Big Data Driven Shoe Enterprises Pformation And Upgrading, Tap The Potential Of Domestic Demand, Create Personalized Customization

China is the largest shoe producing country and exporter in the world.

In recent years, China has produced over 10 billion pairs of shoes each year, accounting for 66% of the total global shoe making industry, and is the largest in the world.

Manufacturing base is also the largest footwear exporter in the world.

In recent years, the domestic footwear industry has encountered many challenges. According to DDT's research report, in the past 10 years, China's labor cost has increased 5 times to the United States, coupled with the exacerbation of environmental problems, resulting in the rising price of raw materials.

According to the world clothing shoes and hats net,

The IHS Markit study by the survey firm showed that the proportion of China's low cost labour force's destination fell to below 50% for the first time in 2016.

The famous international brands such as Adidas, Puma, CONVERSE and Reebok have pferred more and more orders to Southeast Asia and Africa. China's export oriented OEM plant has been in the predicament of overcapacity.

And other famous international brands have pferred more and more orders to Southeast Asia and Africa. China's export oriented OEM plant has been in the predicament of overcapacity.

Tap the potential of domestic demand and create personalized customization

The excess capacity is accompanied by high inventory. As China's footwear industry always regards OEM as the main way of profit, it leads to the lack of independent innovation capability and the serious homogenization of products. The profit structure of single point single product business has changed. With the further development of flat channel, the profit margins will be smaller and smaller. These problems require shoe enterprises to solve them through pformation and upgrading.

At present, with the gradual increase of the national consumption level, consumers' demand for products is more and more diversified. This makes it difficult for Chinese shoe companies that have long been accustomed to the traditional mode of large-scale industrial production to adapt to the situation. The products can not meet the needs of consumers, which is accompanied by a backlog of inventory. Many shoe enterprises are also suffering from the pressure of capital chain breaking in this process.

Consumers and enterprises are being rebuilt, and shoe companies should make corresponding changes and adjustments according to the current market demand in pursuit of new development directions.

At present, many shoe enterprises have grasped the preferences of consumers for diversification, personalization and fashion, and launched related customized business. The chairman of the Putian Footwear Association has changed the shoe brand to a personalized factory. Users can choose shoes in the store and choose shoes, colors, embroidery patterns and patterns according to their own preferences. The customized system will respond to the production system quickly according to the choice of users, and users will be able to get the finished products in about twenty minutes.

The general manager of personalized customization project, general manager of the double smart general manager, said at the recent sixth (2017) China Footwear Industry Development Summit Forum: "nowadays, consumers' demands for shoes are more and more diversified. Continuing to produce in traditional ways will only create a backlog of inventory, which is not conducive to the long-term development of shoe enterprises. We build customized systems to allow users to participate fully in the production process of shoes, so that users can feel the ability of comfort and quality of shoemaking technology more intuitively."

Big data driven shoe enterprises pformation and upgrading

In addition to catering to the needs of consumers and launching corresponding customized business and products, shoe manufacturers themselves must speed up the process of informatization, industrialization and service.

Under the background of industrial 4, shoe companies also need to follow the trend and speed up the information process of the whole industry chain, that is, intelligent pformation of production processes, flexible production and rapid response, all of which are inseparable from the application of big data.

Jinjiang's well-known shoe companies, 361 degrees, have jointly established a "big data innovation laboratory" with Baidu to jointly study and manage users' real data, and develop and produce digital products based on user needs.

In addition to smart children's shoes, other intelligent products will also be launched. The research and development of this series of intelligent products will be based on the grasping of user needs behind the big data and the identification of user life forms.

361 degrees president Ding Wu said: "in the context of the impact and change of the Internet on traditional enterprises, the reshaping and pformation of traditional enterprises are becoming more and more urgent. User centered product R & D and service oriented user thinking will be a new business mode."

The double foot enterprise and the Chinese Academy of Sciences jointly build the foot type big data and shoe industry personalized customization research center. The joint research and development foot scanning equipment, based on the machine vision three-dimensional foot parameter measurement and reconstruction technology and the flexible pressure sensing technology, integrates the three-dimensional foot type measurement and the plantar pressure distribution measurement in an integral whole, can comprehensively and accurately measure and analyze the foot's three-dimensional morphological characteristic parameter and the foot pressure distribution characteristic, provides the foot type data for the foot long foot, the foot width, the foot long, the foot arch and so on, and uploads the data to the "Chinese foot type database" in real time, recommends the most suitable footwear to the user through the big data analysis.

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