Under the new economic normal, refined operations have become the key driving force for corporate growth, which puts forward higher requirements for decision-making quality. At the same time, the complex and ever-changing business environment has continuously increased decision-making constraints and put forward higher requirements for decision-making agility. Therefore, traditional business decisions relying on business rules and expert experience are increasingly difficult to meet the needs of enterprises, and enterprises need to upgrade their decision-making methods.
Intelligent decision-making comprehensively utilizes various intelligent technologies such as machine learning, deep learning, reinforcement learning, and operational research optimization to achieve enhanced and automatic decision-making. Based on established goals, comprehensive constraints, strategies, preferences, uncertainties and other factors can be used to construct relevant data. Model analysis to automatically generate optimal decisions. Intelligent decision-making has the ability to help enterprises upgrade their decision-making methods.
Through the research on the intelligent decision-making market, Aianalysis found that the technical paths of different intelligent decision-making manufacturers are quite different, and they also have their own strengths in application scenarios. Enterprises need to combine their own digital development plans and business scenario needs to select the most suitable vendors to build intelligent decision-making capabilities. Based on the above background, Aianalysis hopes to help enterprise decision makers to accurately select the right manufacturer and successfully implement intelligent decision-making projects through the panorama of intelligent decision-making manufacturers and best practice case studies.
From the perspective of technical architecture, the intelligent decision-making market can be divided into two parts: intelligent decision-making platform and intelligent decision-making application solutions. The intelligent decision-making platform provides tools that support intelligent decision-making algorithms, models, and application development and calculation. The application solution layer focuses on intelligent decision-making solutions for industries such as finance, consumer goods and retail, national defense, government and public services, manufacturing, energy, logistics, aviation, medical care and medicine, and automobiles.
This report focuses on the three markets of intelligent decision-making solutions for the financial industry, intelligent solutions for the consumer goods and retail industry, and intelligent decision-making solutions for the defense and military industries as key research objects to conduct research on intelligent decision-making.
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