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详解丨大数据彻底厘革供给链打点的十大方面

来源:新闻门户     作者:华夏门户     浏览:次     发布时间:2021-02-02
摘要:大数据可觉得供给商网络(Supplier Networks) 提供更好的数据精确性(Accuracy)、清晰度(Clarity)和洞察力(Insights),从而在共享……

大数据可觉得供给商网络(Supplier Networks) 提供更好的数据精确性(Accuracy)、清晰度(Clarity)和洞察力(Insights),从而在共享的供给网络中实现更多的情境智能(Contextual Intelligence)。

Bottom Line: Big data is providing supplier networks with greater data accuracy, clarity, and insights, leading to more contextual intelligence shared across supply chains.

有前瞻眼光的制造商们正在将80%或更大比例的供给网络策划勾当构建在其企业外部,他们操作大数据和云计较技能来打破传统ERP系统和供给链系统的范围性。对付贸易模式基于快速产物周期迭代和产物上市速度的制造商,传统的ERP/SCM系统仅仅是为了完成订单交付、发运和生意业务数据而设计的,这样的传统系统的扩展性极其有限,基础无法满意当下供给链打点所面对的各种挑战,已经成为企业供给链打点的瓶颈。

Forward-thinking manufacturers are orchestrating 80% or more of their supplier network activity outside their four walls, using big data and cloud-based technologies to get beyond the constraints of legacy Enterprise Resource Planning (ERP) and Supply Chain Management (SCM) systems. For manufacturers whose business models are based on rapid product lifecycles and speed, legacy ERP systems are a bottleneck. Designed for delivering order, shipment and transactional data, these systems aren't capable of scaling to meet the challenges supply chains face today.

如今的制造商都驻足于在精确性(Accuracy)、速度(Speed)和质量(Quality)方面开展市场竞争,这必然位迫使企业的供给商网络必需具备必然水平的情景智能的本领,传统的ERP/SCM系统是无法辅佐企业告竣这一竞争方针的。然而当今大大都企业还没有将大数据技能引入其供给链运营傍边,本文先容的十大体素将成为企业将来供给链计谋厘革的重要催化剂。

Choosing to compete on accuracy, speed and quality forces supplier networks to get to a level of contextual intelligence not possible with legacy ERP and SCM systems. While many companies today haven't yet adopted big data into their supply chain operations, these ten factors taken together will be the catalyst that get many moving on their journey.

举个小实例来说明大数据阐明(BDA - Big Data Analytics)如安在精确性、速度和质量方面临供给链打点晋升的浸染:

亚马逊Amazon操作大数据来监控、追踪、确保其15亿库存商品精确的存放于全球200个订单推行中心(fulfilment centers)傍边。亚马逊操作预测阐明(Predictive Analytics)技能可以实现“预期发货(anticipatory shipping)”的情景,即,当客户规划购置一件商品的时候(留意是规划购置尚未正式下单),亚马逊就将货品提前发运(pre-ship)到离客户最近的仓储中心。这种对供给链打点的优化极大的晋升了其客户的体验。

大数据厘革供给链

 详解丨大数据彻底厘革供给链打点的十大方面

1、情境智能 Contextual Intelligence

今朝,由供给链发生的数据的局限(scale)、广度(scope)和深度(depth)都在加快增长,为情景智能(contextual intelligence)驱动的供给链提供了富裕的数据基本。

The scale, scope and depth of data supply chains are generating today is accelerating, providing ample data sets to drive contextual intelligence.

下面“图1”很有意思,它收集了整个供给链中的52种差异的数据源(包罗布局化/半布局化/非布局化数据),并从大数据的三个维度(3Vs)举办了统计阐明,数据量(Volume)/数据速度(Velocity)和数据多样性(Variety)。个中很明明绝大部门数据都是从企业外部发生的。有前瞻性的制造商已经开始将大数据作为更遍及供给链协作的催化剂。

The following graphic provides an overview of 52 different sources of big data that are generated in supply chains Plotting the data sources by variety, volume and velocity by the relative level of structured/unstructured data, it's clear that the majority of supply chain data is generated outside an enterprise. Forward-thinking manufacturers are looking at big data as a catalyst for greater collaboration.

 详解丨大数据彻底厘革供给链打点的十大方面

图 1:点击查察高清大图

值得留意的是,在焦点生意业务系管辖域内,传统的ERP, SRM和CRM系统凡是在企业内部的数据量(Volume)是很高的,可是这些数据放在整个52中数据源框架下只占了很小的比例,这就是为什么图1中的“焦点生意业务系统数据”处于纵向较低的位置。假如你看右上角可以发明,高数据量和速度的非布局化数据多半是与“客户”交互的数据:社交数据、在线调研、移动位置传感设备等。

责任编辑:华夏门户
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