road network data. As a result, the logistics managers can easily plan and schedule deliveries, considering predictions about weather conditions or accidents.

The result is not only increased efficiency of logistic operations but more real-time updates for the customers and partners. They can monitor the delivery status of parcels in real-time. Moreover, the customers get automated notifications if any delay is expected.

Reduced Cost

There are many ways in which the use of Big Data in logistics can help save money. These are the main areas of cost-reduction:

  • Route optimization. Big Data technology can help to find the best route for delivery. Analyzing data from sensors in vehicles as well as weather reports and traffic updates, advanced logistics software can help to select the optimal course of action. As a result, the companies can save a great deal of money, mostly due to reduced fuel consumption.

  • Predictive maintenance and driving optimization. Advanced analytics systems can dig into the driving habits such as speeding up, braking, driving time, etc. Some inefficient practices can be spotted and weeded out. On top of it, the data about fleet conditions allows companies to conduct maintenance in advance. The result is reduced fuel consumption and fewer delays due to vehicle breakdowns.

  • Smooth last-mile delivery. According to the study carried out by SOTI in partnership with Arlington Research, 59% of transport and logistics companies in the U.S. and 78% in Canada consider last-mile delivery the most inefficient link of the entire supply chain. The surveys suggest that it occupies a large share of the total delivery cost. 59% of transport and logistics companies in the U.S. and 78% in Canada consider last-mile delivery the most inefficient link of the entire supply chain. Big Data in logistics can help analyze the information about all stages of the delivery process, including the last mile. As a result, logistics companies detect specific patterns to optimize their delivery strategies.

  • The data can reveal behavioral patterns of drivers and delivery crews that have local knowledge about their route territory and know better than any algorithm or data source where to park, which shortcut to take, or which congestion hotspot to avoid. Extracting this knowledge without having to disrupt crew member workflows can achieve significant improvements in route planning and more effective delivery instructions”, claims Matthias Winkenbach, the Director of the MIT Megacity Logistics Lab.

  • Efficient warehousing. Big Data provides warehouse managers with detailed insights into the process of loading, carrying, and unloading goods. On top of it, they understand the change in customers’ behavior changes and expectations from supply chain managers and manufacturers. This information allows managers to improve routes and scheduling deliveries. Therefore, safety improves while petrol consumption decreases.

Improved Responsiveness and Customer Experience

Big data analytics in the supply chain & logistics has a profound impact on its performance. A responsive supply chain allows companies to meet consumer expectations delivering quality products on time. Big data analytics helps managers understand the market situation, predict its future state, segment customers, and find new sales opportunities. In the end, the logistic companies get more control over inventory and more satisfied customers.

How Does It Work: Big Data Use Cases in Logistics

To understand the potential of this new technology for the transportation industry, let’s look at three examples of application of Big Data in supply chain management & logistics.

Warehouse Automation by Amazon

Amazon warehouse automation - big data analytics use case for logistics and transportation

The advancements in robotics, Big Data, and the Internet of things make smart warehouses real. Amazon fulfillment centers provide vivid examples of logistics automation.

The company began using robotics in 2012 as it acquired a Boston-based Kiva systems company (renamed Amazon Robotics). In 2014 the company used around 15,000 mobile drive unit robots in its warehouses. By 2018 this figure grew to 100,000 units, and in 2021 it reached an astounding 350,000 units.

Big Data technologies are of top importance in operating such warehouses. The algorisms have to process huge amounts of data to choreograph hundreds of robots. They determine how many bots should be deployed, which routes they should use, how fast they should move, etc. Complex simulations are run to determine the optimal parameters.

Complex algorithms are required to keep Amazon's automated warehouses efficient

Robots operate at dozens of more than 175 fulfillment centers across the globe. However, their goal is not only to allow the world’s largest online marketplace to keep up with the torrent of orders. The company officials believe that new advanced robots and control systems will help achieve the goal of reducing incidents at all Amazon operations sites in the U.S. by 50% by 2025.

On-Road Integrated Optimization and Navigation technology (ORION) by UPS

ORION software - application of big data in supply chain management

UPS, one of the largest shipping couriers globally, began testing its ORION algorithm in 2003, but it was deployed only in 2012. In 2019, the company added UPSNav to its route guidance platform. UPSNav provides turn-by-turn directions to guide drivers to specific package pickup and drop-off locations near the recipients, even if they are not visible from the street. ORION implementation resulted in a route reduction of eight miles per driver.

The latest upgrade, which is being rolled out in 2021, is called "dynamic ORION.” Its distinctive feature is reoptimized routes, which are fine-tuned depending on changing conditions. The latter may include traffic, pickup commitments, or changes in delivery orders. The result is driver routes, which are shorter by an average of two to four miles per driver. Almost all UPS vans use the new system.

The company claims that ORION has saved around 100 million miles and 10 million gallons of fuel each year. The new version is expected to push those figures even higher.

DHL SmarTrucking

DHL trucks use IoT sensors - supply chain big data use cases

DHL, the German-based transportation giant, offers another of IoT, AI and Big Data in supply chain examples. In 2018 the company launched its innovative trucking solution — DHL SmarTrucking. A large portion of its fleet can transport perishable goods, requiring specific temperatures (from -25ºC to +25ºC).

The smart vans are filled with IoT-enabled sensors monitored through the control tower. As a result, both operations teams and customers can track the consignment and its temperature in real-time. Status updates are also sent through the customer portal and mobile applications. The accumulated data about the vehicle and its condition is used for route optimization and preventive maintenance.

According to DHL, these innovations resulted in reducing transit times by 30% in comparison to the conventional trucking industry. Moreover, DHL SmarTrucking claims to provide 95% on-time delivery. At present, the company operates in India, having 745 trucks and 12 SmartHubs at its disposal.

Why Should You Choose Acropolium as Your Partner for Implementing Big Data in Logistics Project?

Acropolium has the expertise and experience necessary to build complex Big Data solutions for supply chain. We’ve been working in this sphere for more than 10 years. During this time, our team delivered 84 solutions for 56 clients from different spheres, including logistics. For instance, we introduced systems, collecting data about a vehicle’s location, weight, fuel level, etc. We have adapted our cloud-based software to collect and process information from dozens of third-party gadgets available on the market.

To understand our expertise better, let’s have a look at one of the projects we’ve completed for our client.

Mobile App for the Shipping Service Provider

Our client, a US logistics company, required an efficient mobile app for truck drivers and brokers to track the number of working hours. Brokers refused to pay for the extra hours, and drivers were forced to work due to external circumstances, such as vehicle breakdowns, traffic jams. Brokers suspected that the drivers were exaggerating the time required for delivery. The software solution had to solve the issue.

The main goals were as follows:

  • Protect brokers from drivers overstating their amount of work
  • Provide drivers with solid proof of extra hours they are required to complete the delivery
  • Deliver the MVP in three months

Our team audited the existing web solution and Android mobile application. We found several critical issues resulting in scaling, maintenance, user experience, and security problems. Our specialists optimized the core architecture, detected and fixed existing bugs. The team developed an iOS application from scratch. We completed the whole project within a tight timeframe of three months.

As a result, both brokers and drivers got a user-friendly app with maps and real-time geolocation tracking.

Read also: Guide to logistics app development.

Results of application of big data in supply chain management

Make your Logistics Smarter with Big Data Technologies

The transportation industry faces new challenges as customers strive for even higher delivery speed and transparency. At the same time, the advancements in Artificial Intelligence, the Internet of Things, and Big Data allow companies to accumulate more information, generating valuable insights. Optimized routes, reduced fuel consumption, more efficient warehousing, a better understanding of consumer needs are just a few benefits of using Big Data in logistics.

However, implementing these new technologies in your business processes may be challenging. First and foremost, collection and processing enormous volumes of data is a complex task. Besides, developing and fine-tuning machine learning algorithms, which produce real business value, requires experienced and knowledgeable engineers. Off-the-shelf software isn’t tailored to your needs, so a custom solution is usually a preferable option. On top of it, you must protect your data from unauthorized access.

Acropolium has solid expertise in Big Data technologies to address those challenges. Besides, our company has been working with clients from the transportation industry for 8 years.

We can offer you tailor-made solutions for freight forwarding optimization, supply chain, warehouse management, document generation systems, etc. Acropolium has a strong background in auditing the existing solutions and consulting companies on upcoming projects. Let’s unleash the full potential of Big Data for logistics in your company together.