Supply chains in 2021 may have reached breaking point, but 2022 could offer some semblance of recovery. Businesses can learn from the lessons of the past year to start rethinking their approach to sourcing the materials and products they need to operate. How can companies capitalize on the failures of the previous year to ensure that their supply chains fully recover this year and become less vulnerable in the years to come? This means investing in AI, automation and machine learning to digitize the supply chain and support manufacturing diversification.
Invest in AI, automation and machine
The global supply chain has become increasingly unstable during the pandemic, leading to a shift in thinking about how to recover and create a more robust future supply chain. Businesses are turning to technology to improve processes, reduce time and create greater transparency. Gartner predicted that at least 50% of major global enterprises will use artificial intelligence (AI), advanced analytics and IoT in supply chain operations by 2023.
By embracing AI, automation, and machine learning, companies can develop a 360-degree view of the existing supply chain and more proactively manage potential disruptions. AI can quickly analyze an intensive amount of data to provide increased visibility into operations and enable better decision-making. Artificial intelligence now has the power to do everything from demand forecasting models to end-to-end transparency. For example, AI can alert businesses to how an upcoming severe weather event will disrupt the supply chain and make suggestions on how to address bottlenecks in real time.
By being able to predict transportation disruptions, positive or negative demand shocks, and production issues, companies can intervene and adjust their supply chain processes more quickly. The gain for investing in this technology will be enormous. McKinsey estimates early adopters of AI-powered supply chain management improved logistics costs by 15%, inventory levels by 35% and service levels by 65%, compared to competitors slower.
Location and diversification of manufacturing
Chip manufacturing needs both localization and diversification. There is a reliance on a few key geographies for manufacturing, which makes the supply chain vulnerable to disruptions in these areas. For example, if China were to stop shipping PCBs, the world would experience a severe shortage. Companies used to move their operations overseas for more profit and now efforts are being made to bring manufacturing closer to home. A study by the European Commission found that Europe is “heavily dependent” on China, Vietnam and Brazil for imports, particularly in areas such as batteries, raw materials and semiconductors. In response, the European Union, like many other government bodies, has stepped up efforts to build resilience in its supply chain through policies to support the creation of more diverse alternative supply chains.
COVID-19 has exposed the underlying issues and lack of resilience in the global supply chain. For our supply chain to fully recover in the long term, companies need to invest in the latest technologies while governments around the world need to support the localization and diversification of manufacturing. Without the integration of technologies that enable greater visibility into a variety of effects, as well as more geographically diverse production chains, companies will continue to suffer the backlash of the fragility of global production. Accelerating the use of AI technologies and beginning to reconfigure the supply chain to make it more diverse will have significant long-term payoffs in creating a more resilient and secure global supply chain.
all quarters, Source engine publishes a comprehensive lead time report covering the electronic components industry.