Tariffs are at the front of minds of businesses as well as shoppers, who in numerous surveys say affordability is the number one economic issue. A key point in attempting to keep costs down is the managing of their supply chain, where technologies such as RFID, IoT and artificial intelligence (AI) have risen in prominence since the pandemic.
To get a better handle on these issues, RFIDJournal.com talked to Lisa Henriott is SVP Product Marketing at Logility, a leading provider of AI-first supply chain management solutions engineered to help organizations build sustainable digital supply chains. With over 30 years of experience in supply chain technology, Henriott has worked with hundreds of organizations to solve their complex supply chain challenges.
During this discussion, Henriott explained which technologies companies are using to help navigate tariffs in the current landscape, lessons learned from the pandemic that are being used now and findings from Logility’s 2025 Supply Chain Horizons Report.
RFIDJournal.com: What are some of the technologies that companies are using to help them navigate the recent tariffs imposed?
Lisa Henriott: Companies are using technologies like AI-powered analytics, and continuous network optimization in their supply chain planning solutions to navigate recent tariffs. The challenges of 2025 demand smarter, faster, and more adaptable supply chain strategies.
For supply chain leaders, this means leveraging a continuously optimized supply chain network that senses change, simulates alternatives, and adapts in real time. This approach allows businesses to predict risks, adjust sourcing and transportation based on rates and availability, and balance cost-efficiency with demand changes and service-level requirements. Unlike traditional methods, these technologies ensure supply chains are proactive, agile, and optimized for cost, service, and sustainability.
RFIDJournal.com: RFID and IoT are key technologies in giving companies insight into their inventories and supply chains. How are companies using these technologies?
Henriott: Companies are leveraging multiple data sources, including IoT, to gain deeper insights into consumer behavior and sales trends, ultimately improving inventory availability and supply chain performance. Advanced AI and machine learning are used to optimize inventory at the finished goods and WIP levels, providing real-time alerts and visibility into inventory performance. This helps planners resolve issues promptly and achieve higher service levels.
Additionally, IoT data is integrated to create a digital twin of the physical supply chain network. This digital representation allows companies to model multiple business scenarios and perform real-time simulations to determine the best course of action. These IoT-driven insights enable businesses to anticipate disruptions, optimize inventory across various locations, and ensure compliance while improving service levels and reducing costs.
RFIDJournal.com: What industries are most affected and how?
Henriott: While almost every industry is affected by tariffs and other similar impacts, you can think of them in three buckets:
- Rigid and brittle industries: Automotive, industrial durables, and semiconductors, for example, have deeply entrenched supplier communities. Qualifying a new supplier in a new geography takes lead time and confidence in making the right decisions.
- Flexible but cost-sensitive industries: Consumer goods and food & beverage sectors that need to pivot frequently to maintain tight profit margins.
- Secondary impact industries: Component manufacturers and logistics providers and component manufacturers that get caught in the ripple effect of broader supply chain changes.
RFIDJournal.com: RFID, automation, and AI-driven analytics are helping businesses track cost fluctuations at every stage of the supply chain, uncover hidden savings, and ensure compliance. Can you provide examples of this?
Henriott: In Logility’s 2025 Supply Chain Horizons Report, only 48 percent of respondents can predict disruption up to a week in advance. This means the rest are struggling to make scenario predictions quickly enough to keep pace with supply chain fluctuations. Further, 52 percent said that implementing the selected scenarios they can imagine is a challenge. But there is hope as we have seen the power of using automation and AI-driven analytics improve business response.
One example was with a global heavy equipment manufacturer that relies on a worldwide steel supply. When steel tariffs hit, they found new suppliers and used AI-powered simulations to model the entire supply chain impact. They realized a butterfly effect—a change in supplier volumes might ripple to different component production sites, ports of entry, and distribution flows.
Initially, the direct impact of paying a tariff or higher production cost for a new supplier would have cost the company $100 million. However, by re-optimizing the whole supply chain, they managed to mitigate the impact and realized a cost increase of only $60 million. This was achieved by tweaking supply routes, adjusting production locations, and shifting final distribution points without causing significant disruptions. This strategy went beyond merely swapping out suppliers to include the optimization of the entire production and logistics flow.
RFIDJournal.com: The pandemic was the last time supply chains faced such challenges. What lessons were learned then that are helping companies now? And what technologies that were not in use then are being utilized and how?
Henriott: The pandemic taught us that the ability to respond to change and pivot quickly was critical to survival. We also learned that a supply chain strategic roadmap, typically reviewed yearly or less frequently, needs to become a living, dynamic model. Even if the supply chain is not changing this month, the organization needs to know when suppliers, ship-from/ship-to, and carrier needs are changing. Traditional one-off network design projects— based on outdated assumptions and complicated tools— are no longer fast enough. By the time companies finalize a response to one change, data is stale, and circumstances have changed.
The difference between a reactive supply chain and a continuously optimized one comes down to the speed at which changes in environmental data like demand, costs, or tariffs are sensed, processed, and presented to decision-makers. If this can be done autonomously (runs while you are sleeping) actions can be taken without latency.
More than ever, businesses must leverage technology to be more proactive, not reactive. Businesses can predict risks – from tariff changes to supplier failures – before they cause disruptions.