Strategies for Data-Driven Decision-Making in Intelligent Enterprise Management: A Comparative Study of China and Germany

Abstract

This article investigates the strategies employed for data-driven decision-making (DDDM) in intelligent enterprise management, with a comparative focus on China and Germany. As digital transformation accelerates across industries, enterprises in both countries leverage big data, artificial intelligence, and innovative technologies to enhance operational efficiency and strategic planning. Using a comparative case study approach and secondary data analysis, this paper identifies key strategic frameworks, examines real-world applications, and assesses the challenges and opportunities of DDDM. A case study on Alibaba (China) and Siemens AG (Germany) highlights best practices in each country. The discussion section analyses policy, cultural, and technological differences that shape enterprise intelligence strategies. The paper concludes with policy recommendations and strategic insights for global businesses seeking to optimise intelligent decision-making systems