The pandemic disrupted and damaged global supply chains to the point that, two and half years in, we’re still experiencing critical shortages. Exacerbated by the massive adoption of e-commerce, the disruptions have put supply chains in the spotlight. And, as with many other aspects of the pandemic, it has also accelerated the adoption of technology solutions to meet the new challenges. Industry 4.0 technologies like IoT, AI, machine learning, 5G and digital twins are now driving automation and robotics across the industry.
Five years ago, DHL did an often-referenced survey in which they found that 80 percent of warehouses were completely unautomated and, of the rest, only five percent, fully automated. Since then, the picture has changed significantly, with automation expected to grow at a CAGR of 13.6 percent between 2021 and 2025, according to a Global Warehouse Automation Market report. In last year’s report from MHI and Deloitte, 49 percent of supply chain leaders had accelerated spending in digital technologies to make their operations more agile and responsive. Cloud computing, robotics, and inventory/network optimisation tools saw the biggest jump in terms of supply chain investment.
Whether it’s a manufacturer that relies on a just-in-time inventory systems or a retailer trying to manage a front-end e-commerce site, having data on where goods and materials are in the supply chain is becoming critical. Yet, a common complaint of both B2C and B2B suppliers during the pandemic has been the lack of visibility into where products or materials are hung up and when they can be expected to arrive. This makes production planning very difficult for manufacturers and, for retailers, it’s hard to manage customer expectations.
As goods move through ports to ships, trains and trucks on their way to local warehouses, they pass through multiple grey areas where real-time data on payloads is simply not available, often because they are using paper-based systems. Although usually implemented to help reduce the time required to search for items, digital inventory tracking systems are becoming essential throughout the supply chain to provide transparency to upstream and downstream clients.
Digital data is the lifeblood of most modern logistics systems. The most advanced systems can model the end-to-end process as a digital twin, using AI and machine learning to analyse and predict arrival times, bottlenecks and even predict shortages. The Achilles heel of these systems, however, is not having all the relevant data in real-time. Without end-to-end transparency, planning, pricing and delivery commitments can all be affected, meaning lost business, rising costs and reputational harm.