Logistics management is going through a significant digital transformation toward Internet of Things (IoT) technology. The arrival of 5G plays a role in this transformation, along with Artificial Intelligence (AI), blockchain and other innovations. The result is more efficient operations, faster delivery and more satisfied customers. Here’s a look at how this revolution is impacting logistics management.
Like utilities and other early smart technology adopters, transportation companies have helped pave the way toward a more sustainable future thanks to omnipresent smart sensors. One of the ways this technology is improving the industry is with a driver app solution for delivery service couriers. This app connects the driver and communicates with recipients through the cloud to track the shipping process.
One of the most talked about innovation trends for logistics management in recent years is the adoption of artificial and augmented intelligence. This technology can bring quick insights to drivers and transportation company leaders about historical data and recommendations for solutions. Routing and scheduling, for example, can be optimized with machine learning software that monitors real-time weather and road conditions.
Improving logistics management can be achieved with the strategic placement of IoT sensors equipped with RF transmitters. The sensors are placed in vehicles, transit hubs and other locations that monitor traffic and the process of delivering goods from point A to point B. An emerging technology called telematics is used by insurance companies in which sensors installed in vehicles collect data on driver behavior, which is important to monitor for safety and liability reasons.
Real-Time Supply Chain Visibility
Part of this transformation involves adopting an always-on cloud environment in which big data collection on production processes is endless. Tracking the delivery process in real time throughout an entire shipping cycle helps all members of the supply chain. It keeps them updated on where cargo is located at any given time. IoT data can further measure the speed of the delivery and predict destination times.
Access to real-time supply chain data helps wholesalers and retailers plan their inventories. Stores can now find out instantly when a customer wants to make a purchase if the item is available or must be shipped. Analysts can use the data to evaluate supply chain members for reliability and sustainability. The more suppliers learn about each other via data gathering, the better they can assess and build a strong supply chain network.
One of the biggest problems in shipping is the $50 billion in losses each year due to a variety of reasons such as theft, damage or mix-ups. Blockchain technology is a solution for transportation companies to facilitate efficient and accurate shipment tracking and secure online transactions. Blockchain is a decentralized public ledger system that keeps data locked in encrypted blocks that are too complex for cybercriminals to crack. The ledger is useful to verify and update public records while keeping data private from unauthorized parties.
The use of blockchain can eliminate unnecessary middlemen as a cost-cutting strategy. Other benefits include more accurate freight and fleet tracking, easier driver onboarding and use of smart contracts that make transactions more seamless. These benefits are now understood by leaders in the logistics industry. Blockchain logistics apps currently available for transportation companies include Chronicled, ShipChain and Modum. These apps help make the shipping process more efficient.
Data Standardization and Advanced Analytics
One of the major challenges shippers face is the lack of logistics data standards, which makes it difficult to charge data when different suppliers use different formats for collecting and storing data. Adopting IoT standards in the logistics industry would create a more seamless digital environment. The digital transformation of delivery services to track movement and condition of containers in real time will be maximized if logistics firms come together to support industry standards.
Demand for advanced analytics continues to grow, as deeper data and sophisticated analysis can provide a competitive edge. Advanced analytics goes beyond typical business metrics to uncover overlooked insights, make projections and suggest solutions based on historical data. Machine learning, pattern matching and cluster analysis contribute to advanced analytics. This data is useful for developing visual presentations of graphs that make learning easier.
Increasing Investment into Logistics
As interest grows among investors for greater sustainability practices in logistics, startups from VCs and enterprises should consider investing in IoT technology. Big data is the key to streamlining any business operation, which is why a new wave of efficiency-minded investors has emerged to support sustainable companies. The market for global IoT in logistics reached $34.5 billion in 2019 and is projected to surpass $100 billion by 2030, according to Research and Markets.
Key components for companies looking to improve efficiency in logistics include the cloud, IoT sensors, AI software and mobile apps. Voice-activated virtual assistants can answer questions on the fly to help drivers understand their assignments better. Another way investing in IoT technology pays off is it delivers alerts when it detects something that requires immediate attention, like repairing a certain vehicle component. The most sophisticated IoT software for automotive applications has self-correcting automation features.
Utilizing real-time data to make adjustments to schedules or other operational issues can help a large company save millions of dollars per year. The data helps decision makers identify wasteful elements of its operations and then make improvements. By investing in the right hardware and software, a company can achieve higher output at less cost while reducing waste.
By investing in telematics a transportation firm can monitor driver behavior, which will lead to more stringent hiring and safer deliveries. This technology pays for itself in the sense it helps prevent accidents and provides data that can be used to promote the firm’s commitment to driver safety. The technology tracks various aspects of the vehicle’s mechanical activity and physical conditions. Speed, idle time, location and fuel consumption are just some of the metrics that can be monitored with telematics. Evidence of safer driving behavior can help cut costs on insurance.
Sustainability Powered by Technology
The technology necessary to reach sustainability in the logistics industry can be divided into four main groups: communications systems, vehicle tracking, supply chain monitoring systems and IT security.
Autonomous vehicles (AVs) are also playing a major role in this transformation toward greater mobile connectivity. Auto manufacturers have used automated robots since the sixties that have mainly been stationary to perform repetitious high-speed tasks. Modern warehouse robotics technology has gone a step further with more portable and smaller robots known as “cobots” that collaborate with humans or other machines. Automated machines that pick, sort and package items are now used at transportation hubs in the last-mile delivery process.
Businesses across all industries face growing pressure to adopt and promote sustainable solutions, not just to cut costs but to reduce environmental damage. Last century’s investors typically ignored the financial and health costs of pollution, whereas this century’s investors are keeping track. Going more green is at the heart of sustainability as it preserves the value of nature resources.
The logistics industry is helping pioneer the adoption of mobile smart technology to monitor fleets and a wide range of shipping data. The main hurdles to overcome for this transformation to be successful are costs for new technology and the need to develop data standards in the logistics industry. Early adopters have been able to streamline operations and are setting models for future supply chains to follow.