Targeting a 300-trillion-yuan logistics market, how can costs be reduced?

A well‑connected, multi‑modal logistics network is injecting robust vitality into the real economy. By ensuring smooth “micro‑circulation” at the ends of industrial chains and keeping the economy’s “major arteries” flowing, the thriving logistics sector is accelerating the development of new‑type productive forces. Chinese logistics enterprises have largely reached a comparable level to those in developed Western countries in building intelligent logistics systems. However, significant room for improvement remains in areas such as basic components, original technological innovation, brand building, and enterprise scale.

▍To effectively reduce society-wide logistics costs

On February 23, General Secretary Xi Jinping likened logistics to the “lifeline” of the real economy at the fourth meeting of the Central Financial and Economic Commission. Xi emphasized the need to effectively reduce society-wide logistics costs, strengthen the core competitiveness of industries, and improve the efficiency of economic operations.

According to an analysis of logistics performance in 2023, the total social logistics volume nationwide reached RMB 352.4 trillion, up 5.2% year on year at comparable prices—a growth rate that was 1.8 percentage points higher than in 2022. This reflects not only quantitative expansion but also qualitative improvement. Smart logistics is a key tool for effectively reducing society-wide logistics costs; by leveraging advanced information, networking, and intelligent technologies, it enables visibility, predictability, and controllability throughout the logistics process. The integration of emerging technological solutions has propelled smart logistics onto a fast track of development.

Yin Junqi, Vice Chairman of the Logistics and Warehousing Machinery Branch of the China Heavy Machinery Association, stated that Chinese logistics enterprises are broadly on par with their Western counterparts in building intelligent logistics systems. However, significant room for improvement remains in areas such as basic components, original technological innovation, brand development, and enterprise scale. China’s logistics costs as a share of GDP have consistently remained high; last year, they fell for the first time from above 14.7% to a record low of 14.4%, yet they still lag considerably behind those of the United States and other advanced Western economies. Several factors contribute to this gap: first, manufacturing accounts for a relatively large share of China’s GDP; second, the value added of Chinese manufactured goods remains comparatively low. Given that external conditions cannot be altered, logistics companies have few fundamental avenues for reducing costs. Leveraging technology to enhance operational efficiency, optimize supply chains, and implement lean management practices are widely recognized as essential strategies.

Lin Guoqiang, Director of Big Data at SF Technology, stated that from a transportation perspective, costs can be reduced by optimizing route planning and lowering empty‑haul rates. From a warehousing standpoint, refining direct‑from‑origin shipping, consolidating multiple facilities into one, and streamlining cross‑category scheduling can enhance warehousing service capabilities while cutting expenses. From a management angle, SF leverages new technologies to implement granular, data‑driven operations. Effective data governance is the foundation of such refined management—so how does one manage the data across thousands of systems? After years of experience, SF has distilled a “three‑pronged” framework: defining strategy, structuring the organization, and setting clear objectives.

A typical passenger car comprises roughly 10,000 non‑removable, individual components, while more complex vehicles—such as Formula 1 race cars—can include as many as 20,000 distinct parts. According to Wang Zhou, Director of Logistics at SAIC‑GM‑Wuling, the company works with approximately 800 suppliers and maintains 2,800 sales and service outlets. By advancing smart logistics, the company has achieved annual cost savings exceeding RMB 100 million. In automotive manufacturing and delivery, logistics plays a pivotal role. Whether managing component supply chains or handling final vehicle deliveries, companies can cut costs and boost efficiency by devising well‑structured logistics plans, selecting the most economical transportation modes, and optimizing warehousing and distribution processes—thereby offering consumers more competitive pricing and strengthening overall competitiveness. Guided by the principle of “agile supply and seamless coordination between vehicles and materials,” SAIC‑GM‑Wuling has built a digital supply chain system that provides end‑to‑end visibility and enables rapid market responsiveness. According to Wang Zhou, on one hand, the company has established an integrated, end‑to‑end digital operations platform, linking strategic supplier inventories, in‑transit stock, and warehouse holdings into a unified, transparent data ecosystem. This allows real-time monitoring of physical inventory across the entire supply chain, resulting in a 30% optimization of overall inventory levels. On the other hand, SAIC‑GM‑Wuling has moved beyond traditional consumption‑driven pull‑based logistics, adopting dynamic collaborative manufacturing and precision demand‑driven pull strategies. Leveraging 5G, IoT, blockchain, and computer vision technologies, the company has pioneered unmanned material handling, achieving a 50% reduction in on‑site inventory.

SAIC-GM-Wuling has broken away from the traditional one‑item‑per‑location, fixed‑storage model, developing a unique flexible layout and dynamic warehousing system. Coupled with advanced intelligent equipment, it has also pioneered the implementation of CTU unmanned warehouses in the automotive industry. “The LIM factory logistics system deploys more than 40 CTU robots, with over 20,000 dynamically assigned storage locations, and material management at the bin level. Through intensive R&D, we have overcome key technical challenges—including automated depalletizing, weight‑based sensing, visual recognition, precise docking between CTUs and material cages, thermal analysis, and real‑time scheduling—resulting in a 145% increase in labor productivity, an 180% improvement in warehouse utilization, and a 50% reduction in overall operating costs,” said Wang Zhou.

In addition to internal logistics, external logistics is an indispensable component of end-to-end value-chain management, serving as the bridge that connects a company with its raw-material suppliers, component manufacturers, and sales outlets. Factories must procure components from dozens or even thousands of suppliers—how much should be ordered, and when will it arrive at the plant? When will new vehicles be delivered to retail dealerships? Addressing these questions requires the support of smart logistics, which optimizes planning, manufacturing, transportation, and other processes to achieve seamless integration across the entire supply chain.

▍China’s smart logistics systems are on par with those of developed countries.

The World Bank’s latest Global Logistics Performance Index Report for 2023 shows that China has advanced from 26th place in 2018 to 20th place in the overall ranking. In particular, China ranks within the top 10% globally in both logistics infrastructure and international freight capacity, reaching an internationally advanced level. Its infrastructure ranking now surpasses that of developed economies such as the United States and France, improving by six places since 2018; meanwhile, its international freight capacity has risen four spots compared with 2018. China’s shipping fleet has reached 250 million deadweight tons, up roughly 10% year on year. Yin Junqi noted that Chinese logistics enterprises are broadly on par with their Western counterparts in building intelligent logistics systems, and that the country’s logistics sector enjoys several distinct advantages. First, there is strong support from the national government and public authorities—every level, from the State Council and the National Development and Reform Commission to various ministries, attaches great importance to the industry. Second, the market is enormous: as early as 2014, China had already become the world’s largest single logistics market, with annual growth consistently exceeding 10%, accounting for approximately 40% of global demand. Finally, a surge of talent and capital has injected vibrant new energy into the sector.

Technologies such as the Internet of Things, artificial intelligence, and big data are being deployed at an accelerating pace, ushering in a golden era for the logistics industry. “On the supplier side, China boasts more than 100 logistics system integrators and thousands of equipment manufacturers and component suppliers. Each year, over 1,000 new logistics systems are commissioned—an unprecedented scale worldwide,” summarized Yin Junqi. Among system integrators, leading players include Beizhi Technology, Beijing Institute of Automation, Wuqiang Intelligent, KunChuan Intelligent, and LanJian Intelligent. In the equipment sector, Shanghai Jingxing, Nanjing Yinfei, Huzhou Dema, Suzhou Jinfeng, Shenyang Siasun, Hikvision, Huazhang Technology, Roboteck, and Suzhou Pucheng have all demonstrated strong performance. Meanwhile, Fuller Technology stands out in the software space.

Smart Logistics Industry Chain Integrator

However, China’s logistics industry as a whole remains unevenly developed, with a pronounced east–west disparity. In specific sectors, China has taken a leading position in building smart logistics systems across pharmaceuticals, tobacco, automotive, retail, apparel, and e‑commerce. In recent years, logistics system development among new‑energy vehicle manufacturers has also advanced rapidly, making them among the frontrunners in the country’s drive toward intelligent manufacturing logistics.

Smart logistics industry chain equipment supplier

“There is still considerable room for improvement in areas such as basic components, original technological innovation, brand building, and enterprise scale. Basic components like PLCs, electric motors and gear reducers, photoelectric switches, and barcode readers largely rely on imports; moreover, the core technologies and equipment used in logistics systems—such as stacker cranes, AGVs, sorters, KIVA robots, and shuttle cars—originate entirely from overseas,” said Yin Junqi. “Addressing issues such as severe overcapacity at the low end, intensifying price wars, heavy reliance on imported basic components, and a low level of standardization will require a substantial amount of time.”

Smart logistics industry chain software provider

▍Main Factors Constraining the Reduction of China’s Logistics Costs

Logistics costs have long been a key concern for both the industry and society. Data show that China’s logistics costs as a share of GDP have remained persistently high; last year, they fell for the first time from above 14.7% to a record low of 14.4%. Nevertheless, the gap compared with Western developed countries such as the United States remains substantial.

Yin Junqi stated that the reasons behind this gap can be attributed to several factors. First and foremost is the structure of the economy, which is one of the most significant contributors. In 2022, manufacturing accounted for 26.3% of China’s GDP, compared with just 10.3% in the United States, while the service sector represented 58.6% of China’s GDP versus 84.4% in the U.S. Given that logistics costs in manufacturing are three to ten times higher than those in the service sector, this industrial structure explains why China’s logistics expenses as a share of GDP remain relatively high.

Second, China’s manufacturing sector generates relatively low value added, with most firms positioned at the downstream end of the value chain. Coupled with the long distances involved in transporting bulk commodities, this has kept logistics costs persistently high. As logistics pricing is based on both cargo volume and distance, enhancing the quality and market price of manufactured goods is a key strategy for reducing relative logistics costs.

Third, transportation modes can be further optimized. Comparing several typical modes, we find that road transport is the most expensive but offers the greatest flexibility, while rail transport is relatively more cost‑effective and waterway transport is the least expensive. Increasing the share of rail and waterway logistics would help reduce overall logistics costs.

Fourth, enhancing technological capabilities remains the key to reducing logistics costs. Digitalization, intelligent technologies, and standardization will play a crucial role in lowering overall logistics expenses.

In addition, excessively high highway tolls, elevated fuel prices, and substantial tax burdens, coupled with a low level of logistics standardization, are among the key factors affecting logistics rates. Moreover, the uneven development of logistics technologies is another significant constraint on reducing China’s logistics costs. To address these issues—particularly through industrial restructuring, promoting high-end manufacturing, and lowering tolls, fuel costs, and taxes—relevant policies must be introduced to yield tangible results.

With highway tolls, fuel prices, and taxes all relatively high, do logistics companies simply pass these costs on to their customers? Not necessarily. Yin Junqi noted: “Years of intense competition and price wars have kept China’s logistics rates comparatively low—roughly only 20% to 25% of those in the United States—and many firms are operating at a loss. What we need to reduce is overall logistics costs, not engage in price wars. Price wars inflict severe damage on logistics companies.”

▍How Can Enterprises Reduce Logistics Costs?

Given that the external environment remains unchanged, logistics enterprises have few fundamental avenues for reducing costs. As Yin Junqi summarizes, “Leveraging technological tools to enhance operational efficiency, optimize supply chains, and implement lean management are universally recognized as essential strategies.” In practice, each company has its own unique characteristics; only by tailoring solutions to local conditions and devising effective measures can the desired outcomes be achieved. On the one hand, companies must fully recognize the transformative power of digitalization and intelligent technologies, boldly investing in and experimenting with new innovations. On the other hand, technology is not a panacea: even the most advanced systems require human oversight and management to deliver their full potential.

For logistics companies, transportation, warehousing, and management constitute the primary cost drivers. Transportation accounts for more than 50% of total logistics costs, warehousing makes up roughly 35%, while logistics management represents less than 15%. Take SF Express, a leading domestic logistics player well-known to consumers, as an example. Its network spans 208 countries and regions worldwide; it operates over 2,000 warehouses, 429 express‑and‑courier transit hubs, and employs more than 430,000 delivery personnel. The company boasts Asia’s largest air‑freight fleet and road‑transport fleet, operating 120 global routes with 23,200 flights, and maintains over 150,000 vehicle‑delivery routes within China. It serves more than 625 million individual customers and 1.9 million corporate clients. With such an extensive logistics network, how does SF Express achieve cost reduction and efficiency gains?

Lin Guoqiang, Director of Big Data at SF Technology, stated that from a transportation perspective, costs can be reduced by optimizing route planning and lowering the rate of empty‑haul trips. “Optimizing route planning is a highly effective cost‑reduction measure; it’s not only deployed internally at SF but also offered as a service to select clients.” From a warehousing standpoint, the “three optimizations” can enhance service capabilities: “By refining origin‑direct shipping, consolidating multiple facilities into one, and optimizing cross‑item scheduling, we can boost warehousing performance while cutting expenses.” From a management perspective, SF has invested heavily in digital and, in particular, granular management. “For example, we deploy specialized systems to monitor on‑site retained and exception items in real time, promptly alerting relevant personnel to address them. Additionally, SF has developed its own digital twin for transit hubs, improving throughput capacity and operational efficiency.”

According to reports, SF Express’s digital twin transit hub replicates the real-world environment at a 1:1 scale, achieving 99% fidelity—from the external landscape to the internal data.

Through its digital twin hub, SF Express can validate the effectiveness of sorting schedules, assess sorting throughput under varying parcel volumes, and evaluate the appropriateness of staffing and equipment allocations. Traditionally, verifying the feasibility of a single shift would take an entire day—time‑consuming, labor‑intensive, and costly. In contrast, the digital twin system enables iterative validation and optimization of thousands of sorting plans within a single day, delivering rapid feedback and continuous refinement to produce smoother, more efficient sorting workflows, thereby helping the company reduce costs and boost operational efficiency.

▍To effectively manage logistics data, we must adhere to the “Three Constants”

Digital twins that remain detached from business data—relying solely on abstract theories and models—are little more than empty rhetoric. Only by building upon existing business operations and custom‑integrating AI, algorithms, models, and related technologies can enterprises develop digital twins that are truly tailored to their unique needs. “SF Express operates thousands of distinct business systems and hundreds of business units, each with varying levels of data quality,” says Lin Guoqiang. “The biggest challenge we face is how to standardize data across these disparate systems and units so they can work in concert. Based on our experience over the years, it’s essential to get three key elements right: defining a clear strategy, establishing an appropriate organizational structure, and setting well‑aligned objectives.”

First, define the strategy. At the outset, it is essential to underscore the strategic significance of the data mid‑end and to articulate a precise definition of it. “The data mid‑end must feature connectivity, data accumulation, and on‑demand sharing,” said Lin Guoqiang. “It should efficiently bridge the data supply and consumption sides, continuously build up shared data capabilities, and enable secure, on‑demand data sharing—enhancing customer experience while maintaining robust risk controls—to support SF Express’s operations.”

Second, establish an organizational framework. This is a massive undertaking that cannot rely solely on a single IT department or a dedicated big-data team within the enterprise. According to Lin Guoqiang, the prerequisite for leveraging data is to develop robust data standards, which require close collaboration across all business lines and functional departments. To ensure smoother progress, SF Express has set up a Data Governance Committee that encompasses legislative, judicial, and enforcement roles. The legislative function involves formulating data standards and usage guidelines, while the judicial role entails oversight of data‑usage processes by the Information Security Department and data architects. The enforcement component comprises the data‑warehouse team, the data‑quality team, and the data‑services team, all working together to ensure the effective operation of the data governance framework.

Third, set clear objectives. Data standardization and data governance are merely processes; their ultimate goal is to support the enterprise’s high-quality development. “We must adopt a results-oriented approach, leverage quantitative metrics, engage with all key business lines, and establish specific performance indicators to achieve unified goals,” said Lin Guoqiang.

With robust data governance in place, the company’s drive for intelligent operations has gained solid confidence. According to its 2023 annual report, SF Holding recorded revenue of RMB 258.4 billion, up 33.4% year over year. In 2023, SF handled a total of 11.97 billion parcels. Behind this massive volume lies the intelligent planning of SF’s extensive logistics network.

SF Express has consistently leveraged cutting-edge technologies to build a “smart brain,” integrating artificial intelligence, operations research and optimization, and big data into its planning and dispatch processes, covering every stage from pickup and delivery to capacity planning and transit. This transformation has shifted traditional manual network design toward systematic, algorithm-driven intelligent planning. Even before a customer places an order, SF Express proactively forecasts upcoming business volumes—such as the parcel volume for Beijing next week, tomorrow, or even for a specific shift—and accordingly schedules couriers, vehicles, and other resources while streamlining operations at transit hubs.

Once a customer places an official order, SF Express determines the specific vehicle or flight, as well as the delivery courier, based on factors such as time‑sensitive requirements and service expectations. Throughout this process, SF also dynamically forecasts the estimated arrival time for each shipment; if potential delays are detected, it promptly adjusts arrangements to ensure timely delivery. From pre‑shipment forecasting to in‑transit monitoring, with real‑time route optimization for billions of parcels every day, the company strives to balance resource allocation across time and space while achieving the optimal trade‑off between speed and cost.

Leveraging intelligent algorithms to drive business operations is a key component of SF Express’s smart‑city initiatives. In the realm of internal knowledge management, SF has built a unified enterprise‑wide Q&A platform powered by large language models. For delivery couriers, this eliminates the need to memorize operational procedures and spares them the frustration of sifting through and deciphering vast volumes of process guidelines when confronted with complex pickup and delivery standards or unexpected handling issues. The AI‑driven “Xiao Ge Service Center” enables instant, on‑demand responses, providing SF couriers with fast, accurate, and easy‑to‑understand comprehensive information and support.

Moreover, unlike consumer‑facing scenarios, Q&A in the logistics domain involves handling standards for pickup and delivery, shipping rates, and collection‑delivery operations, making the accuracy of system‑level information understanding and integration especially critical. At the same time, large language models must precisely extract key details such as origin, destination, and the nature of the consignment, and automatically invoke the relevant APIs. Consequently, the platform must not only respond quickly and comprehensively but also with high precision to be genuinely adopted by delivery personnel. In addition, by participating in national hub‑building initiatives, SF Express has long been committed to helping reduce overall logistics costs across society. Centered on Ezhou Huahu Airport, SF is developing a route network that “covers the entire country and radiates globally,” aiming to transform the Ezhou hub into a global supply‑chain center and a high‑end processing and distribution hub. As of the end of October 2023, SF had launched 44 domestic cargo routes and 10 international routes from Ezhou, with nearly 90 daily cargo flights operating at the airport.

(China Informationization Weekly)