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Forecasting sales in the supply chain: Consumer analytics in the big data era

机译:预测供应链中的销售:大数据时代的消费者分析

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Forecasts have traditionally served as the basis for planning and executing supply chain activities. Forecasts drive supply chain decisions, and they have become critically important due to increasing customer expectations, shortening lead times, and the need to manage scarce resources. Over the last ten years, advances in technology and data collection systems have resulted in the generation of huge volumes of data on a wide variety of topics and at great speed. This paper reviews the impact that this explosion of data is having on product forecasting and how it is improving it. While much of this review will focus on time series data, we will also explore how such data can be used to obtain insights into consumer behavior, and the impact of such data on organizational forecasting.
机译:传统上,预测是计划和执行供应链活动的基础。预测驱动着供应链决策,由于提高了客户期望,缩短了交货时间以及需要管理稀缺的资源,因此预测变得至关重要。在过去的十年中,技术和数据收集系统的进步已导致以各种主题快速地生成大量数据。本文回顾了数据爆炸对产品预测的影响及其改进方法。尽管本文的大部分回顾都集中在时间序列数据上,但我们还将探索如何使用此类数据来深入了解消费者行为以及此类数据对组织预测的影响。

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