The most popular digital transformation in China's

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The development potential of digital transformation in China's Pan industrial sector is huge

data show that the scale of China's digital economy will reach 39.2 trillion yuan in 2020, accounting for 38.6% of GDP; The growth rate of digital economy has reached more than three times that of GDP, which has become a key driving force for stable economic growth. Data show that in 2020, the digital economy will further develop. The scale of China's digital economy has accounted for nearly 40% of GDP and contributed nearly 70% to GDP. It is expected to further increase to 4.756 billion yuan in 2021. In this context, digital transformation has become the top priority of the development of major industries. In this process, what role does data intelligence and industrial interconnection play? What specific challenges and opportunities will you encounter? What is the future development potential of the digital economy

2021 will be the first year of the digital intelligence era

China's digital economy has great potential for development. First of all, China's current digital economy accounts for a large proportion of non-standard GDP that avoids manual readings and records compared with advanced countries in Europe and the United States. At present, we are 36% to 40%, while the United Kingdom, Germany, the United States and other European and American countries have reached 60%. Secondly, in the composition of China's GDP, the financial and export unit prices are improving the digitalization of it and retail industries. The retail industry accounts for about 2% of GDP, but giants such as Alibaba and have emerged. However, pan industry accounts for 52% of GDP, which is still in the early stage of realizing digital transformation. It can be seen that there is a huge space for the development of digital economy

Accenture's 2020 China enterprise digital transformation index study shows that 85% of the executives interviewed said they hoped to see the effect of digital transformation within one year, and 43% of the enterprises hoped to see the effect of digital transformation within six months. According to the requirements of customers, we will introduce a survey conducted by IDC for China's top 1000 enterprises two years ago, which shows that more than 50% of enterprises say that digital transformation is their important strategy. It can be seen that the whole market has a good understanding of digital transformation

SASAC issued the notice on accelerating the digital transformation of state-owned enterprises in 2020, specifically encouraging central and state-owned enterprises to take the lead in digital transformation. The Ministry of industry and information technology also issued the "industrial interconnection innovation and development action plan (2021 2023)" in January this year, requiring all enterprises to strengthen the construction of industrial interconnection, especially the digital management

therefore, from the perspective of market and policy, 2021 will be the first year of the digital intelligence era

industrial interconnection construction from digitalization to digital intelligence

digitalization transformation mainly includes two parts. The first is business digitalization. That is to say, extract the data from the business, and then analyze it through the integration of data, so as to have an insight into the whole business. The digitalization of business should be done through industrial interconnection. The second is digital business. This requires the help of data intelligence technology. Data intelligence refers to the integration of artificial intelligence and big data, that is, using big data to make the algorithm model and application scope of artificial intelligence better. First of all, the extracted data should be built into a model, followed by simulation, prediction and optimization, so that decision makers can make more accurate, better and more forward decisions through the data

as a tool, industrial interconnection plays a vital role in digital transformation. We have found and focused on the five challenges of industrial interconnection in practice

the first is the expansion of data dimension. Digital transformation requires the integration of data from different data sources to open up data islands. This requires unified analysis and modeling of data

the second is that it is more and more widely used. The original AI is basically face recognition, speech processing, human-computer dialogue of language, etc., which are almost to C's businesses. Now we see more applications of artificial intelligence in the field of to B. the scope of this application is much larger, and there are many more scenarios, involving all walks of life

third, the application depth of artificial intelligence has increased. In addition to face recognition, speech recognition and other cognitive services, AI also needs to carry out prediction and early warning, which requires more in-depth analysis of data and consideration and analysis of all historical data

the fourth is global optimization. It turns out that you see more local optimization. It is applied to a process point, a process, and a small scene. For enterprises, it is more important to optimize the overall situation. We should coordinate the operation of the iron triangle of supply, production and marketing to better improve the operating efficiency of enterprises

the fifth is the systematization of intelligence. This digital intelligence system is mainly used for decision makers to make auxiliary decisions. It is equivalent to equipping decision-makers with a brain to truly be an enterprise brain, and this enterprise brain should not only be able to manage all departments, businesses and processes of the enterprise, but also do a good job of upstream and downstream coordination and be able to flexibly deal with peripheral markets

industrial interconnection enterprises should find the right position according to their own characteristics

in the blue ocean of industrial interconnection, many start-ups continue to emerge. In just threeorfour years, hundreds of start-ups have emerged. There are more than 100 platform level industrial interconnection enterprises with strong industrial and regional influence, and these more than 100 enterprises have connected 70million devices, and another 590000 industrial apps have appeared. In such a short period of time, it is a good phenomenon that industrial interconnection has been popularized so widely

but just because it is in a big sea, we should pay special attention not to lose our way. Every start-up enterprise should find the right position according to its own characteristics


this field is a bit like artificial intelligence, that is, all technologies actually have certain troughs. Artificial intelligence has appeared for two winters in the past 60 years, and the field of industrial interconnection also needs the patience of investors. Industrial interconnection is a good track, but there is a long way to go

in industrial enterprises, all changes need patience, and products should be polished carefully. To C can spread instantly through market effect, but to B needs to do its own work carefully in the industry

at the same time, we should also recognize that the construction of industrial interconnection will produce massive data. On the one hand, these data need high-quality data governance; On the other hand, data security and privacy is a very important issue. From a legal point of view, some European and American countries have special laws and regulations, and China also has the data security law (Draft). These laws and regulations will play a good role in data security and privacy protection

(Liu Zhen, academician of IEEE and chairman of Aolin Technology)

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