Weathering geopolitical storms with local supply chains

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Manufacturers are now more than ever having to deal with the impact of global events such as U.S. tariffs on imports and exports and ongoing conflicts such as the Ukraine-Russia war. Localization provides an important solution for future-proofing supply chains that allows manufacturers to rely on local assets, but it often brings its own set of challenges, including increased distribution costs. Let’s take a look at how manufacturers need to align their operations across four business areas: remanufacturing, product design, sustainability reporting, and event prediction using industrial AI to reap the benefits of a localized supply chain.

Localization is getting a lot of attention. 68% of executives believe localized supply chains are a key strategy this year. But for manufacturers transitioning to localization, the process brings its own obstacles, such as aging infrastructure, which can lead to disruption and increased distribution costs. The switch to localization, especially when it comes to sourcing raw materials, can be further exacerbated by outdated technology that obscures visibility and overall connectivity within the supply chain. But industrial AI is ready and waiting to fill that gap.

Localization requires the transformative power of turning industrial AI into a future-proof plan for manufacturers to reap immediate benefits. Already, 82% of businesses have improved their resilience through localization, and an additional 77% have benefited from cost savings through localization, eliminating the need for costly transportation and currency inflation. So how can others make the transition to localization and start reaping the benefits?

1. Streamline your parts supply process and say goodbye to single sourcing

One of the most overlooked sources of supply chain vulnerability is product design. For example, highly customized components can limit a manufacturer’s flexibility as they are tied to single-source suppliers and long lead-time parts that are difficult to replace during supply chain disruptions. This is why manufacturers who simplify product design by moving from bespoke to standardized components can open themselves up to a wider range of suppliers, including companies close to home.

Nimble automakers led by example during the semiconductor shortage, deciding to replace custom chips with more commonly used multipurpose chips used in consumer electronics. In doing so, it was able to offset the initial drop in revenue, even though global car sales in 2021 fell by more than 12% compared to 2019. Standardization has made industries less dependent on specific critical resources and allowed companies to build more resilient and shorter supply chains. So what important lessons can we learn from this experience?

Manufacturers who design with flexibility in mind and focus on standardized modular designs can support faster sourcing, reduce lead times, and facilitate inventory management while responding quickly to changes in customer demand and raw material availability.

2. Upcycled materials for a greener carbon footprint

Because remanufacturing reduces the need for raw material extraction and long-distance transportation, it can be an important strategy for manufacturers to reduce their carbon footprint and supply risks. In fact, the Environmental Protection Agency (EPA) recommends remanufacturing as one of the most effective ways to reduce environmental impact while conserving resources. Local disassembly and repair centers also bring production sites physically closer to consumers, creating a more sustainable and responsive regional loop.

According to research, the U.S. auto remanufacturing market is expected to grow significantly, reaching an estimated USD 24.3 billion by 2030, as manufacturers compete to keep costs down. But this only scratches the surface of how remanufacturing can benefit manufacturing companies.

When manufacturers add industrial AI to the mix, they have a 10x chance of streamlining their remanufacturing processes. Industrial AI can also assess which components can be reused, match salvaged parts to new production needs, predict failures and improve recovery plans, identify the shortest supply chains, and flag companies that can use one company’s waste as raw materials. When it comes to core forecasting, industrial AI tools can also help remanufacturers reduce core safety stock by 2-4% by reducing expedited transportation costs and save 3-5% on transportation costs.

3. Transparent sustainability is now critical to business success

Sustainability practices are no longer just good for the planet, they are essential to long-term business success. Regulators, investors and consumers now expect increased transparency from companies, especially when it comes to Scope 3 emissions. Witness the fact that 80% of American consumers are willing to pay more for sustainable products, driven by a commitment to environmental health.

Supply chain localization provides a way to reduce emissions from transportation, allows for better monitoring of supplier practices such as energy use and working conditions, and helps manufacturers ensure they meet regulatory targets. But how can manufacturers clearly demonstrate that they meet these requirements?
Sustainability on the back end needs to be visible, transparent, and auditable, and AI-powered data collection and analysis is key to creating this record. Manufacturers can use industrial AI to automate emissions calculations and embed sustainability into daily operations. This allows companies to gain accurate carbon insights at scale and embed sustainability into their daily operations.

4. Unleash the power of AI to mitigate the next blow to your supply chain

The final piece of the puzzle is scenario planning. Today, only 5% of organizations worldwide are able to proactively predict and mitigate disruption before it impacts their business. Additionally, 75% of the world’s manufacturers still utilize static systems and siled organizations, with minimal collaboration between engineering and supply chain teams. Here, real-time intelligence and always-on insights enable a more proactive approach to supply chain risk, and industrial AI is key to that.

Manufacturers can say goodbye to what-ifs and instead simulate interruptions and replan in minutes using Agentic AI systems built into enterprise systems. Whereas previous scenario planning would take a human-led team a week to test a few key elements, AI agents will now be able to ingest massive datasets such as supplier performance, geopolitical risk, and weather and suggest real-time actions based on the patterns it learns.

AI also enables upside-down materials requirements planning logic by suggesting what can be built with available inventory, rather than simply what should be built based on old assumptions. For example, if a supplier experiences delays during a particular holiday season, AI can flag the risk and suggest alternative products that manufacturers can produce based on available resources so that manufacturing programs are not disrupted.

Smart ways to localize your supply chain

For manufacturers, localization is not about navigating the supply chain through an oncoming storm, but overcoming anticipated obstacles with the help of industrial AI.

Today’s supply chain models must address ESG impacts and sustainability issues while allowing manufacturers to remain agile to adapt to external factors and geopolitical forces. Manufacturers that take the initiative to realign their localized supply chain strategies will emerge as market leaders.