How can OEMs navigate election-driven tariff shifts?


Firms that plan ahead to rethink where and how they source supplies in the new political landscape will gain a significant advantage, writes Neil Lustig

As the US elections unfold, automakers are holding their breath to see how the outcome will impact tariffs on critical automotive imports from China such as semiconductors and batteries. While the two presidential candidates have differing views on the use of tariffs, both are clear that they will be hard on China. Not only that, but the potential also exists for additional tariffs from other countries known for their manufacturing capabilities as the candidates look to level the playing field for US Manufacturers to bring growth and jobs on-shore.

Needless to say, no matter the election outcome, auto manufacturers’ supply chain costs will increase. There will be significant pressure on them to find a way to mitigate these cost hikes rather than simply passing them on to consumers. In the end, prices will rise. However, the firms that effectively plan ahead to rethink where and how they source supplies in the new political landscape will gain a significant advantage over competitors. So, what steps should auto manufacturers take to prepare for this seismic market shift?

People, process, and technology

Uncertainty inevitably equals risk. Supply chain leaders must understand this risk and take appropriate steps to soften the impact. This process ultimately comes down to three key pillars of any business: people, process, and technology.

Supply chain leaders need to ask themselves now if their teams have the requisite experience to address the risk. In addition to the experience, if they have the right processes in place to systematically assess and alleviate this specific risk. And, finally, if they have the right technology in place to enable this risk assessment. There is no quick fix for this challenge, given the complexity of the supply chain. It’s imperative for supply chain leaders to understand that addressing a shift in tariff policies will require long-term action.

On the people front, leaders should ask themselves three important questions when evaluating their team’s ability to navigate such challenges:

  1. Does the team have the requisite experience?
  2. Does the team have the skill and temperament to drive rapid change?
  3. Does the team have the capacity to take on this task?

Once they are confident about the people, it’s time to consider processes, which starts with identifying alternate supplier regions to fortify the network.

Developing a robust supplier network

Developing a robust, diverse supplier network is essential for combating supply chain crises. However, many factors must be considered when doing so.

The first thing to keep in mind is diversification to avoid an overreliance on any one supplier. Geographic diversification helps manufacturers reduce the risk associated with localised disruptions by sourcing materials from various regions. Regular audits of suppliers and partnerships to evaluate their capacity can help ensure reliability, scalability and responsiveness in a crisis. Implementing strategic inventory management practices to maintain reserves of critical supplies can provide a temporary buffer against sudden supply chain shortages.

Supply chain leaders must understand this risk and take appropriate steps to soften the impact

For example, during the most recent 2024 Olympics in Paris, and in many other Olympic instances throughout history, organisers experienced significant disruptions due to an over-reliance on specific suppliers. Companies can learn from this by incorporating proven tactics such as supplier diversification, demand forecasting, and others to enhance their supply chain resilience.

Compliance should also be top of mind. Many alternative regions have their own complications and could increase the risk of being out of compliance with, for example, US or EU regulations. As a supply chain leader, you don’t want to trade one set of tax and regulation issues for another. So, leaders must put in the time and due diligence required to research potential new suppliers thoroughly and work through any possible barriers they might pose for manufacturing or other production processes. Whatever suppliers they might come across, it’s likely they will encounter some new logistics hurdles or at least arrangements that will need to be made. But, with the proper time and focus, supply and procurement teams can overcome these challenges and identify new, reliable suppliers.

Political winds shift constantly, as do tariffs. This is a remarkably complex arena, so if this is new ground for a supply chain team, it would be wise to seek expert advice on the region in consideration. No one wants to be scrambling at the last minute with everyone else who’s underprepared. Predicting the problem and taking steps in advance to mitigate the issue early will determine success in the coming years. The role that technology, particularly AI and machine learning (ML), plays in predicting these challenges and providing actionable insights cannot be understated. By analysing vast amounts of data from various sources, AI and ML can help organisations not only foresee potential disruptions but also identify trends that may impact supply chain dynamics. This proactive approach allows businesses to make informed decisions and optimise their operations before issues arise.

Leveraging AI and ML

In today’s rapidly changing political landscape, real-time insights and predictive analytics are crucial for maintaining cost-effective supply chains and ensuring timely deliveries. Automakers can harness the growing power of AI and ML in several key areas, such as supply chain monitoring, demand forecasting, and cost-saving identification.

At the top of the list is supply chain monitoring. While AI cannot predict true black swan events, AI tools and applications constantly track market conditions and supplier performance, which means they can offer early warnings about potential disruptions. So, if one supplier is facing delays due to geopolitical complications or tariff changes, then AI can alert automakers with enough advanced notice to pivot and identify alternative supply sources before it impacts production.

The impact of the US elections on auto manufacturers and their supply chain costs cannot be understated

Tesla is an excellent case study for quickly reacting to a dynamic supply chain challenge. The company understood the scarcity of battery materials early in the electric vehicle (EV) transformation and acted to secure scarce raw materials before others had even realised the looming shortage. While not every company has the same resources that Tesla has at its disposal, the lesson to be learned here is to get ahead of the problem before it becomes a full-blown crisis.

AI can also quickly analyse historical data and current market landscapes, enabling manufacturers to forecast fluctuations in demand and adjust their procurement strategies accordingly. For example, if there’s an anticipated demand for EVs due to new sustainability or green consumer incentives, manufacturers have enough time to ramp up production and secure components, preventing shortages and increasing revenue.

AI and ML algorithms can also help auto manufacturers reduce looming cost increases. Semi-autonomous applications can create more effective competition across spend, identify cost-saving opportunities across the supply chain, pinpoint inefficiencies in purchasing patterns and optimise shipping routes. They will be a huge advantage when it comes to navigating rising tariff expenses and ensuring competitive pricing.

The impact of the US elections on auto manufacturers and their supply chain costs cannot be understated. And the time to act is now. Supply chain leaders that fail to take proactive steps to get ahead of the issue risk inflated costs, longer procurement cycles, and, ultimately, falling behind competitors. It’s crucial to take bold and proactive measures such as carefully evaluating your team, developing a robust supplier network, and leveraging AI and machine learning. These are the keys to success when it comes to navigating the complex global trade landscape ahead.


About the authro: Neil Lustig is Chief Executive of Arkestro



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