The preceding decade saw how automation trends transformed supply chain management and made it more efficient and competitive. Technological advancements in the supply chain industry spurred innovations and research in various sectors of supply chains that increased resilience in operations. In fact, the advancement in technology powered the generation of more specific data analytics that support predictive analytics and future trends.

In these most unpredictable times, digital empowerment through blockchain technology for automation provides improved integration of operations. It can predict future demand, avoid overstocking or understocking, and efficiently manage unknown expenses. In a nutshell, cloud-based supply chain solutions have made SCM inclusive, effective, and target-oriented.

In the following paragraphs, let’s explore how the latest trends in supply chain automation have optimized various operations of supply chain management.

Latest Trends in Supply Chain Management

Supply Chain Management has multiple operations, though each is independent but reciprocates to action and data received from the other. Manual feeding of data generated at various levels of operations slows the work, increases the possibility of errors, and delays analysis. Technology advancements relay information in real time and help in decision-making.

• 1. IoT in Supply Chain—The Internet of Things is connected with physical devices to monitor, trace, and track an object. This reduces human intervention, and data about the location and volume of products can be obtained instantly. Real-time visibility in the Supply Chain optimizes logistics management and gives control over inventories spread over multiple locations. Automated inventory tracking through sensors allows insight into the wear and tear of goods, anticipated demands, location, and need for replacement or shipping to other places. IoT has transformed the way supply chain management functioned in the past; today, decision-making is faster with efficient monitoring of stocks, automated reordering process, accuracy in projection of consumer demands, error-free and overall boost to investment and profit.
   
  Retailing requires robust SCM and logistics. Automation streamlines operations and data sharing is possible in real-time. Real-time visibility enables tracking deliveries and sending updates to consumers, which builds loyalty and improves customer relationships.
• 2. Artificial Intelligence & Machine Learning—Artificial intelligence and machine learning are active agents in supply chain automation. AI algorithms and machine learning enhance real-time reporting with interactive data visibility and allow businesses to make proactive decisions related to demand forecasts and changes. For example, AI-generated predictive analytics for inventory management has reduced businesses’ response time. Inventory planning is streamlined, cost-cutting opportunities are identified, and interactive real-time reporting detects consumer interest and buying patterns. AI automates operations for focused and result-oriented work processes.
   
  Another example is the Integration of Machine Learning in Logistics. The algorithm and predictive analytics generated by AI and Machine Learning help in studying the demand pattern. This can reduce fuel consumption and make the supply chain sustainable and more economical. Innovative order fulfillment ways can also be found for order management.
• 3. Warehouse Automation Solutions—Automation in the warehouse takes care of the movement of inventories within and in & out of a warehouse. Warehouse Management Software Trends optimize space utilization and management of inventories for multiple points of sales. Automation organizes and speeds up repetitive, mundane tasks of maintaining records of the inventories. Repetitive tasks are prone to errors by humans, and automation reduces the scope of wrong data inputs and analysis. Managers use Artificial Intelligence in Warehousing to accomplish and finish time-consuming, repetitive, but essential tasks for generating predictive analytics regarding consumer demands.
• 4. Robotics—Integration of Robotics in Logistics brings accuracy and swiftness in the supply chain. Robots improve work quality by reducing human errors and increasing work speed. Productivity is enhanced as robots, unlike humans, can work around the clock without losing focus and energy. Robots increase agility and flexibility; they efficiently perform warehouse tasks of sorting, stacking, and counting with greater accuracy and speed. Robots are ideal to compete with the need for sustainable transportation and several other omnichannel operations of the supply chain, as they can track and trace without losing interest or patience.
• 5. Augmented Reality—Supply Chain Automation Companies also recommend the installation of Augmented Reality, as businesses lack sufficient knowledge about inventory or other aspects of the supply chain required in demand forecasting. It works in collaboration with AI and Machine Learning and generates real-time data, which is helpful in intelligent decision-making related to the supply chain. Augmented Data Intelligence provides big data required for resolving issues, regular decision-making, forecasting, and obtaining insights. Businesses use AR in packaging, sorting, and labeling for quick clearing of orders and building customer loyalty by being accurate with specifications and details pertaining to the orders.
• 6. Automation Trends in Transportation—Among all supply chain management operations, transportation is the most critical and expensive cell in this complex matrix. Technological advancements such as the integration of AI in logistics have opened ways to cut costs, be sustainable, and deliver orders to consumers on time. AI algorithms and predictive analytics of Machine Learning optimize route planning. Rerouting, opting for sustainable transportation and freight management, becomes efficient and cost-effective with automation.
   
  Remote monitoring and control systems give real-time insight into shipping and transportation. The system generates alerts about weather disturbances, blockages, new policies for crossing borders, any deviations from or in the intended path, etc.; such knowledge prepares management and reduces downtime in delivering an order. AI also monitors and reduces the chances of theft or loss during shipping. Businesses also use automation in transportation to locate cargo and reasons for fleet delays.
• 7. Automation in Last-Mile Delivery—Of all the operations of SCM, last-mile delivery is the most crucial and sensitive part. It is directly connected with the customers and is the chance to gain their confidence. It is also the costliest part of the process, as customers want quick delivery, and location varies. Remote monitoring and control systems have helped drones pick up orders for last-mile delivery since these can be monitored and guided remotely. An automated system can work out more fuel-saving options, such as EV cycles or store collection. It maps all the routes and singles out those that can reduce cost without impacting delivery time.
• 8. Cloud-based Supply Chain Solutions—Supply chain software such as TMS (Transport Management System) or OMS (Operation Management System) and others are cloud-based solutions. These can be remotely monitored and controlled without incurring any extra cost in creating a hub for the system. This software syncs supply chain operations and provides insights into work; these further help in proactive decision-making and demand forecasts. Managers use various operations software to streamline the supply chain for more intelligent decision-making and increasing accuracy in data generation.