Making China’s Industries Smarter, Faster

The greatest impact on the global value chain was felt in Mainland China, where nearly 30 percent of global manufacturing output originates. This sent China’s economy into a nose dive, resulting in a record contraction in output of 34 percent in the first quarter of 2020, according to World Bank figures.To get more news about chinese industry and management practice, you can visit acem.sjtu.edu.cn official website.

While second quarter growth of 3.2 percent signals a rebound for China, manufacturing enterprises are aware that a return to "business as usual” is not an option. They need to address issues that will make them vulnerable to the next potential supply chain disruption.

If the benefits of digitalization were not clear to c-level executives before the crisis, they should be by now.

Digitalization is widely viewed as one of the keys to a sustainable recovery from the pandemic. Studies show that companies that move early and decisively to digitalize their operations during challenging times can turn adversity into advantage. Boston Consulting Group found that 14 percent of companies were able to emerge stronger from the four most recent global economic downturns, increasing both their sales and profit margins

Staying power is also key. Research by management consultant McKinsey found that companies which remained steadfast and committed to their long-term growth strategy during a downturn were able to accelerate faster coming out of it.

Some markets are benefitting from government stimulus packages that support investment in new technologies. In China, a government infrastructure package passed in March totaling $US4.8 trillion is aimed at softening the blow of current and future disruptions. It encourages investments in new data centers, artificial intelligence (AI), smart manufacturing, and 5G networks. The expectation is also that by rejuvenating legacy systems, China’s manufacturing will be able to reverse the productivity decline it has experienced since the global financial crisis of 2008.

The main applications for AI in manufacturing include value chain redundancy, remote operations, process automation, industrial robotics, predictive maintenance and machinery inspection, and autonomous materials movement. Machine learning now makes up 40 percent of all patents in the AI realm.Companies that can scale up their AI use cases during the crisis will be better able to navigate uncertain supply and demand, adjust to disruptions in operations and supply chains, allocate their workforces, and adapt to sharp changes in consumer confidence and priorities, according to analysts from Boston Consulting Group.

There is no shortage of automation experts touting the benefits of manufacturers investing in AI; investments in this technology are expected to reach $18.8 billion by 2027 (see below for more analyst predictions).

Sam Li, global senior vice president and general manager of SAP China, is convinced that digitalization will drive China’s economy out of its current trough, and that AI shows the most promise in making companies resilient.

"Just as digitalization has enabled China’s consumers to access life-essential services and stem the deadly chain of infection, digitalization in the business-to-business sector to create intelligent and integrated enterprises will be the engine for economic recovery,” Li said last month at the 2020 World Artificial Intelligence Online Conference (WAIC) in Shanghai.

He sees huge potential for AI in China’s manufacturing industries, and believes SAP is set up to become a main driver for AI in this sector: "As a global technology company with both business and R&D headquarters in Shanghai, SAP will help build a world-leading AI co-innovation and technology center in Shanghai and actively promote the integrated development of AI and industry in China.”

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