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为了满足这些具有挑战性的电子商务需求，DHL Supply Chain——合同物流领域的市场和德国邮政 DHL集团的一部分——越来越依赖基于 IT 的智能预测和分析工具来优化大型电子商务的在线订单的仓储和处理。 - 卖家。

　　COVID危机向我们表明，个别产品不可预见的数量波动会给供应链带来巨大压力。库存水平不明确和可用性数据不正确可能导致个别产品出现瓶颈，延迟交付给Zui终客户，DHLSupply Chain 信息官兼运营官 Markus Voss解释道。我们正在与我们的客户——大型在线商店和零售公司——合作开发更具抗压能力、更可靠的算法和工具，以更好地预测需求波动，优化人力分配，从而加快货物的吞吐量和订单周期。

　　我们的 IDEA 分析工具是我们应对这些电子商务挑战的众多解决方案之一，DHL Supply Chain解决方案设计执行副总裁 Dietmar Steins说。通过其算法，这种人工智能解决方案有助于优化仓库内的拣选路线。订单也按逻辑进行聚类，这有助于优化我们仓库同事的拣选。集成的智能任务规划还可以优化仓库员工的工作量分配并帮助优先处理时间紧迫的发货。IDEA降低了错误率以及员工培训所需的时间。

　　IDEA 算法可以显着改善 DHL 运营的仓库中的订单拣选流程。由于 DHL开发的软件与大多数传统仓库管理系统兼容，并且可以轻松集成到现有 IT基础设施中，所涉及的成本相对较低。在其商业部署中，该解决方案将仓库员工的出行距离减少了多达 50%，并将单个 DHL地点的生产力提高了多达 30%。

　　DHL Supply Chain 开发和设计了专门用于电子履行仓库的 IDEA 软件解决方案。合同物流专家雇佣了一支由大约350 名开发人员、工程师和解决方案设计师组成的专门团队，代表其客户开发和优化仓储物流流程。

The COVID crisis has resulted in steadily growing online sales.Especially online orders of everyday staples, such as food,medicines and other drugstore products, are higher today thanbefore the pandemic. The trend poses challenges for retailersworldwide. In many cases, orders have increased, but the size ofshipments is smaller. New and more diversified product ranges meansmore stock keeping units for online retailers. Moreover, endcustomers expect fast, sometimes even same-day delivery with hightransparency and traceability.

　　To meet these challenging e-commerce needs, DHL Supply Chain –market leader in contract logistics and part of Deutsche Post DHLGroup – is increasingly relying on intelligent, IT-basedforecasting and analysis tools to optimize warehousing andprocessing of online orders for major e-sellers.

　　"The COVID crisis has shown us that unforeseen volumefluctuations for individual products can put enormous stress onsupply chains. Lack of clarity regarding stock levels and incorrectdata on availability can lead to bottlenecks for individualproducts and then delays in delivering to end customers," explainsMarkus Voss, CIO & COO at DHL Supply Chain. “We are working withour customers – large online stores and retail companies – on morestress-resilient, reliable algorithms and tools to betteranticipate demand fluctuations, optimize the allocation of manpowerand thereby accelerate the throughput of goods and ordercycles.