Newness Forecasting as a Tool to Navigate the Uncertainty Posed by Tariffs

The apparel industry is bracing for potential disruption as uncertainty around tariffs looms large. With the possibility of new tariffs impacting goods manufactured in China, brands, suppliers, and retailers are left navigating a complex and unpredictable landscape with higher costs and longer lead times. While the exact nature and timing of policy changes remain unclear at least until January 20, the potential implications are significant. 

In the technology sector, we try to see disruption as a positive force. So where can technology provide a silver lining in the apparel industry's current tariff situation?

The Market Opportunity Posed by Disruption

As someone who's spent years developing predictive analytics solutions, I see the uncertainty around China-manufactured goods as both an immediate threat and an opportunity for long-term success through digital transformation. Here are a few key opportunities for brands. 

First, as unit costs increase, overbuying becomes a less attractive hedge. This means that the value of accurate short- and long-term demand forecasting becomes more apparent in the P&L calculation. 

At the same time, it becomes even more important to optimize allocation and replenishment to sell as much product at full price as possible. 

Finally, tariff threats are a positive force for brands to diversify their approach to regional manufacturing to better align lead times with demand predictability. 

Not All Product Strategies Are Equal In The New Tariff Economy

Through our work with major retailers, we've identified a clear pattern: never-out-of-Stock (NooS) and established product lines benefit from demand predictability — you know (for the most part) what to expect and when. 

For brands with heavy NooS assortments, shifting manufacturing suppliers or even regions should offer a viable hedge. Low variability provides a clearer and more reliable margin, so any manufacturing shifts that don’t exceed that margin will allow for sustained profitability.

However, for brands that include newness or other “fast” assortments, the road ahead will be bumpy, with higher costs and longer lead times creating significant risks.

Overbuying is probably the default mitigation strategy, but it's expensive, inefficient, and ultimately unsustainable. Long lead times make it difficult to pivot quickly, and excess inventory leads to financial strain, especially if consumer demand shifts unexpectedly. 

As an alternative, brands may consider near-shoring newness items in order to shorten lead times. At the same time, this is also an opportune time to take a more test-and-learn approach while reshaping strategic operations and building new competencies.

The Technology Solution: Precision Forecasting as Infrastructure

As part of that reshaping effort, I recommend a focus on short-term testing and more agile production cycles, as well as exploring technology that improves forecasting accuracy. At Syrup, we've approached this challenge the way we approach any complex system problem — by building better prediction engines. We are investing heavily in better forecasting methods for newness items — such as event-based trend analysis — to enable our customers to better respond to market signals while minimizing overstock and waste. 

Our investment in better newness models isn't just about forecasting; it's about creating a resilient infrastructure that can adapt in real-time. By constantly testing against market signals and adjusting predictions, we've built a system that doesn't just survive uncertainty — it thrives on it.

Looking Ahead: The Imperative for Digital Transformation

The future belongs to organizations that treat their supply chain like a modern tech stack: agile, data-driven, and infinitely scalable. This means moving beyond traditional inventory management to embrace what I call "predictive operations" — where every decision is backed by robust data analytics.

While the industry awaits policy clarity, the real opportunity lies in building systems that turn uncertainty into a competitive advantage. From rethinking safety stock calculations to prioritizing speed and flexibility, the brands that adapt swiftly to these changes will be best positioned to maintain strength in this new economic reality.