The 2025 holiday shopping season may still be weeks away, but there’s already an unpleasant chill in the air for retailers as they deal with the destabilizing effects of tariffs and trade policies on their supply chains, planning, and overall business strategy.
In July, for example, reports indicated that Target would end its popular price-matching policy as a result of tariff-related cost pressures. Meanwhile, the Toy Association, a trade group representing the toy industry, urged the Trump Administration to lift tariffs on toys imported from China amid ominous assertions that without relief, many small and midsized companies would go out of business.
These developments surrounding retail and tariffs came as companies contended with a slowdown in sales that the National Retail Federation attributed to “continued consumer worries about the impact of government policies on the economy.”
Three of the biggest pressure points retailers face as a result of the trade turmoil include:
Now let’s dive into those pain points, along with steps that can be taken to gain some relief.
In a recent survey of retail, consumer packaged goods and wholesale professionals, 60% of respondents indicated their companies were overhauling their supply chains in response to the fluid tariff situation.
Diversifying the supply chain away from China and suppliers in other heavily tariffed countries, in favor of nearshoring and multi-thread sourcing seems like an obvious solution, but for many companies, that’s easier said than done.
It’s not enough merely to identify a cheaper supplier. Other factors like volume, reliability, cost, and geopolitical risk also must weigh in the equation.
To do so, retailers need to develop supplier networks or ecosystems that enable them to share information in real time. They also need intelligent predictive tools that can analyze that information in light of current tariffs and export policies, then make supplier recommendations accordingly, showing trade-offs involving pricing, margins, inventory, logistics and the like under varying supplier, trade and tariff scenarios.
Many retailers responded to tariffs (or at least the threat of tariffs) by stockpiling import inventory, with a focus on shelf-stable goods and high-demand SKUs. Some reduced or discontinued inventory of tariffed products in favor of other options. There are, of course, trade-offs with these approaches.
Stockpiling can tie up working capital and reduce liquidity, increase warehousing costs, create logistics bottlenecks, and heighten shrinkage and obsolescence risk. That’s why some retailers combined stockpiling with new pricing strategies and/or supply chain shifts.
The first and most crucial step in getting a better handle on inventory is to unify the inventory-related data that may reside in multiple systems, including enterprise resource planning, inventory management, warehouse management, and point of sale. From there, it becomes a more straightforward exercise to apply intelligent analytics to the data.
With intelligent tools like these to support inventory decision-making, companies can shift from seasonal or quarterly planning to more responsive monthly or even weekly inventory planning, an important move when conditions are so volatile. Technologies like RFID, IoT, and warehouse automation also can play a key role in helping them reduce shrinkage and improve inventory visibility.
Creative approaches such as inventory pooling with marketplace partners can also mitigate some of the added cost and risk associated with tariffs.
For years, AI was seen as out of reach for smaller retailers, reserved for businesses with the cash to splurge on cutting-edge technology. But times have changed, and AI is leveling the playing field for retailers of all sizes.
Fluid trade and tariff policies have thrown demand forecasting and planning into chaos at many retail organizations, creating supply and demand imbalances that wreak havoc on the bottom line and reflect poorly on the company and brand.
Here’s another area where predictive analytics and AI-powered scenario modeling can restore a measure of clarity and sanity to demand forecasting and planning. Intelligent demand planning models enable companies to dynamically forecast demand within specific regions and customer segments, and right-size inventory, in response to shifting policies, without compromising service.
AI forecasting models have the ability to analyze huge volumes of real-time data (macroeconomic indicators, weather data, consumer sentiment, historical sales, social trends) to make on-target predictions that inform planning for specific SKUs based on changes in import prices or sourcing regions.
In today’s trade landscape, retailers have a lot to worry about, but by taking proactive measures and leveraging new AI capabilities, they can roll with the changes and even come out ahead.
