The logistics sector is undergoing a major digital transformation, driven by technological advancements, exponential growth in e-commerce, and heightened demand for speedy and last-mile delivery. Artificial intelligence (AI) has made considerable inroads into the sector, with the development and implementation of various AI-powered technologies. These include predictive and prescriptive data analytics, robotics and autonomous vehicles. Leading logistics enterprises are rapidly adopting these solutions for increased operational efficiency and supply chain optimisation.

A look at the key technology trends that are transforming the logistics sector…

ML and analytics

Machine learning (ML) can automate warehouse operations, eliminating manual errors that lead to delays or shipment losses. Routine tasks such as picking, sorting and palletising of goods are automated. It can also provide insights into inventory levels, stock availability, shipment time frames and fulfilment rates. ML algorithms can suggest the most efficient route for delivery, while minimising driving time and emissions by analysing real-time data such as traffic patterns and distances. When combined with predictive analytics, they can also anticipate traffic congestion and disruptions due to weather conditions and other unforeseen circumstances. ML can also analyse data from real-time market events and risks along with point-of-sale data to improve forecast accuracy at the granular level.

A recent innovation on this front is Carrier Logistics, Inc.’s AI-enabled routing logic and planning optimisation tools that empower fleets to automatically route and assign shipments for each customer. This optimisation not only reduces fuel consumption and operational costs but also ensures timely deliveries. Meanwhile, Ecom Express Limited launched Bulls.ai to simplify geolocation-related challenges for the delivery of e-commerce parcels across India, especially in small towns and cities. Bulls.ai solution improves operational accuracy by correcting, standardising and predicting geo coordinates for addresses in Tier II cities and beyond, where the address quality becomes inferior.

In addition, AI capabilities broadly offer four types of advanced analytics in the logistics sector:

  • Descriptive analytics: It provides clarity by stating facts about things happening within the supply chain, through indicators such as delivery time and freight cost per unit.
  • Diagnostic analytics: This provides the reason behind a phenomenon or event. It can help prevent the recurrence of problems or identify past scenarios, which yield good results and can be recreated.
  • Predictive analytics: This is helpful for risk management and presents the most probable outcomes and business implications in a given scenario.
  • Prescriptive analytics: This offers data-driven recommendations for achieving operational and financial goals in the supply chain.

From the environmental viewpoint, carbon dioxide emissions from freight transportation account for 30 per cent of all transportation-related carbon emissions from fuel combustion. By using predictive analytics solutions in the areas of route optimisation, robotics and anticipatory shipping, real and quantifiable improvements can be made to sustainability in last-mile delivery.

Internet of things

Internet of things (IoT) in logistics involves wireless devices such as radio frequency identification tags, eSIM and global positioning system sensors to track shipment location and monitor real-time data. With IoT technology, AI algorithms can process this data to assist route management and improve security by predicting emerging issues. IoT technology can also be used to automate inventory management. With the automatically obtained data on inventory levels from smart shelves and IoT sensors, companies can improve forecasting and optimise stock levels. Further, fleet management is a common application of IoT devices that can be installed in vehicles to track their location, speed, fuel consumption and other critical parameters. This can help businesses optimise routes and schedules, diminish idling and improve fleet performance. These solutions can help reduce fuel costs and assist in monitoring driver safety.

For example, DHL uses IoT devices to monitor the location, temperature and humidity of its shipments in real time, enabling the company to optimise its supply chain and enhance customer satisfaction. DHL also uses IoT devices to track the movement of its vehicles and optimise its routes.

Autonomous vehicles

Autonomous vehicles, also known as self-driving or driverless vehicles, are a reality in logistics now, thanks to rapid advancements in AI, sensor technology and connectivity. These vehicles can operate without human intervention, navigating roads, making decisions and safely transporting goods. Autonomous vehicles can operate round the clock, reducing downtime. Moreover, these vehicles can combine other process steps such as loading and unloading in order to increase the overall efficiency of operations. While safety concerns exist, autonomous vehicles have the potential to reduce accidents caused by human error, such as fatigue or distraction. Many autonomous vehicles are electric or hybrid, contributing to reduced emissions and a greener supply chain.

Cloud logistics

Cloud logistics involves the use of cloud computing to control operations performed across the supply chain. It encompasses the mass storage of data, information and web services processed through servers connected to the internet. This modality makes it possible to acquire and install digital programmes internally or through a supplier, which houses them on its own servers. Cloud-based logistics solution offers scalability in infrastructure to meet increasing demand, while remaining cost effective by eliminating the need for hardware infrastructure.

Companies that manage their logistics processes in the cloud rely on programmes such as a warehouse management system (WMS) in the software-as-a-service model. Cloud simplifies the installation and deployment of WMS. As per industry reports, 86 per cent of supply chain-based companies will incorporate cloud computing into their operations within the next five years. This is a significant rise from the current 40 per cent adoption rate.

Safexpress collaborated with IBM to deploy an end-to-end cloud-native transportation management system platform, PROPEL-i. The logistics operations platform is helping Safexpress to remodel its core business processes. It enables the company to obtain dynamic pricing modelling capabilities, attain agility in demand management, along with enhanced visibility and transparency for its customers. It will also help the company to further expedite the adoption of next-gen technologies and digital solutions. The platform leverages the container management capabilities of Kubernetes to offer availability, scalability and security with a self-healing runtime environment.

Blockchain

In logistics, blockchain offers a secure and inalterable method of verifying the authenticity of products. For example, DHL and Accenture have a joint blockchain project, a serialisation prototype, to track pharmaceuticals right from the point of origin to the consumer. The pharmaceutical and health industries stand to benefit from high safety standards through the use of a common and secure ledger. All stakeholders in the supply chain including manufacturers, suppliers, distributors, pharmacies, hospitals and doctors have access to this ledger. Further, blockchain-based smart contracts can automate and streamline supply chain processes effectively, improving efficiency and reducing costs. Self-executing contracts can be achieved with the terms of an agreement between buyer and seller, written directly into the code.

Blockchain solutions can also help solve disputes due to missing cargo. A notable example is FedEx’s blockchain-based ledger to address the issue of missing cargo and resolve freight claims. The system collects information from the shipping and receiving parties as well as carriers, effectively reducing fraud attempts and eliminating third parties. It has helped FedEx secure the chain of custody for all packages and streamline data exchange, saving millions of dollars annually in freight claims.

Digital twins

Digital twins are the virtual replicas of physical sites. Unlike 3D models or simulations, digital twins are dynamic, data-driven entities that evolve over time, just like their physical counterparts. When trialling changes to a supply chain, a digital twin can be created to test in a virtual environment without disrupting the existing operations. In logistics, digital twins can simulate complete supply chains, providing valuable insights into areas such as warehouse operations, inventory management and transportation efficiency.

DHL Supply Chain introduced its first digital twin of a warehouse in the Asia-Pacific for Tetra Pak. The digital twin is supplied with real-time data on a consistent basis from the physical warehouse in Singapore and makes changes consistently in real time.

The future of transit

The global logistics industry is already leveraging cutting-edge technologies to ensure competitiveness and reduce costs. Gartner projects that 50 per cent of supply chain organisations will invest in AI-powered applications and advanced analytics through 2024. However, India’s logistics sector is comparatively behind in adoption, largely due to the complex infrastructure and varied terrains of the country, the fragmented nature of the industry with many small players and integration issues with legacy systems. Nonetheless, continued industry efforts and the regulatory push through the National Logistics Policy are paving the way for the digitalisation of the sector.

Sarah Khan