You receive a notification on your phone that a critical shipment from your China factory has missed its filing deadline with the customs broker. Your logistics manager is alerted that there is an 80% chance that the components he's waiting for are likely to be delayed another 48 hours by excessive port traffic and your GTM software advises diverting the shipment to an alternate port facility. Your compliance officer is informed that there is a 95% chance that a shipment of parts from Malaysia is likely to be held for up to three days to be subjected to a detailed customs inspection. If you think this type of information would be of great assistance to your supply chain business planning and operations, you are not alone. It is this type of integrated data and communications that are becoming the backbone of the Big Data led revolution underway in supply chain.
IDC recently released a report, "IDC FutureScape: Worldwide Manufacturing Predictions 2018," surveying the global manufacturing landscape. When creating its predictions the firm examined ecosystems and experiences, greater intelligence in operational assets and processes, data capitalization, the convergence of information technology (IT) and operations. Most of the group's predictions refer to a continuum of change and digital transformation (DX) within the wider ecosystem of the manufacturing industry and global economy.
Companies are starting to apply artificial intelligence across global supply chain management to improve efficiency, speed and decision-making in areas such as supply chain planning, warehouse automation, and logistics. The SCM World 2016 Future of Supply Chain Survey found that the importance of artificial intelligence has grown rapidly, with 47 percent of supply chain leaders believing the technology is disruptive to global supply chain management strategies. Market-research firm IDC predicts that by 2020, 50 percent of mature supply chains will use AI and advanced analytics for planning, and to eliminate sole reliance on short-term demand forecasts. Supply chain planning and optimization, including demand forecasting, are among the key areas where AI is already beginning to be deployed. Experts say that global supply chains have become so complex, and are affected by so many variables, that AI may be essential to help identify and predict problems and potential solutions.
Across industries, value chains are facing increasing uncertainty from climatic anomalies, market volatility, and the COVID-19 pandemic, among other factors. Industries as diverse as agriculture, oil and gas, and mining face essentially the same problem: they need the ability to both run with increased efficiency and recover quickly from unforeseen or unexpected challenges. But these two goals often conflict. If companies simply increase production levels, they'll inevitably run into bottlenecks--and if failures occur that worsen those bottlenecks, the entire network can slow down and become less resilient. For more on how COVID-19 has affected supply chains, see Knut Alicke, Richa Gupta, and Vera Trautwein, "Resetting supply chains for the next normal," July 21, 2020. Resolving this conflict presents several challenges.
How Does Technology Accelerate Supply Chain? While digitalization is affecting the transportation and logistics industry, new technologies are reshaping the market, influencing all stages of the supply chain and contributing to cost reduction and efficiency gains. Manufacturers and other assets – intensive organisations work to innovate, use technologies, discover new skills and help each other in every possible way. Continuous intelligence is key to accelerating the pace of innovation in the world's largest and most complex supply chains. In the face of increasing product complexity and customer demand, companies are turning to advanced technologies to transform their supply chains from pure operational hubs to epicenters of entrepreneurial innovation.