SPICI03 At present, the magnificent digital wave is constantly promoting the formation and development of new quality productivity, and has a profound impact on the transformation of industrial form and market pattern. Ding Xiaohong believes that the core elements of new quality productivity are innovation and high-quality development, green, low-carbon and digital intelligence. In the interplay of these factors, digital transformation will take on new characteristics.
On the one hand, the driving force of digital transformation of enterprises will become stronger and stronger, actively pursue energy saving, cost reduction and efficiency, create their own differentiated competitive advantages, and ultimately establish their own influence in the industry; On the other hand, enterprise digital transformation will become more pragmatic, and enterprises will consider both short-term input-output ratio and sustainable development goals in combination with their own demand priorities and application scenarios.
At the same time, at the level of industrial ecology, it will be more integrated and co-created, open and collaborative. Through the selection of appropriate partners, joint innovation is carried out to jointly promote the integration of digitalization and low-carbon, the integration of software and hardware, the integration of process optimization and energy optimization, and the integration of industrial application scenarios and cutting-edge new technologies such as AI, digital twins, machine learning, and 5G, to fully release the digital potential and form a greater industriaSPICI03 l influence.
Transformation tool: clear path, cultivate internal skills, make good use of technology, integration of ecology
To do a good job, you must first sharpen your tools. Through the right methods and tools, to promote the actual landing of digital transformation, and truly create actual value and opportunities for enterprises, is the “only way” to judge the effectiveness of digital transformation.
In the field of digital transformation, Schneider Electric has summed up four experiences of “clear path, cultivation of internal skills, good use of technology and integration of ecology” through its own practice and profound accumulation of service industry users over the years.
Ding Xiaohong said that when enterprises promote digital transformation, first of all, clear the path, combined with their own industry characteristics and demand pain points, do a good job of the overall plan of “small step fast run”, and flexibly adjust the pace against the phased goals; Secondly, enterprises need to continuously cultivate internSPICI03 al skills and continuously improve the awareness and ability of digital and intelligent organization; Third, make good use of technology, enterprises should choose mature and stable software technology and tools to achieve the integration of key data throughout the life cycle, and truly create their own digital and intelligent factories; Finally, the integration of ecology, specialized industries, and resource complementarity relying on the ecosystem will help promote the digital transformation process more efficiently and quickly.
The integration and innovation of AI and application scenarios has become a strong engine for digital intelligence transformation
Among the series of cutting-edge technologies driving the wave of digital transformation, AI technology has shown unlimited development potential and has become a new key variable to promote the transformation of industrial digital intelligence.
In this regard, Ding Xiaohong believes that the key to play the potential of AI technology is to promote the integration and innovation of AI technology and practical application scenarios. She said that at present, Schneider Electric has widely applied AI technology to a series of specific scenarios such as visual recognition, predictive analysis, equipment control, process optimization, energy efficiency optimization, and operator training, and actively leads the industrial ecology to co-create, becoming an excellent “practitioner” and “enabler” of AI technology.
According to Ding Xiaohong, as a “practitioner”, Schneider Electric has extensively deployed AI algorithm-based predictive maintenance in all factories in China, which not only doubles the average time between failures of key equipment, but also reduces downtime and spare parts consumption. As an “enabler”, Schneider Electric’s AI-based solutions can help users achieve 3%-5% efficiency improvements and annual energy consumption reductions of 5%-10%.
