What will smart logistics look like in the future? Jack Ma: All today’s couriers will be laid off!
In just 6 days, the four major domestic e-commerce platforms, Alibaba, JD.com, Suning, and Vipshop, announced their major logistics moves and the implementation of related concepts and technologies. With the advent of major changes, the most eye-catching one is naturally the JD.com Group, which is known for its "Why don't you go to the sky?"
1JD.com enters the aerospace logistics industry
On May 22, JD.com Group and Xi'an Aerospace Base signed a cooperation agreement on JD.com Global Logistics Headquarters, JD.com Unmanned System Industry Center, and JD.com Cloud Operation Center, which will build JD.com Group's largest comprehensive smart logistics industry base in the country.
According to the agreement, JD.com plans to invest 20.5 billion yuan in five years to carry out in-depth cooperation with the Xi'an Aerospace Base and jointly carry out the "334" project. The so-called "334" project refers to the construction of "three headquarters, three platforms, and four major industries"
Project 334
By the end of this year, the two parties will complete the establishment of JD.com's unmanned system R&D team and gradually carry out the construction of JD.com's integrated testing system for "drones, unmanned vehicles, and unmanned warehouses". In addition, JD.com will also register and establish a wholly-owned subsidiary at the aerospace base for the management, operation and investment of the unmanned system technology R&D team, and build an industrial-grade drone R&D and production base, including the entire industry chain of R&D and production, assembly and debugging, testing and maintenance, delivery and operation, control management, and data analysis.
At the same time, Xi'an Aerospace Base will provide hardware support for the development of JD's unmanned system technology, including a 5-kilometer "pipeline" airspace, a 1,500-square-meter professional drone R&D and manufacturing plant, and a 200-acre test flight field for JD's drone R&D, manufacturing, test flights and testing. The two parties will also use Xi'an Aerospace Base as a carrier to build a JD Town Demonstration Zone - Aerospace Town, and innovate the industrial development model of "general aviation airport + smart logistics + technological innovation + trade and tourism".
As the world's first company to propose using drones to build a short-distance air logistics network, JD.com is beginning to turn a series of visions into reality.
2Ali Cainiao launches ACE plan
An interesting coincidence is that when JD.com and Xi’an Aerospace Base signed a strategic agreement, JD.com’s old rival Alibaba also announced related logistics strategies and plans on the same day.
At the 2017 Global Smart Logistics Summit that day, Cainiao Network released a future green smart logistics vehicle plan code-named "ACE", and will work with SAIC, Dongfeng, Ruiqi and other automakers to build one million new smart logistics vehicles.
Cainiao ACE plan also launched products such as "vehicle design and manufacturing", "shared transportation capacity" and "industry solutions". The goal of the plan is to build 1 million new energy logistics vehicles equipped with "Cainiao smart brain".
The "Cainiao Smart Brain" system can generate the optimal delivery route in real time based on order dynamics, and can also dynamically adjust the interface based on business and road scenarios, realize voice interaction with drivers, and achieve smart logistics delivery. Ultimately, "connecting lines into a surface" will create a mobile green smart logistics backbone network.
Shi Han, the person in charge of the Cainiao ACE program, revealed that the new vehicles developed by the "ACE" program were piloted in Shenzhen and Chengdu in April . Taking Shenzhen as an example, the distance traveled by a single vehicle was reduced by about 30%, the empty driving rate was reduced by 10%, and the cost was saved by more than 20%. Based on this calculation, the launch of the Cainiao ACE program can save 10 billion yuan in costs for the logistics industry in one year.
As always, Jack Ma spoke eloquently at the summit that day.
Jack Ma warned that China will soon face the challenge of 1 billion packages a day, which will have a huge impact on the express delivery and logistics industry that was unimaginable in the past decade.
" Many of the couriers we have managed to organize today may lose their jobs because of robots, driverless cars, and drone delivery, which is a relatively good concept today. "
Jack Ma believes that the future competition in logistics will be about technology and people's service capabilities. Only in this way can we gain market share and profits from the future 1 billion packages.
" Your organization is not ready. In the past six months, I have paid close attention to the express logistics industry. I found that the vast majority of logistics companies are not ready in terms of organization, talent, information technology, and vision. And you will definitely be eliminated. "
When Jack Ma made this statement, those listening in the audience included Chen Dejun, Chairman of STO Express, Yu Weijiao, Chairman of YTO Express, Lai Meisong, Chairman of ZTO Express, Nie Tengyun, Chairman of Yunda Express, and Zhou Shaoning, Chairman of Best Logistics.
3. Application Outlook of Smart Logistics in 2025
If we compare the logistics moves of Alibaba and JD.com on May 22, we will find an amazing pattern: JD.com and Alibaba are on the same path, these two companies that were once known for their channels have transformed into technology-driven companies. Of course, Jack Ma may not know that while he was still talking about the concept, the low-key Liu Qiangdong took the lead in making a vigorous layout.
Based on the best practices of leading companies and the development trends of the logistics industry , the China Federation of Logistics and Purchasing forecasts the application scenarios of China's smart logistics from now to 2025, and outlines the framework and main contents of smart logistics applications.
The overall architecture is reflected in three levels from top to bottom: smart platform, digital operation, and intelligent operation. Figuratively speaking, if smart logistics is regarded as a "person", the smart platform is the "brain", digital operation is the "center", and intelligent operation is the "limbs".
China Smart Logistics 2025 Application Outlook Framework
The "brain" is responsible for open integration, sharing and collaboration. It conducts overall strategic planning and decision-making by integrating market relations, business models, technological innovation and other factors, outputs industry solutions, and coordinates all participants.
The "hub" is responsible for serial dispatching, relying on cloud-based information systems and intelligent algorithms to connect and dispatch all participants to work together;
The "four limbs" are responsible for the execution of operations, relying on interconnected and autonomously controlled intelligent facilities and equipment to achieve high efficiency and low cost in logistics operations.
Intelligent platform
As the number of commodity trading categories increases, the requirements for logistics delivery timeliness become higher and higher, and the scope of logistics services becomes wider and wider, the logistics network layout and the coordination of upstream and downstream supply chains face huge challenges. This urgently requires relying on intelligent platforms and realizing upstream and downstream coordination and win-win results through data-driven intelligent network layout .
Data-driven, intelligent layout
Network layout is a multi-objective decision-making problem that requires taking into account indicators such as coverage, inventory costs, operating costs, and delivery time. In the future, we will have the ability to use big data and simulation technologies to study and determine how to achieve the optimal warehousing, transportation, and distribution network layout. Based on the modeling analysis, solution, and simulation operation of historical operating data and forecast data, we will more scientifically and reasonably determine the inventory deployment of each type of goods, as well as the location and production capacity of each sorting center and distribution station, and a series of related issues.
Take the intelligent construction/dismantling of stations in the distribution network as an example: by constructing multi-dimensional models such as comprehensive evaluation model, cost optimization model, minimum number of stations model, etc., based on input parameters such as order quantity, road area coordinates, and constraints such as station transmission time and delivery radius, intelligent algorithms such as genetic algorithms are used to solve the problem, and obtain planning decisions such as the optimal number of stations, coordinates of each station, and average delivery radius.
Big Data Network Layout Example - Intelligent Site Building/Teardown
Open collaboration, value-added and win-win
One of the goals of smart logistics is to reduce costs and increase efficiency, but the current coordination costs of all parties in the logistics industry are still too high. In the future, we will unify industry standards, share basic data, and gain insights into the logistics operation rules of various industries and links based on big data analysis, form best practices, and clarify the most suitable roles for each participant in the smart logistics system.
On this basis, upstream and downstream parties share information at the sales planning and forecasting levels, guide the operation of various links such as production and logistics, and achieve deep coordination of the supply chain.
Industry insights and deep supply chain collaboration
Digital Operations
Logistics needs are becoming more diversified and personalized. In the future, digital technology will be used to make dynamic decisions based on real-time needs in the entire business process of warehousing, transportation, and distribution horizontally, and in the entire operation process of decision-making, planning, execution, monitoring, and feedback vertically. Autonomous management will be carried out based on operating rules with self-learning and adaptive capabilities, and these decisions will be implemented in information systems.
Dynamic decision-making, autonomous management
It is mainly reflected in two aspects: full-link intelligent production scheduling and intelligent setting of operation rules.
(1) Full-link intelligent production scheduling . Future production scheduling will be a dynamic optimization that integrates all links of the full-link, including warehousing, transportation, and distribution. A capacity model is built based on operation plans, customer needs, load monitoring, resource capabilities, etc., and solved through a production scheduling algorithm. The bottleneck links are dynamically identified, and the capacity thresholds of each link are intelligently calculated and updated. The production rhythm of each link is dynamically arranged to achieve smooth production in each link. By setting a moderate backlog safety buffer, the pressure of peaks and valleys can be reduced, saving costs.
Full-link intelligent production scheduling
Take the intelligent scheduling of order production and loading sequence as an example: based on the real-time positioning application, according to vehicle information (including the estimated time of arrival at the warehouse/sorting center, vehicle specifications, etc.), as well as the address and delivery time information of the actual order, the dynamic cut-off time is intelligently set, the order production sequence and the order collection and picking sequence are arranged according to waves, and the loading sequence is reversed according to the package delivery order.
Intelligent arrangement of order production and loading sequence
(2) Intelligent setting of operation rules . Logistics needs will become more scenario-based and refined. In order to meet various needs, it is necessary to refine the operation rules item by item, model the conditions and triggering operations of logistics timeliness, freight, last mile and other businesses, verify them through simulation, and configure them in the rule engine to drive various businesses to operate according to the rules. In the future, through machine learning, the rule engine will have the ability of self-learning and self-adaptation, and be able to make autonomous decisions after sensing business conditions.
Take the e-commerce B2C logistics operation rules as an example: online shopping has two scenarios: peak (such as 618, Double 11 promotion) and normal. Due to the huge difference in order size, the corresponding order production methods, delivery time, freight, abnormal order processing and other rules vary greatly. The future rule engine will be able to automatically sense time, product category and other conditions, and independently set the optimal operation rules for each type of order.
Intelligent setting of operation rules
Soft and flexible, intelligent scheduling
In the future, operations in various links such as warehousing, transportation, and distribution will rely on SAAS information systems, and achieve dynamic and real-time scheduling through componentized business applications and intelligent algorithm services.
(1) Warehousing . Based on basic data such as warehouses, commodities, orders, and waves, intelligent scheduling of various operations in the warehousing, storage, retrieval, picking, packaging, outbound delivery, and inventory will be realized in the future.
Take intelligent consumables recommendation as an example: in order to make better use of the space in the packaging box, when the goods are packed according to the order, by measuring the volume data and packaging box dimensions of millions of SKU products and using deep learning algorithm technology, the system intelligently calculates and recommends consumables and packaging sorting, thereby reasonably arranging the box type and product placement plan.
Digital Operations-Warehousing
(2) Transportation and distribution . Based on basic data such as vehicles, sorting, distribution stations, and waves, intelligent scheduling of various operations in the transportation, sorting, and delivery links will be realized in the future.
Take intelligent route recommendation and dynamic sorting as an example: in the transportation process, based on information such as product type, cargo weight and volume, merchant address, and destination address, the system uses historical data and intelligent algorithms to match door-to-door pickup vehicles of corresponding specifications and generate a transportation route.
Moreover, the system can dynamically adjust the route in real time according to the actual situation. When there is a delay in reaching the transfer station, the system automatically recommends a new subsequent route. In the distribution process, according to the production capacity and load of each sorting center, the system dynamically adjusts the road area covered by the sorting center to make the load of each sorting center more balanced, avoiding uneven busy and idle time, which affects the delivery time of some orders.
Digital Operations-Transportation and Distribution
Intelligent operation
The core of intelligent operation is to rely on a series of interconnected and autonomously controlled intelligent facilities and equipment, and realize the intelligent execution of various operations in warehousing, transportation and distribution under the intelligent scheduling of business operation systems such as WMS, WCS and TMS.
Under the premise of meeting customer needs, realize high efficiency and low cost in logistics operations. Since the attributes of goods vary greatly, logistics companies should choose the most suitable intelligent operation implementation method based on their own actual situation .
At present, the density of logistics robots in China is less than 1 per 10,000 people . With the implementation of the Made in China 2025 strategy and the national robot industry development plan, and with reference to the development and outlook of European logistics robots, China's logistics intelligent operation system will be more widely used. By 2025, we predict that the density of logistics robots will reach about 5 per 10,000 people , which is expected to save 20-40% of logistics operation costs.
Real-time interaction, autonomous control
Warehousing operations have been developing at the automation level for many years. In the future, we need to improve the level of intelligence, design different operation processes according to the attributes of the product, such as the type, weight, sales volume, and delivery time, and use matching logistics intelligent systems to implement them. In the future intelligent warehouses, robots, AGVs and other equipment are interconnected and have the ability to autonomously control, self-learn, and adapt to new rules, as well as higher flexibility and stability.
Take the storage and picking process as an example: Goods-to-person picking based on multi-layer shuttle technology has been realized, and in the future, the goods-to-robot picking method with higher picking efficiency and the robot picking method that integrates picking and picking will be applied .
Intelligent Operation-Warehousing
Real-time positioning, dynamic delivery
Assisted driving, convoy transportation, automated and robotic sorting, and smart terminals have been applied in the transportation, sorting, and delivery links. With the fragmentation of shopping scenarios and the dynamic nature of delivery locations, in the future, while achieving unmanned operations, delivery will be achieved at a dynamic node in the consumer's daily life based on real-time positioning applications, perfectly integrating with the consumer's work and life.
Take mobile delivery as an example: after a consumer places an order at home, the system obtains the consumer’s geographic location in real time while on the road, and delivers the package to the consumer at a suitable location by an unmanned delivery vehicle or a mobile pickup cabinet.
Intelligent Operation-Transportation and Distribution
Conclusion
Unmanned delivery vehicles plan routes, avoid pedestrians, go up and down stairs, and scan faces to receive goods. Drones travel across mountains and rivers to deliver goods to remote rural areas, which means that they can enjoy the same shopping experience as consumers in the city. This is the future of smart logistics!