Chinese small factories shift to 'small-order, quick-response' model, ditching million-yuan orders for 50-piece batches with up to 40% margin

Source: Times Weekly | By: Liu Ting

Editor's Note

Amid global trade fluctuations, a cooling consumer market, and the rise of AI, China's small factories are quietly shifting gears. Zhejiang Province, in particular, is home to a dense concentration of "hidden champions"—manufacturing firms, supply chain enterprises, foreign trade companies, specialized market operators, and consumer brands. Though these small factories may not occupy center stage, they form the solid foundation of Chinese manufacturing. They are evolving from earning processing fees to building brands, from relying on manual labor to leveraging AI for efficiency, and from chasing bulk orders to embracing small batches—continuously reinventing themselves.

Times Weekly launches the China's Small Factories series to spotlight these units at the end of the supply chain and document the most vivid business stories and transformations.

The Rise of Small Orders

"More and more small orders of just a few dozen pieces are coming in. Customers leave increasingly detailed requirements—changing designs, adding logos, sometimes even redoing the packaging." Yan Qing, founder and CEO of Yiwu Heting Outdoor Products Co., Ltd., spoke with evident emotion.

His company, which produces cycling masks, neck gaiters, and other outdoor gear, has grown accustomed to handling small orders daily. In fact, when orders worth 500,000 yuan or 10 million yuan come in, the company sometimes actively turns them down. "Because orders of 20,000 to 30,000 yuan offer higher margins," Yan explained.

Yan broke down the numbers for a reporter. For an order of around 500,000 yuan, after multiple rounds of price inquiries from foreign trade companies, the gross profit margin might be only 5%–10%. For orders of 10,000–20,000 yuan, margins can reach 20%–30%. For even smaller custom orders, margins can hit 40%–50%.

Yan's approach is not unique. Dozens of kilometers away, Shu Kai, general manager of Zhejiang Yifan Daily Necessities Co., Ltd., is also rethinking his business partnerships.

Shu revealed that Yifan wants to pursue online customization and take on more fragmented, urgent orders. But the supply chain built around large orders may not keep up. Decisions must be made: which products stay in-house, which go to external suppliers, and whether partner factories are willing to adjust production schedules for dozens or hundreds of items.

Shu's solution is to concentrate orders with a few core suppliers, using consistent business volume to secure their cooperation on small and urgent orders. "You have to handle big orders, but you also have to handle small ones," he said.

The 'Small Order, Fast Response' Model

The supply chain model adopted by Yan and Shu is known in the industry as "small order, fast response" (小单快反) .

Under traditional manufacturing logic, a small workshop grows into a factory by expanding facilities, adding equipment, and scaling orders from hundreds to thousands or tens of thousands. But this model creates a mismatch between supply and demand. Long production chains, rapid seasonal changes, and unstable consumer preferences mean that suppliers who stockpile large quantities in advance face high inventory costs, long payment cycles, and financial pressure.

In contrast, "small order, fast response" is a supply chain model that emphasizes small-batch production and rapid response to market feedback. Companies first test the market with small batches (typically 50–200 units), then use real-time sales data—such as store sales or e-commerce click-through rates—to drive production of best-selling items.

This approach shifts the supply chain from "producing based on sales forecasts" to "producing based on actual demand." It has not only transformed small factories like Heting Outdoor and Yifan Daily Necessities but has also become the standard in industrial clusters across Yiwu, Shaoxing, and beyond.

These small Chinese factories are rewriting the "pricing logic" for a single order.

No One Dares to Go All In

In the long-established division of labor within Chinese manufacturing, factories sit several steps away from consumers. Brand owners, trading companies, distributors, and retail channels stand between them. Questions like "Why do consumers like this style?" or "Will they still like it next season?" are answered by those closer to the market.

Under this system, the factory's job was simply to make good products.

Shu Kai recalls the rhythm of Yifan's early business with supermarkets. From design to production to shelf placement, the cycle was long. It took three to four months before the company knew sales results. By the time a poorly performing style was identified, half a year might have passed, and unsold goods could even be returned by the channel.

In the era of large orders, efficiency came from certainty. Someone placed a bet first, and the factory scaled it up.

Wu Xianmin, founder and CEO of Zhejiang Duopin Daily Necessities Co., Ltd., described this traditional factory mindset as "yield per mu" (亩产). Factory owners focused on whether their facility could generate 30 million or 50 million yuan in annual output. With more orders, they bought more machines and expanded capacity. Where the market ultimately went was left to brands, traders, and channels.

This logic built the solid foundation of Chinese manufacturing. Decades of industrial division had broken the supply chain into increasingly fine segments: someone weaves fabric, someone prints patterns, someone makes molds, someone handles packaging. As long as orders were clear, factories could produce 10,000 or 100,000 items faster and cheaper.

That path still exists, but a new fork has appeared. Truly large orders no longer always appear on day one. Instead, they grow slowly from repeated small orders.

The 1688 platform offers a clear window into this trend. Platform data shows that demand for personalized, fragmented, and customized procurement is growing rapidly. Many buyers use AI to complete designs, then turn to 1688 to find factories for customization. In the apparel industry, for example, traditional first orders after sampling typically ranged from 3,000 to 5,000 pieces. Now, e-commerce merchants can test the market with 50–100 pieces first, then reorder based on feedback.

This shift in order patterns has first rewritten the factory's customer list.

Sales staff at Yifan Daily Necessities responsible for Xiaohongshu (Little Red Book) clients now deal with small buyers who previously had difficulty entering the factory's procurement system. Some are still in high school, using AI to generate product images before sending them to the factory to confirm colors, expressions, and shapes. Others pay sampling fees first, receive the physical product, then open group-buying sessions on social media—starting with just 100 or 200 pieces.

Small orders do not necessarily mean short-lived business relationships. Traditional brand clients might order several thousand or even 10,000 pieces at once, but the next order could take a long time to arrive.

Shu Kai has a Xiaohongshu client selling bath towels. Each reorder is only 200–300 pieces, but the client returns every 10 to 15 days, and a single style can be replenished multiple times. A large order is thus broken into many small ones. The factory doesn't produce the full quantity on day one but follows real sales step by step.

This model has helped domestic cross-border platforms like Alibaba International Station, SHEIN, TEMU, and TikTok Shop go global, and it is also recognized by cross-border e-commerce supply chain companies.

A textile company executive in Shaoxing told Times Weekly that Amazon sellers they work with also want factories to accept "small order, fast response" because clients are afraid to stockpile. They produce a small batch first, and if it sells, they reorder. Some clients don't even want to hold inventory themselves, asking suppliers to handle drop-shipping.

High school students, Xiaohongshu sellers, and e-commerce platform merchants operate in different markets but follow the same logic: until demand is verified, no one wants to bet everything at once.

Rethinking the Inventory Equation

When buyers reduce first orders to dozens or hundreds of pieces, factories seem to inherit a more difficult inventory calculation.

For manufacturers, goods sitting in warehouses are a cost. By the end of 2025, finished goods inventory at China's industrial enterprises above a designated size reached 6.73 trillion yuan, up 3.9% year-on-year. The turnover days for finished goods stood at 19.9 days, an increase of 0.6 days from the end of the previous year.

"Small order, fast response" first tackles the inventory bottleneck across the entire chain.

Yan Qing recalls that Heting Outdoor initially outsourced laser cutting. After printing patterns in-house, the fabric was sent to external processors, often requiring a wait for scheduling. "The partner factory has other clients. You're in a hurry, so are they. There's always a queue." For a small order measured in days, a few extra days in queue could eat up the buffer time gained earlier.

To adapt, Yan brought laser cutting, embroidery, and label-ironing equipment in-house. Heting's warehouse now keeps a stock of undyed grey fabric. The fabric enters without patterns or confirmed colors. Only when an order is finalized does the fabric go through digital printing, heat transfer, laser cutting, and sewing to become a specific product.

Under normal conditions, a sample can be completed within 24 hours. For urgent orders, Yan can schedule production to deliver a sample in as little as six to seven hours. Small orders of 100–200 or 1,000 pieces are handled in-house whenever possible. Larger orders are directed to external capacity suited for mass production.

Times Weekly noted that many small factories are adopting Yan's approach. To reduce invisible time costs, they purchase equipment to maintain control over their schedules.

A textile executive in Shaoxing told Times Weekly that new clients typically request samples and test quality first. Once a stable合作关系 is established, they increase purchase volumes. Because the warehouse holds ample现货, the company can handle very small orders. "I can even sell one meter," the executive said. Clients select colors from swatches, and the fabric is cut to the exact length needed for a garment.

Under the "small order, fast response" model, the core inventory question shifts from "how much to stockpile" to "at which stage to hold inventory." And as orders move toward small batches and multiple runs, factories face another challenge: the pace of inventory management and production adjustment must accelerate.

At Yifan Daily Necessities, for example, the online product catalog includes hundreds of items. A sales staff member recalled that early inventory planning involved pulling store sales data every two weeks or even monthly, then cross-checking with warehouse stock. After integrating sales data with the ERP system, the team can monitor online sales and actual inventory more frequently, determining which products need replenishment and which should be controlled.

Reducing inventory at the brand level and increasing turnover at the manufacturing level both point to the same operational discipline. When the market offers no certainty, the supply chain should avoid one-time bets and leave room for multiple "course corrections."

In the world of small orders, warehouses, machines, and time are all placed on the same balance sheet.

A Single Order Orchestrates an Entire City

Shu Kai told Times Weekly that the hardest part of handling orders for dozens or hundreds of pieces is not taking the order—it's orchestration.

Sometimes, while a large order is in production, a client suddenly inserts a batch of customized items with a tighter deadline. Who has spare capacity? Who is willing to adjust their production schedule on short notice? These questions determine whether delivery dates can be met.

Factory buildings and equipment are fixed assets. A single factory has clear limits on how many machines it can house, how many product categories it can cover, and how much output it can achieve. No matter how precisely the internal accounts are calculated, the physical constraints of machines and space are an unavoidable wall.

A single factory can only control so many machines. But the industrial capacity of an entire city can be reconfigured to match orders. To address this capacity mismatch, Shu Kai has gradually developed a new cooperation mechanism with external suppliers.

He now concentrates similar orders with one or two core partner factories. Only when order volumes are stable enough will those partners make room for urgent or small orders. "If your order volume is large enough, you can negotiate anything. If it's small, you have to rely on goodwill." Shu makes it clear to his partners: big orders must be done, but small orders must be done too.

Wu Xianmin, founder of Duopin Daily Necessities, shares this understanding. When Wu first started his business in Yiwu, Duopin's warehouse was only about 50 square meters, and the team worked from a living room. Yet, when the company received an order for silicone dolls, from receiving the client's requirements to creating the mold and producing a sample, the entire process took just nine days.

According to Wu, if all processes were dedicated to a single order, the cycle could be compressed to about five days.

A company with a tiny warehouse can complete mold-making and sampling in days—not because it has a full set of equipment on-site, but because it relies on the specialized division of labor within the industrial cluster: someone makes molds, someone prints patterns, someone handles packaging, and someone manages warehousing and logistics.

This collaborative mechanism is not unique to Yiwu.

A textile company executive in Shaoxing's Keqiao district told Times Weekly that after a bolt of fabric is woven, it may need to go through several different processing factories for subsequent steps. The company's ERP system tracks not only warehouse inventory but also where fabric is sent from headquarters, which factory handles each process, and the sequence—potentially passing through factories A, B, and C before returning to the warehouse.

Division of labor within industrial clusters is nothing new. But in the past, it primarily served cost control for large orders. As small orders multiply, the same industrial infrastructure gives rise to a different kind of efficiency: orders can be quickly broken down, equipment can be temporarily reassigned, and capacity can be shifted between enterprises.

However, challenges remain under the new model. Shu Kai notes that external factories each have their own schedules and ways of working. Supply chain managers must closely monitor production progress and ensure goods move smoothly from one factory to the next.

The "flexibility" of the small-order, fast-response supply chain lies precisely in these gaps. It requires suppliers to adjust schedules for small orders, demands that someone track delivery dates as orders flow between different companies, depends on the industrial cluster retaining enough producers with diverse processes, and requires each company to know when to do things itself and when to pass orders on.

Shu Kai later calculated that instead of making daily phone calls to chase schedules, it was better to assign one person to oversee the entire network. He eventually put a dedicated person in charge of supply chain orchestration. He has become increasingly convinced that while a 10,000-piece order relies on a single large factory running continuous production, a 100-piece order may require an entire city to work in relay.

Conclusion

Large orders have not disappeared. They simply no longer monopolize every workshop. Small orders have not overthrown the old order. They have simply taught more factories how to keep their machines running amid uncertainty.

Disclaimer: The content above (including any images or videos) is uploaded and published by a user of the NetEase Hao self-media platform. This platform provides only information storage services.