Every technological change will bring about the continuous upgrading of productivity and production methods. Nowadays, all walks of life are accelerating on the road of digital transformation. The process requires many capabilities, and the commonality of those enterprises that take the lead in transformation lies in the deep integration of cutting-edge intelligent technology and production technology to further realize business innovation and digital transformation and upgrading. Take a Chinese ICT industry giant as an example. It has hundreds of factories. Its core requirement is to share capacity pool and collaborate with multiple factories to optimize overall benefits. With the help of intelligent technology to improve decision-making efficiency, the company achieved a 20% increase in order fulfillment rate, a 30% reduction in capacity loss rate and a 70% reduction in manual intervention, which has brought hundreds of millions of cost benefits for the whole chain business, and with the deep application of intelligent decision-making technology, its value is rapidly rising.
Gartner, Deloitte and Big idea, the world's well-known research institutions, all listed the intelligence-related technology trends as the only way to develop: artificial intelligence/machine learning, super automation and fine management. At the same time, more and more enterprises realize that the single intelligent technology of perception layer, such as face recognition and voice recognition, is limited for enterprises to achieve leapfrog growth, and the high-efficiency, automated response intensive, combined demand decision-making intelligent technology will be the driving force for future enterprise development.
Born at the right time, advanced decision-making intelligent technology
With the gradual maturation of digital technologies represented by 5G, artificial intelligence, big data, cloud computing and digital twinning, data assets surge, and "from data-driven to decision-oriented" has become the consensus of industrial digital transformation. The collaboration between global mass production and digitalization further promotes the crossover and integration of different links of the industrial chain, and greatly increases the complexity and sophistication of the industrial operation system.
Reviewing our country market, after many years of digital construction, some head enterprises information construction has been basically completed, and the digital infrastructure has begun to take embryonic form. The next step is to look for new technology engine which can make business the second breakthrough and enterprises take off again. This year's 14th Five-Year Plan clearly states that we will give full play to the advantages of massive data and diverse application scenarios, promote the deep integration of digital technologies with the real economy, enable the transformation and upgrading of traditional industries, foster new industries and business forms and models, strengthen new engines of economic development, and seize the commanding heights of future economic and technological development.
No matter from what perspective, industrial upgrading can no longer be limited to individual intelligence, but should be extended to all links of the industrial value chain. It is no longer limited to the exploration of intelligent decision-making, but pays more attention to the deep integration and innovation of intelligent decision-making technology with retail, manufacturing and other cross-technology fields. For example, ICT giants mentioned in the beginning complete multi-link optimization of complex manufacturing scenarios through intelligent decision-making technology, and realize intelligent production scheduling of hundreds of factories. Intelligent decision making can provide more profound business insight in the operation of enterprises, improve the quality and efficiency of decision making, deduce the optimal decision plan from the results of 100 million level, and make the operation more efficient and precise.
The landing point of intelligent decision: Technology + middle stage + scene
Although it is at the cusp, it is undeniable that it is a long-term and gradual process to promote the implementation of intelligent decision optimization technology in China. In addition to the common problems such as greatly increased operational complexity of industrial system and higher requirements for market response sensitivity, Chinese enterprises are also faced with many challenges such as key technologies being controlled by others, core industrial software being mainly dependent on imports, poor system integration, and technology and business scenarios being "unadaptable".
Technology: Localization, breaking international technical barriers
In the field of intelligent decision making, the mathematical programming solver as the underlying core computing engine can help users transform complex business problems into mathematical problems, and then model and solve them, and find the optimal solution from thousands of feasible schemes. At present, the domestic innovative enterprises represented by Sansu Technology are at the forefront of the intelligent decision optimization field by relying on the innovation ability of domestic solver products and platform solutions. For example, they launched the first completely independently developed integer programming solver COPT in China, which has been successfully applied to the national key fields such as aerospace, energy and power, intelligent manufacturing, supply chain management, etc. For example, the combination optimization of power grid units, dynamic adjustment of 5G base station power, multi-factory collaboration of industrial chain, large-scale optimization of parallel computing and other scenarios.
Middle Desk: Modular design, create intelligent decision-making middle desk
For super-large enterprises, limited by industry attributes and complexity of business scenarios, one-to-one solution customization is usually required, but it also requires universality and flexibility. Therefore, the importance of mid - Taiwan is shown. The operational research model, statistical model, machine learning model and other module components of the decision-making platform cannot be directly applied by the business, but when the front-end needs, it can meet the changes of various business scenarios through rapid modular configuration or customized development of special scenarios based on the module, so as to achieve the goal of sharing, coordination and flexibility. Help clients solve high-frequency business decisions and operational optimization problems that occur every day.
Scenario: Application scenario is the basis of intelligent decision making
In order to achieve a business breakthrough, intelligent decision-making technology must be deeply combined with the application scene. In a real sense, from the engine, to the middle platform, and then to the scene, a "whole chain" closed loop is formed to realize the opening up and integration of the digital chain. For intelligent decision-making technology, the underlying computing engine is just a standardized product. How to use it in different enterprises, how to "adapt to local conditions", different industries have different solutions, involving the typical application scenarios of complex industries: including supply chain optimization in the retail industry; Manufacturing industry production scheduling, inventory optimization and so on.
Taking the end-to-end supply chain optimization platform program created by the World Top 500 and international food leading enterprises as an example, from demand planning, replenishment plan, dynamic pricing, precision marketing, collaborative distribution to intelligent warehousing, with the help of the intelligent algorithm of Shensu technology and decision optimization technology, the accuracy of sales forecasting is increased by 10%, the management efficiency is increased by 60%, and the number of days of inventory turnover is reduced by 20%. When the appropriation of inventory funds decreases by 10%, the overall profit increases by about 10%. This kind of scenario can also be applied to other industries, such as e-commerce, retail, manufacturing and other industries to build flexible supply chains.
At present, the basic capabilities of cloud, data accumulation and AI service capabilities have been organically integrated, and diversified business digital application scenarios in various industries also provide an excellent stage for decision optimization. Building a digital "decision brain" with leading decision technology and driving the transformation to digital intelligence is gradually becoming a key force for the digital transformation of enterprises and industries.
