The conversation around bringing fashion and apparel manufacturing back to the United States has grown louder in recent months as tariff news continues to hit the stands—especially as 97% of goods in the industry are imported. For many, the idea seems aspirational; limited by high labor costs, outdated infrastructure and a lack of technical workforce, the barriers appear to be high. But we’re at a critical inflection point. Automation and artificial intelligence (AI) have matured to the point where reshoring is not only possible—it is practical given the right circumstances.

Our CEO, Max Ma, shared his opinion on reshoring for fashion and apparel with Sourcing Journal: https://sourcingjournal.com/topics/technology/reshoring-immigration-technology-manufacturing-trump-made-in-america-1234749503/

There was a time when regions across the country were thriving apparel production hubs. Factories operated efficiently, often powered by skilled immigrant labor and close ties to local retailers. That ecosystem didn’t vanish because it was inherently flawed, it shifted overseas due to cost advantages. Today, however, the dynamics have changed. Labor costs in countries like China have risen significantly, while regulatory burdens and global instability have introduced new risks into extended supply chains.

Meanwhile, pockets of domestic production still exist. Lower-cost regions such as South Carolina maintain infrastructure and history in apparel manufacturing, and niche factories continue to operate in urban centers like Brooklyn, New York. The conditions for regrowth are in place. What is needed is an alignment in policy, technology and the industry’s commitment.

The Role of AI in a Reshoring Revolution

Automation and AI are the great equalizers in the reshoring conversation. Dark factories have been seen in other industries—so it’s not unfounded that they could be possible for fashion as well but it’s unlikely apparel manufacturing will be entirely human-free; significant portions of the production process from fabric cutting, dyeing, material transport and even quality control, can be automated today. These advancements dramatically reduce dependency on manual labor while increasing output consistency.

Beyond the factory floor, AI-driven platforms like 7thonline are already transforming how retailers plan and manage inventory. By automatically generating merchandise plans based on historical data and predictive analytics, retailers can reduce overproduction, avoid lost sales and respond more quickly to changing demand. These benefits are particularly compelling when paired with shorter, domestic supply chains.

When production happens thousands of miles away, a single purchase decision can take months to reach the sales floor. The risk of misalignment is high. Reshoring, supported by intelligent planning systems, drastically reduces that lag and associated costs.

Policy Must Match Industry Momentum

For this reshoring vision to become a reality at scale, government support is essential. Other countries that have successfully built automated manufacturing sectors, such as Japan, South Korea and China, have done so with significant public investment. These governments have subsidized robotics, funded workforce training and created tax incentives to attract industrial development.

The United States should review success stories and take inspiration while following suit. Subsidies for automation equipment, tax incentives for reshoring investments and grants for workforce development would create a more level playing field. These policies should be considered industrial aid because they are strategic investments that can lead to job creation, higher tax revenue and greater national resilience.

Looking Ahead: A Smarter Supply Chain

The time to act is sooner rather than later. The fashion and retail industries are under immense pressure to improve speed to market, reduce waste and operate more sustainably. Especially as tariff uncertainty continues to hit the newsstands. A smarter, more localized supply chain that’s enabled by automation and powered by AI is the solution.

As we look to the future, the question is no longer whether reshoring is possible. The question is: are we ready to do the work collectively, across sectors and with government support to make it happen? With the right combination of policy, technology and willpower, we can build a new era of American manufacturing. One that is more intelligent, responsive and resilient than ever before.

7thonline is a global leader in AI-native demand planning and inventory management solutions, offering retailers and wholesalers innovative functionality that optimizes their supply chains and drives profitability across all key channels. To learn more about our merchandise software solution, contact the team at info@7thonline.com or book a demo.

As global trade dynamics continue to shift, retailers and wholesalers are finding themselves in a new era of volatility. Once beneficiaries of globalization, the consumer goods sector is now facing increased uncertainty as protectionist policies and tariff expansions raise the stakes across supply chains. 

According to a recent PwC report, these tariffs could impact the consumer product sector by up to $134 billion. That’s five times the current tariff load of $27 billion. And the apparel industry is bearing the brunt of it. To remain competitive and profitable, businesses must embrace a more precise, tech-enabled and forward-thinking approach.

5 Tariff Strategies to Avoid the Cost of Getting it Wrong

One of the most underestimated consequences of tariffs is the cost of getting it wrong. Overbuying, inaccurate forecasting, or delayed inventory movement now come with a heavier price tag. Goods that were once slightly overstocked and marked down for clearance are now inventory liabilities that were more expensive to import in the first place.

As Arielle Knutson, CEO of athleticwear brand Oiselle, said to a Reuters reporter, “Ordering the right amount of product—and not being stuck with too much cash tied up in inventory—is key. It’s an almost impossible needle to thread.”

It might feel impossible, but it isn’t. Here are five tariff strategies wholesalers and retailers can take to offset the impact of tariffs:

1. Ditch “Excel Hell” for a Dynamic AI Platform

Managing critical functions through disconnected spreadsheets is no longer sustainable. Excel may have once worked for forecasting and inventory planning, but it can’t keep up with the pace, complexity and volatility created by shifting tariff policies and global supply chain disruptions. Relying on siloed data leads to misalignment across teams, delayed decisions and costly mistakes. If merchandising, planning and supply chain teams are all working from different files or outdated reports, it’s nearly impossible to respond in time to tariff-driven cost increases or sudden inventory shifts. Integrated, AI-powered platforms replace “Excel hell” with a centralized system of truth—eliminating manual processes and enabling faster, smarter decision-making.

These tools analyze real-time data across departments including merchandising, demand planning, sourcing and logistics, to generate predictive insights that help retailers buy smarter, reduce overstock and respond swiftly to market changes.

2. Nail Down Forecasting Accuracy

Historically, imprecise forecasting has plagued the industry, leading to overstocking, stockouts and wasted resources that impact profitability. With tariffs, the cost of being inaccurate is magnified. To succeed, retailers must embrace planning tools that offer better insight into what sells, where and when. Advanced inventory planning systems, powered by AI, allow retailers to align supply with demand precisely. By analyzing sales data and market trends in real time, AI-driven systems can accurately forecast demand and ensure inventory is purchased with purpose. 

3. Start Earlier

Timing is everything. Beginning the product lifecycle earlier gives businesses more room to negotiate with suppliers and avoid price shocks. One 7thonline client saved an average of $1 per garment simply by starting the production planning process one week earlier than competitors.

Early actions also allow businesses to diversify sourcing, reroute logistics and hedge risk before it becomes a crisis. If one supplier faces an increase in tariffs, retailers have more time to react; they can negotiate, find cost savings elsewhere or go with an alternative supplier.

4. Don’t Let Excess Inventory Drain Your Margins

Tariff-inflated products that don’t move fast enough get marked down, wiping out margins even further. Excess inventory takes up space, ties up capital, increases carrying costs and in a tariff-laden landscape, represents money spent on goods that may never sell at full price.  The key to reversing this trend is smarter buying from the start, backed by real-time visibility into demand signals. With integrated inventory management platforms, retailers can continuously monitor sales data and adjust open-to-buy budgets accordingly. 

5. Give People What they Want

Rather than planning for supply, retailers need to plan for demand. That starts with better buying strategies that prioritize precise assortment planning and allocation; the ability to identify the right products and match them to the right store locations, in the right sizes, is critical for the consumer experience. Inventory management solutions ensure retailers are stocked with high-demand products and can adapt to shifting consumer behavior. AI provides smarter allocation recommendations based on the propensity to sell for each product at each store location. 

Read the original article on Fashion Mannuscript here.

To learn more about how your team can use AI to offset increased tariff costs, email us at info@7thonline.com or book a demo with our team.

Retail is in its AI era. From streamlining operations and optimizing supply chains to increasing personalization for shoppers, retailers have been eagerly jumping on the artificial intelligence bandwagon to modernize their brand and workflows. As the industry continues to embrace digital transformation and adopt innovative AI solutions, it’s important to remember—fragmented systems and duplicative functionality contribute to increased tech debt. 

Be wary of bolting new AI tools onto already complex tech stacks as it could create a sprawling mess of disconnected platforms and overlapping capabilities; simplify your AI stack before it becomes tech debt. Managing technical debt is crucial for maintaining agility and delivering exceptional customer experiences. Technical debt refers to the long-term costs associated with choosing suboptimal solutions that require future rework such as additional implementations. Accumulating technical debt can hinder innovation and agility, making it challenging for retailers to adapt to market changes effectively. 

Duds & Dupes: Your AI Tech Stack

Many retailers are expanding their technology stacks with a variety of AI platforms to support current and future business needs. As businesses grow, and needs change, retailers will seek out more solutions that address new concerns; however, sometimes this leads to patchy workflows and/or duplicative functionality. Streamline your technology stack by adopting a single AI system that aligns with your business needs and scales as you grow—analytics, personalization, forecasting, inventory optimization and more—not only simplifying your AI stack but also enhancing operational efficiency.

In order for AI to be truly impactful, it must be embedded into every step of your workflow. Instead of piecing together a patchwork of specialized AI tools, or worse—fake AI modules, select a system that offers comprehensive functionalities to avoid the pitfalls of managing multiple disparate tools: outdated data, low visibility, inaccurate forecasting, limited collaboration, etc.. 

Eliminating redundant components and embracing multi-purpose services also simplifies your AI stack. You don’t need separate assortment management systems for ecommerce and physical retail, or isolated demand planning for stores and wholesale accounts. Simplification not only cuts down on the resources needed for system upkeep but also accelerates the implementation of new features, ultimately enhancing your ability to respond to market demands and meet shopper expectations. As retailers continue to embrace digital transformation, choosing an all-in-one AI system can be the smartest way to stay ahead—without drowning in complexity.

The takeaway: you don’t need more AI tools. You need a better, unified one.

While adopting AI is essential for staying competitive, retailers must approach its integration thoughtfully—choose integrated and comprehensive solutions that closely align with business needs from the start. Unified AI platforms reduce complexity and technical debt, paving the way for sustained innovation and ensuring that your systems grow in tandem with your business objectives.

7thonline is a leading provider of cross-channel merchandise planning and assortment management solutions, empowering retailers and wholesalers to make smart decisions at every step of the retail workflow. With artificial intelligence and machine learning embedded into the core of the platform, 7thonline has been enabling leading retailers and wholesalers to optimize planning processes, demand forecasting and inventory productivity. To learn more, email us at info@7thonline.com or book a demo with our team.

For retailers that want to get ahead of their competitors, artificial intelligence will play a critical role going forward. Retailers globally lost an astonishing $1.77 trillion in 2023 due to poor inventory management according to IHL. However, AI stands ready to change that—if implemented correctly.

AI is already playing a major role in the retail industry, and its role will only increase over time. In a report entitled “Market Guide for Retail Assortment Management Applications: Short Life Cycle Products,” Gartner predicted that the top 10 retailers globally will tap into AI “to facilitate prescriptive product recommendations, transactions and forward deployment of inventory” by the end of 2025.

Smart allocation will be one area of particular importance for retailers, as getting the right products to the right place at the right time is critical for reducing or eliminating stockouts and price cuts caused by bloated inventory at a particular location.

How AI optimizes product allocation

Traditionally, product allocation is supply-driven; products are allocated based on static, predetermined rules set by internal teams: square footage of stores, sales volume, week of supply, etc. With artificial intelligence, allocation becomes dynamic. 

AI can drill down deep into the data to analyze and generate recommendations for site-specific assortments. Driven by demand drivers such as propensity to sell, AI systems can determine the best style and size mix within each category for each location and channel, and determine a sales index for individual products by analyzing historical sales data. 

To optimize product allocation, AI looks at the retailer’s sales history, including inventory levels and stockouts, to determine where that previous allocation strategy went wrong and then correct it. Effective allocation requires analysis of multiple data sets from each location, and only AI is capable of providing accurate analysis of all these data sets simultaneously.

In short, here’s how AI does all of this. The technology classifies and categorizes information based on visual, numerical or textual data. It then analyzes and modifies the retailer’s strategies, plans and allocations based on real-time data. It automatically generates analysis that makes faster response times possible and can help retailers retrieve relevant information quickly.

Real-time decision making

The advent of AI is empowering smart, real-time decision making across channels and locations. Before AI, retailers relied on spreadsheets and manual allocation methods that were time-consuming and error-prone—this is still common today.

Introducing AI into retail workflows transforms the planning process, making it effective and dynamic. With AI, retailers are armed with real-time analysis and smart recommendations that improve regional and store-level distributions; the industry-specific algorithms continually monitor real-time sales data to provide the most optimal recommendations.

Through this continuous improvement, AI can identify opportunity gaps in product ranges at each location, leading to additional sales—if those gaps can be filled. Without real-time understanding of inventory levels, retailers can refill stock right when it’s needed at the locations that require it.

Adapting to current conditions

Retailers face potential problems at both ends of the sales spectrum. On one side, they must deal with shifting consumer behaviors, but at the other end, they face the potential for supply chain disruptions that could prevent them from addressing those shifting behaviors.

However, AI is capable of continual monitoring and measuring actual performance against the plans created, creating a dynamic feedback loop. This feedback loop enables retailers to map their supply chains and connect parts of their business that were previously disconnected.

McKinsey estimates that retailers which implement technology to capture the variability of demand via forecasting can better predict customer behaviors, resulting in an average of a 3% to 4% increase in revenue. Through machine learning, as more data is collected and analyzed, these plans will become more and more accurate.

How to use AI to make predictions

According to McKinsey, autonomous supply chain planning can boost revenue by 4%, slash inventory by 20% and cut supply chain costs by 10%; AI enables retailers to continue meeting customer demand while reducing inventory (and its associated costs) because they can accurately predict demand across sizes, colors, locations and more.

McKinsey has found that companies have more success with implementing the technology when supported by four essential elements.

The first involves rewiring the organization by deploying real-time allocation dashboards, setting up a cross-functional supply chain organization and increasing the speed of critical decision making.

Secondly, McKinsey advises retailers to streamline their processes by enabling segmented business processes, promoting closed-loop planning and supporting “what-if” predictive scenario planning for allocation. Additionally, retailers should establish standard operating procedures to manage exceptions to typical situations.

Thirdly, McKinsey recommends digitizing the supply chain by leveraging scalable technologies and tools. Retailers are also advised to enable advanced analytics and AI-based planning solutions, integrate their technology across their supply chain and scale their technology to multiple regions and business units.

Finally, retailers should foster an accountability mindset and empower employees to make decisions based on the data and analysis received. Implementing AI also requires building talent with deep machine-learning capabilities—or outsourcing it.

Correct implementation of AI

When implemented correctly, AI is game-changing for retailers, but the key here is “correctly.” To achieve real value from AI, retailers need to move beyond buzzwords and embed AI into every step of their daily processes—rather than amplifying individual modules that are segregated from the rest of the system. 

For example, as a retailer, you need your open-to-buy system to communicate with your demand-forecasting tool, but AIs that doesn’t tap into all data sets simultaneously can’t provide accurate analysis or helpful information. Real AI should be able to provide robust analysis of multiple datasets without a data scientist’s expertise. 

Read the original article on The AI Journal here.

To learn more about our AI-native inventory management and demand planning solutions for retailers and wholesalers, email us at info@7thonline.com or book a demo with our team.

Now is the perfect time to reconnect and see what’s trending for the year ahead within the retail industry. In conversations with industry leaders at various tradeshows and meetings, five key shifts have emerged—especially in the retail tech world. These tech trends are shaping the future of retail, driven by the need for greater efficiency and maximizing the impact of data. Here are the top retail trends leading retailers are keeping an eye on in 2025:

1. Personalize Your Tech Stack

Every retailer needs technology that aligns with their unique business model. Success in retail depends on tailored solutions—there is no one-size-fits-all solution in retail technology. Individuality is why businesses continue to succeed, each carving out its place in the industry with distinction. The tech used and how it’s implemented must align with these differences. Whether a business is a small regional retailer, a global brand, a family-run operation or a publicly-traded company, technology must serve the specific needs of each business. Success lies in understanding those nuances, and tailoring your tech stack accordingly. 

1. Trending Beyond Manual Inventory Management

In retail, success hinges on precise seasonality and allocation, making it clear that manual processes can no longer keep up. The need for technology that balances both replenishment and allocation has never been more critical. Retailers must account for seasonal purchasing patterns, store location, size and even the color variations of garments to ensure the right products are in the right place at the right time. The goal is to avoid excess inventory sitting in a warehouse while also preventing stockouts that lead to missed sales. Getting this balance right will give retailers a competitive edge.

1. Balancing Push and Pull Allocation

For years, retailers have relied on reactive inventory strategies including manual corrections based on what’s needed in the moment. AI integrations and machine learning allow businesses to shift from adjusting to demand to proactively fine-tuning their allocation strategies, often referred to push and pull allocation. For example, let’s say you have two A stores. One is in Hawaii and the other is in New York. A push system would always send the same number of socks to both stores, even though socks are likely not selling well in Hawaii and you might even sell out of certain colors in New York. 

A push system stocks inventory based on store parameters like the square footage and the volume of the store. It’s not based on factors that determine demand. It’s the warehouse that pushes inventory to stores. Push systems make sure stores are fully stocked regardless of who comes to buy it. 

The pull system corrects this issue by stocking stores based on local demand—but it cannot be done without historical data and it cannot be done manually. The challenge for a lot of retailers is that a pull system requires a level of data and metrics. It can respond directly to consumer demand, local weather and store sizes. It helps to keep inventory lean and reduce waste. 

Many retailers are now adopting a hybrid approach, leveraging AI-driven insights to strike the right balance between push and pull allocation. By setting up intelligent, data-backed rules for replenishment and distribution which are tailored to seasonality, store location, product type and customer behavior, businesses can optimize inventory flow and boost profitability.

1. (Small) Retailers Can’t Afford to Stay in “Excel Hell”

The time to shift to real-time, automated data tools is now. Many retailers are moving beyond “Excel Hell,” replacing outdated Excel spreadsheets with technology that provides real-time data, forecasting and reporting. Even small businesses are now embracing digital tools to stay competitive.

Historically, small retailers have been unable to capitalize on innovative tech due to limited resources. With the rapid advancement in retail tech and inventory management solutions, they can’t afford to not adopt. There are a plethora of affordable options, empowering small business to access customizable solutions that streamline inventory management, enhance customer relationships and improve overall efficiency. By leveraging automation and AI-driven insights, small businesses can offer a seamless shopping experience while optimizing operations to reduce costs. 

1. Seasonal Planning: Make it or Break it

The better seasonal inventory is planned, the stronger profit margins can become. However, seasonal inventory management requires long-term forecasting while navigating short-term challenges. Retail supply chains involve multiple moving parts. Those include suppliers, warehouses and shipping partners. All of these elements must work seamlessly to avoid costly disruptions. Unexpected delays can lead to stockouts, resulting in lost revenue and frustrating customers, while overestimating demand can leave businesses stuck with deadstock that are difficult to move after peak seasons. Rigid warehouse contracts can further complicate matters, leaving retailers with high storage costs when demand drops. To optimize seasonal selling, businesses must invest in flexible logistics, data-driven demand forecasting and adaptable inventory strategies. 

2025 Retail Trends and the Art of Finessing Technology

While AI might be the brains behind modern retail, people remain at the heart of its success. Technology can analyze data, predict trends and optimize inventory, but it’s the employees on the ground who understand the nuances that AI can’t capture. They know what can be done better, spot local issues like road construction affecting foot traffic or a special event bringing in new customers, and make the critical adjustments that drive business success. 

To discover more retail trends, industry insights, and innovative shifts in retail tech, read our blogs. Email us at info@7thonline.com to talk to the team.

The retail industry has been struggling for years, even decades with a major challenge—the siloed nature of operations. Traditionally, sales, supply chain and production functions have worked in isolation, leading to inefficiencies, misaligned processes and missed opportunities for growth. It also affects employee morale and their ability to focus on important tasks. These disconnected systems result in inventory imbalances, production delays and a lack of visibility across operations.

At the same time, a significant opportunity is emerging. Integrated demand, the use of artificial intelligence and machine learning and inventory planning systems are redefining how businesses approach operations. By breaking down traditional silos, these systems enable seamless collaboration between teams, fostering smarter decision-making and streamlined processes.

The critical question for businesses now is, how can they bridge the gap between forecasting demand and aligning production with real-time collaboration? Solving this challenge requires advanced tools and a shift in mindset. Retailers need to view the supply chain, demand planning and production as interconnected pieces of a larger, unified strategy.

A Look at the Data: Retail Silos

Silos can be the most costly problems in today’s market. For example, Nike reported holding $9.7 billion in excess inventory in late 2022. That’s an increase of 44% from the previous year and a staggering figure demonstrating just how tough inventory management can be for one of the biggest brands.

Most of us know the results. By 2023 Nike announced an aggressive $2 billion cost-cutting program and employee layoffs. The stock plummeted 12% in a single day following these measures, and gross margins dropped from 45.9% to 42.9% year-over-year. Current global estimates reveal that the global retail industry loses approximately $1.75 trillion annually due to out-of-stock items, representing about 8.3% of total retail sales.

The Evolution of Inventory Management from Sales Planning to Production

Traditionally, inventory management has centered around sales planning and revenue forecasting, with businesses striving to predict how much product they could sell and where those sales would occur. While these projections provided valuable insights, they often stopped short of addressing the next critical step: translating forecasts into actionable production plans. This gap left supply chain and production teams scrambling to meet demand, resulting in inefficiencies, inventory surpluses or shortages that impacted profitability and customer satisfaction.

Key Features of Modern Solutions

Modern inventory management solutions are designed to address the needs of today’s dynamic retail environment with a range of advanced features. Global functionality enables businesses to operate seamlessly across multiple currencies and locations, making these tools scalable for both small retailers and multinational enterprises.

Comprehensive planning tools provide end-to-end support, from pre-planning activities like forecasting revenue and demand to post-planning tasks such as determining production needs and allocation resources. Real-time insights further enhance decision-making by offering a clear view of inventory flow and ensuring alignment with overarching business goals. Together, these features empower retailers to streamline operations, optimize resources and respond quickly to market demands.

Solving Problems Holistically by Focusing on Upstream vs. Downstream

Effective inventory management requires a holistic approach that bridges upstream expertise with downstream integration. Upstream capabilities—such as long-term demand forecasting—enable businesses to anticipate production needs and align them with raw material and resource planning. This foresight helps prevent supply chain disruptions and ensures production efficiency. On the other hand, downstream tools focus on managing in-season inventory and making real-time production adjustments to meet evolving consumer demands. By seamlessly connecting these two ends of the inventory lifecycle, modern solutions provide businesses with a unified system that minimizes inefficiencies, reduces waste and ensures optimal stock levels. In this industry, we know that success means that there is only one item left by the end of the selling season. 

Differentiating Factors in the Market

Flexibility and complexity have become essential in inventory management solutions. Modern systems stand out by offering the ability to adapt to the unique needs of businesses, whether they are small retailers or global enterprises. Customizable solutions allow companies to address specific challenges within their supply chains, sales planning and production processes, providing a significant edge in meeting market demands. This level of adaptability ensures that businesses can scale and pivot quickly, staying ahead in an increasingly fast-paced environment.

Equally important is the value of long-term expertise. Many legacy systems, once focused solely on sales or demand forecasting, have evolved to integrate comprehensive solutions that address both upstream and downstream processes. These platforms leverage decades of industry knowledge while incorporating modern technology—such as real-time data analytics and artificial intelligence-driven insights—to deliver more robust and efficient planning tools.

The Future of Retail Operations

The future of retail operations lies in extending planning horizons to anticipate shifts in consumer behavior before they occur. By leveraging advanced forecasting tools, businesses can move beyond short-term planning and prepare for long-term trends, ensuring they stay ahead of customer expectations and market demands. This forward-thinking approach minimizes disruptions and creates opportunities for growth. It gives us time to think and use the profits saved by using new technologies to future invest in platforms that make an impact. 

Read the original article on Fashion Mannuscript here.

To learn more about breaking down silos and improving retail operational efficiency, email us at info@7thonline.com or book a demo with our team.