Gome, which had been dormant for many years, started the "revival" plan with the return of the helm, and launched the new strategy of "self-management + joint operation" omni-channel supply chain: the plan is to exceed 500,000 SKUs in 18 months, strive to form a scale of 200 billion, and build a scale of one trillion supply chain system in the next five years. Relative to the target, how to meet the daily needs of millions of consumers, how to quickly deliver millions of goods to buyers, is the biggest test for Gome and brand manufacturers supply chain.
According to the data of China Internet Network Information Center CNNIC Prospective Industry Research Institute, the online retail consumption from January to September in 2020 reached 8006.5 billion yuan, with a year-on-year growth of 9.7%, which further highlights the unique advantages of the online retail market. With the successful application of a series of emerging technologies such as big data, artificial intelligence and cloud computing in the retail industry, as well as the transformation of users' consumption patterns catalyzed by the epidemic, the sales channels of commodities have been fully expanded, and the relationship among consumers, commodities and trading places has been reshaped, bringing a new pattern to the retail industry. Many leading retail enterprises began to try to use innovative technologies to improve user experience and corporate efficiency. For example, Holliyou, a well-known candy brand, used artificial intelligence decision optimization technology to solve the problem that the supply chain could not timely meet the demand of orders during the epidemic.
In today's increasingly perfect social network, the new retail industry will usher in the supply chain maturity, innovation and other aspects of competition, the competition between retail enterprises has gradually evolved into the supply chain competition.
Digital supply chain will become the main battlefield of enterprise market competition
With the deepening of digital consumption structure, although it has been the consensus of domestic retail enterprises to build digital supply chain, there are still many problems on the road of transformation:
It is difficult to predict user demand: with the rise of "new retail", consumers are increasingly demanding on the appearance, quality and experience of goods, and the types of SKUs also increase and the life cycle of products becomes shorter. Meanwhile, the reduction of tolerance for stock shortage has become the "new normal" of retail. How to accurately predict market demand and create "popular" goods for retail enterprises becomes the "shortcut" for enterprises to further expand market share;
Poor agility of supply chain: In the digital era, consumers have increasingly prominent requirements for "timeliness" of commodities. This "timeliness demand" requires the layout of retail stores to be infinitely close to consumers, which makes the layout of supply chain network of enterprises, especially the layout of warehouses, more difficult.
The upstream and downstream collaboration cycle is long: retail enterprises, especially large traditional retail enterprises, do not have the visibility of dealer and store data, and data from different channels and different regions within many enterprises have not been completed yet, so the overall collaboration cannot be achieved.
It can be seen that digital technology has great value and advantages in business scenarios with complex structure, and supply chain will become one of the most important scenarios for the application of digital technology, and will also be the key battlefield of industrial competition in the next stage, and its importance in enterprise operation and strategic system will be increased rapidly.
From demand to supply, decision optimization accelerates the digitalization of enterprise supply chain
Based on the above business difficulties, the application of cutting-edge technology, combined with information system and big data, to create a digital supply chain and precision marketing system, open up the whole chain of forecasting, replenishment, inventory, pricing, marketing, sales and logistics, so that retail enterprises can cope with the increasing uncertainty of the consumer market, improve the agility from supply to sales. Business to achieve sustained high growth key.
I. Multi-level demand forecast to realize the integration of product and effect -- In the face of hundreds of thousands of SKU products, unreasonable structure or invalid products occupy limited display resources, will cause the challenge of low product efficiency on the platform, so it is particularly important to investigate, analyze and optimize the SKU promotion situation. At present, some e-commerce flagship stores of daily chemical brands have used mathematical planning solver as the technology engine (the domestic representative manufacturer Shansu Technology) to establish the demand prediction algorithm model, combine the internal and external data of enterprises, mine the commodity attribute relationship, combine and customized high-dimensional data features. To achieve the demand forecast covering daily/week/month, SKU/ category/brand, national/online/offline /KA and other levels, so as to achieve the purpose of attracting consumers as the orientation and increasing the gross merchandise volume (GMV).
Second, from production to inventory, to achieve a balance between supply and demand -- as people's consumption habits shift online, the range and channels of choice expand, and consumers' demand for fresh and other products that are not easy to keep and transport increases significantly. In this regard, retail enterprises can use decision optimization technology to design differentiated safety inventory model and replenishment strategy model according to product characteristics and actual sales situation: Taking into account the performance of indicators such as service level and turnover efficiency, realize intelligent multi-level inventory planning management, and generate daily replenishment and allocation plans for stock shortage, overstock and sales fluctuations in warehouse/stores to achieve sensitive execution level optimization, thus reducing product loss costs and improving customer stickiness.
Iii. Build intelligent transportation to achieve cost reduction and efficiency increase -- Considering various business constraints, retail enterprises want to realize the overall planning of all resources, reduce transportation costs as much as possible, improve resource utilization rate and business response speed, so it is essential to build flexible and efficient intelligent transportation platform. Through the intelligent transportation platform, retail enterprises can quickly respond to the needs of various customer types in various transportation scenarios, such as order classification, vehicle matching, location analysis, rate optimization, etc. At present, intelligent decision optimization companies in China have successfully helped a number of logistics head enterprises to deploy intelligent transportation platforms through the datalization, standardization and transparency of transportation scheduling links, and solved problems such as high transportation costs and traditional manual scheduling. For example, Shanshu Technology helps a large cold chain logistics to deliver food and beverage in the same city, reducing the average daily number of vehicles by 5.8%, saving 7% of the average driving distance, and reducing the daily dispatch time from 4 hours to 30 minutes, greatly improving transportation efficiency and reducing operating costs.
With the rise of new sales models such as community group buying and live streaming, retailers and retail enterprises like Gome are also facing huge challenges in supply chain management while vigorously developing the sinking market to meet more customer demands. At present, intelligent decision-making technology has a large number of leading cases in the decision-making aspects of enterprise supply chain planning, production planning, transportation optimization and other business scenarios, and has become one of the important technical means to build unique competitive advantages in the industry.
