IT Technology Trends Driving Logistics in 2023
In this article, we discuss the most popular IT technology trends in logistics that will be on the rise in 2023
A blockchain is an encrypted distributed computer file system designed to protect from unauthorized access to records in real time. A blockchain ensures transparency of all logistics processes and allows you to use a smart contract to automate business processes.
One of the first startups to develop smart contract apps in the logistics industry was ShipChain, a cargo tracking company. ShipChain’s blockchain-based system allows them to track and trace a product from the moment it leaves the factory to final delivery at the customer’s doorstep.
All relevant information about the supply chain is recorded in a blockchain-based database that can execute smart contracts after conditions are met (for example, when a driver transmits a confirmation of successful delivery). Members of the ShipChain platform purchase a digital SHIP token to pay for freight and settle transactions.
Combined with IoT technologies, blockchains will enable smarter logistics contracts in the future. For example, upon delivery, a connected pallet can automatically convey delivery confirmation and the delivery time as well as the condition of the goods.
A blockchain-based system can then automatically check if goods have been delivered according to the agreed terms and paid, which greatly improves efficiency and integrity.
Last-mile delivery systems
Last-mile delivery means moving goods from a transport hub to their final destination. This is the part of logistics where ecommerce is most aggressive in connecting with customers through fast delivery. It’s also where order tracking technologies such as IoT, Bluetooth Low Energy (BLE), and iBeacon can help businesses stay ahead of shipments and improve the customer experience.
During the first stage of any delivery system, last-mile order details are entered into a centralized system. The system then notifies both the sender and the recipient of the order request. Next, a distribution center delivers the parcel to the transport unit through its fleet.
The last-mile approach starts with orders at transport hubs that are then assigned to delivery staff according to their routes. In this process of delivering a package to the final customer from the warehouse, there are many points of contact where advanced logistics software can reduce operational boundaries.
For example, you can use artificial intelligence-powered sorting algorithms to sort products according to optimal routes. Courier delivery software solutions can easily integrate AI algorithms with cloud computing and the cognitive capabilities of API technology. It can even help you train your delivery staff and suggest the fastest route for more efficient delivery.
As you can see, cloud computing plays a vital role in courier delivery software, namely in sorting operations. Let’s find out how critical cloud computing will be for the logistics industry.
Cloud computing refers to a virtualized pool of computing resources that provide storage, retrieval, networking, software, analytics, and intelligent data over the internet (“the cloud”). Cloud computing software for logistics can increase the efficiency of operations such as fleet management, order management, and delivery.
The logistics industry is using the SaaS (software as a service) model to improve its operations. Cloud-based SaaS logistics services help to consolidate resources or data from customers, retailers, and wholesalers. Then you can use forecasting algorithms to understand the gap between supply and demand.
Fleet management is another great application of cloud computing. Say your fleet is carrying cargo across the Pacific Ocean and there’s a weather-related threat. In this case, fleet managers can track the movement of the fleet using cloud-based logistics software and redirect the fleet to a safe route, avoiding catastrophic damage.
There are many activities related to fleet management such as courier tracking, documentation, and fleet monitoring that can be performed using cloud software. This software is aided by intelligent IoT technologies for analytics and fleet tracking. Let’s see how this is changing the logistics industry.
Robotics is not a new thing, but it will become a dominant technology in the development of logistics. With the advent of mechanical engineering and the cognitive approach of machine learning algorithms, modern robots have become smarter. By 2025, the global robotics market is expected to reach $210 billion, growing at a CAGR of 26%. The robotics market is dominated by industrial and logistics applications.
You can see how Ocado is using robotics to automate product packaging. Robots communicate using 4G technology to avoid disruptions in the air traffic control-type system. Each robot follows the mesh and delivers products to the packaging terminal, where a human or other robot scans them to complete the packaging.
Robots are quite popular in the logistics industry and are a phenomenal fit for automating operations such as exporting, distribution, and delivery. According to a survey, 32% of companies are investing in technology such as robotics and automation, 40% want more robotization, and 55% want enterprise resource planning software.
Using a complex robotic system requires reliable logistics management software to ensure the efficient delivery of goods. You can also apply robotics to fleet management, especially when loading hazardous chemicals.
Artificial and augmented intelligence
Over the past few years, the logistics industry has begun to integrate AI-based solutions including intelligent transportation, route planning, and demand planning into its operations. But this is just the beginning.
AI already plays an important role in logistics, from robots for last-mile delivery and sustainability solutions to automated warehouse picking systems and predictive optimization software. Shippers, carriers, suppliers, and consumers can expect to continue benefiting from these logistics technology trends.
The use of augmented intelligence is expected to grow along with the use of artificial intelligence. Advanced intelligence combines human intelligence with automated artificial intelligence processes. In logistics planning, the use of augmented intelligence may even surpass the use of AI alone, as it can combine the contributions of planners (experience, responsibility, customer service, flexibility, common sense, etc.) with AI technology.
According to Gartner, advanced intelligence will generate $2.9 trillion in revenue and lead to an increase in employee productivity of 6.2 billion hours globally by 2021. Logistics companies can be expected to implement more advanced smart solutions that ultimately enable logistics professionals to do their jobs faster, reducing errors and costs.
Big data & data analytics
Data analytics provides actionable insights to improve warehouse productivity and make optimal use of logistics resources. Location and weather monitoring data as well as fleet planning help optimize routes and delivery planning.
Market data analysis supports further optimization of supplier prices, inventory levels, and risk management reporting. Advanced analytics can identify anomalies and provide predictive maintenance solutions.
The US-based Nautilus Labs offers artificial intelligence solutions that help marine companies reduce fuel consumption and improve their operational efficiency. Nautilus software analyzes historical fleet data and predicts the optimal speed and fuel consumption. The cloud platform also generates data on vessel performance, which subsequently helps to optimize fuel costs.
The American startup FACTIC offers a SaaS platform that provides predictive analytics solutions for the food and beverage industry. FACTIC uses data mining and artificial intelligence techniques to analyze data from internal and external sources to predict sales.
The platform predicts fluctuations in demand and makes data-driven decisions to automate procurement. It also provides tools to optimize inventory through automatic replenishment.
Autonomous technologies increase the safety of vehicles and securely deliver goods while eliminating human driving errors. They also improve the efficiency of first and last-mile deliveries, as they’re designed to work 24/7. In addition, autonomous vehicles improve fuel efficiency through long-haul platoons, reduce traffic congestion, and optimize travel routes through the use of advanced artificial intelligence technologies.
The German startup Spring offers Spring X1, a fleet of autonomous trucks with predictable intelligent systems. Spring-loaded autonomous vehicles are equipped with modular trailers designed for various applications. These trailers can be customized based on their application as mobile lockers or for food or cargo delivery.
South Korean startup Mars Auto is developing artificial intelligence software for self-driving vehicles to transport goods without a driver. The software offers tools to map the surroundings, control vehicles, and guide them to the desired cargo bay. It helps shipping companies deliver cargo in an efficient, reliable, and safe manner without driver intervention.
5G can push the logistics industry towards a full digitalization, providing continuous coverage for monitoring, tracking, and detecting theft. A report from STL Partners says 5G adoption in the transportation and logistics industry could add $280 billion in gross value to the global economy by 2030.
Implementing 5G is challenging and will depend on factors such as investment in 5G infrastructure and a different approach to roaming rules and licensing conditions to help operators collectively achieve 100% coverage.
Digital twins are arguably one of the most exciting logistics technology trends to watch out for in 2021. Logistics professionals know that products will never be the same as their computer models.
Current simulations don’t take into account how parts are worn and replaced, how fatigue occurs in structures, or how owners make changes to meet their changing needs.
However, digital twins technology changes this once and for all: now, the physical and digital worlds can be combined into one, allowing us for the first time to interact in the same way with a digital model as we do with a physical object or its part.
The possibilities of using digital twins in logistics are enormous.
In the shipping sector, digital twins can be used to collect product and packaging data and use this information to identify potential weaknesses and recurring trends to improve future operations
Warehouses and businesses can also use this technology to create accurate 3D models of their components and experiment with layout changes or new equipment to see the effects without risk. In addition, logistics centers can create digital twins and use them to test scenarios and improve efficiency.
In addition to this, delivery networks can use digital twins technology to provide real-time information that will improve delivery times and further aid autonomous vehicles on their routes. It will be interesting to see what other use cases for efficient logistics emerge next year.
Internet of things
The last but definitely not the least important trend is the Internet of Things. We saved it for last because there’s a lot we should cover. IoT is one of the fastest-growing trends in logistics, and it seems like it can do everything.
If you’re working with multiple suppliers to obtain a single component for your device — say, a sheet metal supplier network for an automobile manufacturer — you can use a real-time locating system (RTLS) to track the pallets of that component from each supplier from the time they’re packed. This way, you can know ahead of time if a shipment is delayed, allowing you to keep your production running smoothly with plan B.
Truck drivers have little or no incentive to ensure your goods arrive exactly where you instructed, often resulting in lost or incorrect deliveries. If you use RTLS, you’ll know exactly where the pallets have been placed.
Materials moved in the factory for assembly or shipment are often prey to what we call the “flat surface problem.” The wrong materials can lead to shortened cycle times, employee frustration, and ultimately customer dissatisfaction. With RTLS, you’ll always know the location of tagged materials, such as special test fixtures.
You can control sensitive goods to avoid damage or loss. Some factories regularly receive batches of perishable or sensitive goods that only stay fresh for a short time and/or require certain environmental conditions to maintain quality.
With an IoT logistics app, you can tag a crate of eggs or a barrel of milk and monitor the humidity in the storage area, the product temperature, and the level of shock and vibration these items are subjected to during transport.
You can use this information to notify truck drivers of damaged shipments long before they arrive at your facility and have a new shipment en route.
In addition to choosing the right IoT platform in your warehouse, you also need to explore the analytics capabilities of IoT systems.
IoT analytics means applying data analysis tools and techniques to analyze and make sense of large amounts of collected data (remember that sensor devices collect data on statuses, events, etc. in real time). This is the power of IoT in warehouses and distribution centers.
Data analytics is critical to the IoT ecosystem. It not only helps you analyze the large amounts of data generated by your IoT ecosystem but structures this data to help you make sense of it.
Remember that every component in the ecosystem will generate large amounts of data, so for an organization purposes, it’s essential to make that data meaningful and useful. Without proper data organization, warehouse managers and other decision-makers cannot understand data and take action to improve warehouse efficiency.
IoT data analytics can help you improve efficiency and profitability by deeply understanding operational inefficiencies and enable you to implement effective solutions that deliver measurable operational efficiency.
With an IoT-based system, supply chain companies can track the locations of their vehicles, as well as the personnel assigned to them, at any given time. This provides a transparent view of how resources are used and provides insights into further resource allocation improvements. The Internet of Things can also help companies automate car maintenance and repairs.
Compliance and safety are important aspects of supply chain management, and automating this process can help companies avoid problems.
With a more accurate vehicle, traffic information, and better strategies you can improve fleet and fuel management.
Meeting demand is one of the most important indicators of the efficiency of the supply chain sector. Applications of IoT technologies in the industry are not limited to technical aspects. IoT technologies can also provide insights that improve the ability to forecast demand.
Data collected by Internet of Things devices can help you better understand customer behavior and product usage, needs, and demand.
IoT devices can provide more than just point of sale data. They can provide data to track the actions that lead the consumer to that point.
The Internet of Things makes it easier for manufacturers and suppliers to understand the consumer’s point of view, from the moment of purchase to why consumers make a purchase and how they use the product.
IoT inventory tracking
Inventory management is the most widely used application of IoT for transportation and logistics, allowing you to remotely track inventory assets, monitor their condition, and thereby create a smart warehouse. In addition, fuel level sensors built into vehicles can help to avoid underloading and overloading during transport.
As customer expectations continue to rise and interest shifts towards a variety of products and personalized services, the logistics and supply chain sectors face increasing pressure. The rapid development of new technologies such as the Internet of Things, advanced mobile robots, artificial intelligence, and blockchain-based solutions presents companies with a dilemma when choosing the most suitable technologies in which to invest. As technological advances continue, it’s important for emerging companies to be proactive and identify potentially disruptive changes early on.