What are the applications of industrial big data?

The application of industrial big data is mainly reflected in the following three aspects:

1. Data-based product value mining: create new value through secondary mining of products and related data.

2. Improving service-oriented production: Improving service-oriented production refers to using industrial big data to increase the value proportion of services in production (products).

3. Mainly reflected in two directions: First, it extends forward. For example, in the pre-sales stage, users are attracted, guided and locked by participating in product design or customizing products, and then the collected data is used for product production or research and development; The second is backward extension, which establishes the interaction between customers and manufacturers by selling products and generates lasting value, such as improving and innovating products or services by collecting data such as user feedback and evaluation.

4. Innovative business model: mainly reflected in two aspects: First, based on industrial big data, it is clear what innovative business services industrial enterprises can provide to the outside world; Second, in the context of industrial big data, it is clear what new business services industrial enterprises can accept. The best situation is to gain more customers, explore more blue ocean markets and gain more profits by providing innovative business models; At the same time, by accepting innovative industrial services, production costs and operational risks are reduced.

5. Analysis and optimization of industrial supply chain: At present, big data analysis has become an important means for many e-commerce companies to enhance the competitiveness of supply chain. For example, JD.COM Mall, an e-commerce company, uses big data to analyze and predict the demand of goods in various places in advance, thus improving the efficiency of distribution and warehousing and ensuring the customer experience of the next day's arrival.

6. Product sales forecast and demand management: analyze the current demand changes and combination forms through big data. Big data is a good sales analysis tool. Through the multi-dimensional combination of historical data, we can see the proportion and change of regional demand, the market popularity of product categories, the most common combination forms and the level of consumers, so as to adjust product strategies and distribution strategies.