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Supply chain analytics

机译:供应链分析

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In this article, I describe the application of advanced analytics techniques to supply chain management. The applications are categorized in terms of descriptive, predictive, and prescriptive analytics and along the supply chain operations reference (SCOR) model domains plan, source, make, deliver, and return. Descriptive analytics applications center on the use of data from global positioning systems (GPSs), radio frequency identification (RFID) chips, and data-visualization tools to provide managers with real-time information regarding location and quantities of goods in the supply chain. Predictive analytics centers on demand forecasting at strategic, tactical, and operational levels, all of which drive the planning process in supply chains in terms of network design, capacity planning, production planning, and inventory management. Finally, prescriptive analytics focuses on the use of mathematical optimization and simulation techniques to provide decision-support tools built upon descriptive and predictive analytics models.
机译:在本文中,我描述了高级分析技术在供应链管理中的应用。这些应用程序按照描述性,预测性和规范性分析以及供应链运营参考(SCOR)模型域进行计划,来源,制造,交付和退货。描述性分析应用程序集中使用来自全球定位系统(GPS),射频识别(RFID)芯片和数据可视化工具的数据,为管理人员提供有关供应链中货物位置和数量的实时信息。预测分析以战略,战术和运营级别的需求预测为中心,所有这些因素都在网络设计,容量计划,生产计划和库存管理方面推动了供应链中的计划过程。最后,说明性分析着重于使用数学优化和模拟技术来提供基于描述性和预测性分析模型的决策支持工具。

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