人工智能技术的数字物流
Design logistics processes of the future with advanced analytics using BearingPoint’s 导航器葡京app
Design logistics processes of the future with advanced analytics using BearingPoint’s 导航器葡京app
Data availability and importance have increased rapidly in recent years and will continue to gain significant relevance. Efficient and beneficial data 分析 is one of the most decisive competitive advantages in the highly competitive automotive industry.
人工智能(AI), 有针对性的处理, 协调, 分析, and use of data available along the supply chain becomes possible, enabling processes to be designed more efficiently and creating an optimized planning basis for business alignment. This way, companies can gain a decisive strategic edge.
Autonomous logistics systems of the future will enable companies to create self-controlled, 自动调整的, and optimized material flows and manufacturing areas. 聪明的, decentralized IT systems and robots communicate and collaborate, each taking on a specific role and working towards a common goal.
BearingPoint’s 导航器葡京app bundle innovative advanced analytics, enabling companies to generate added value from their data.
The goal is transparency and increased data quality for fully automated and digitalized processes at reduced costs. Application areas range from process and system 转换s and restructuring to identifying inventory optimization potential across the entire supply chain. 感谢直接的ERP连接, nearly real-time regular data analyses tailored to individual needs become possible.
The cloud software enables processes in transport and logistics systems to be implemented autonomously - with logistical tasks being continuously monitored and actively controlled. Our distinctive expertise extends to the definition, 评价, and implementation of integrated application scenarios. Numerous customers in the automotive industry, 原始设备制造商, as well as suppliers rely on BearingPoint’s 导航器葡京app to drive the digitalization of their logistics.
库存导航器 - Identify, realize, and sustain savings with full cost transparency of your inventory.
数据质量导航器 - Enable effective data quality measurement and control.
