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Using AI to Overcome the Great Supply Chain Disruption

2022-10-24
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Using AI to Overcome the Great Supply Chain Disruption
Illustration: © IoT For All

The increasing mayhem at ports with no end in sight has caused panic in the business world. It has become a big issue, and the world faces a great supply chain disruption. The inability to supply products on time creates chaos for both customers and manufacturers. Due to supply chain disruption, companies often face spoilage of perishable products, reduction in demand, and non-returning customers. The supply chain issue is not limited to a single sector but is blanketing almost every industry. Let’s look at how artificial intelligence can be used to start tackling these supply chain issues.

'Adopting artificial intelligence technology will equip companies with the important information required to ease today's supply chain challenges.' -Ritesh SutariaClick To Tweet

Behind the Disruption

Could it be the lack of truck drivers? No, we cannot blame one single thing for the disruption. Issues like lack of advanced technology, real-time data availability, and hesitation toward adopting new technologies contribute to this issue.

The reason behind the emerging challenges in the supply chain is that current inventory and planning systems run on fixed lead times and demand forecasting, whereas the real world functions on dynamic lead times. It results in poor decision-making and bad planning by the procurement leaders and financial executives, ultimately causing port congestion. Leaders must withhold planning initiatives and vigorously manage their shipments to correct this.

Whenever there is a change in transportation medium while shipping goods, long queues emerge, adding to the problem. While it might appear that a new means of transportation can relieve congestion, this is not a real and practical solution. Therefore, choke points cannot flourish without a substantial investment so the port infrastructure limitations are repaired.

Planning Shipments Accurately

Retailers require real-time inventory visibility across their enterprises to plan more precisely. Generally, stowage plan information is shared with terminal and third-party logistics companies exiting the gate as one value chain. It enhances the efficiency of the first-in, first-out process. Artificial Intelligence can support the supply chain in determining changes in transportation or routes early to ensure on-time and seamless delivery of critical items.

Despite AI implementation being new to supply chain management, early adopters are already leveraging this technology. As per McKinsey & Co., companies embracing AI-enabled supply chain management saw improved logistics costs by 15 percent and inventory levels by 35 percent. As AI technology grows, more companies are attracted to it to churn immense benefits from its potential. Therefore, AI in the logistics and supply chain markets is predicted to expand at a compound annual growth rate of around 42.9 percent between 2017-2023.

Use Cases for AI in the Supply Chain

With the increasing popularity of AI, there is a great chance that it can enhance and make the supply chain process seamless. Let’s take a look at some critical use cases:

#1: Shipment Prediction

Customers expect to receive their ordered goods in a few days. Nevertheless, World Economic Forum data reveals that delivery times within the U.S. and Europe will continue to rise. Moreover, the current environment shows us that increased time frames will remain part of the future. In fact, amid unforeseen circumstances like a natural disaster or poor weather, customers expect that companies have a backup for these situations and deliver their orders on time. AI can assist companies in predicting on-time, in-full drops early using past data to know the way vendors fulfill orders. It permits companies to establish deadlines to switch modes of transportation for customers who create the most significant profit margins. In addition, AI also offers full visibility of materials across the entire value chain, making it easy to find and eliminate bottlenecks promptly.

#2: Deprioritize High-Cost Customers

Garner forecasts that 75 percent of enterprises will drop poor-fit customers by 2025. However, some companies might be unable to discontinue the relationship with costly clients. These loss leaders should not be part of their priority lists. It can appear as a big challenge for businesses to detect these customers. With sorting algorithms, artificial intelligence can automatically identify customers at scale who are not good enough for market-share gains and drain prized capacity. Further, AI can find new opportunities for improvement and discover how these opportunities will influence the bottom line.

Without knowing consumer demand, companies often risk selling products that do not show much demand, costing millions of dollars in loss. AI-driven forecasting can support companies in detecting demand changes as soon as possible, permitting them to optimize products for the best profit margins.

#3: Increase Profit Margins

AI-powered supply chain management offers a 65 percent reduction in lost sales caused by out-of-stock products. On the sales side, AI can support the sales team in identifying upsell and cross-sell opportunities for key accounts. Often, companies have very less knowledge of whom they should be upselling. Nevertheless, the sales team continuously gathers data because most sales tasks occur digitally. AI can use this information to support teams selling more efficiently.

#4: Faster Shipping

In a survey conducted by Convey, 28.6 percent of consumers shared that they like to place an order with companies that can deliver products as soon as possible or within a week of the order. This is a really small window of time, which means faster shipping is important if companies want to attract customers. In this instance, AI can also find shippers who slow down the supply chain. Once detected, companies can remove the players who cannot keep pace and replace them with others who are more efficient. Similarly, suppliers can also use AI to create simulations based on bottlenecks and disruptions.  Once the AI identifies that the specific portion of the supply chain is bottlenecked, it can predict when companies can expect a shortage based on inventory stock levels or extending lead times.

When Will We Resolve the Disruption?

It might take years to resolve the Great Supply Chain Disruption. If businesses wish to deliver products seamlessly, they must change their plan. Adopting artificial intelligence technology will equip companies with the important information required to ease today’s supply chain challenges.

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  • Artificial Intelligence
  • Industrial Automation
  • Supply Chain and Logistics

  • Artificial Intelligence
  • Industrial Automation
  • Supply Chain and Logistics

参考译文
利用人工智能克服巨大的供应链中断
港口不断增加的混乱局面看不到尽头,这在商界引起了恐慌。它已经成为一个大问题,世界面临着一个巨大的供应链中断。无法及时供应产品给客户和制造商都造成了混乱。由于供应链的中断,公司经常面临易腐产品的变质,需求的减少,和不回头客。供应链问题不仅局限于一个行业,而且几乎覆盖了所有行业。让我们看看如何利用人工智能开始解决这些供应链问题。会不会是因为缺少卡车司机?不,我们不能把这种混乱归咎于任何一件事。诸如缺乏先进技术、实时数据可用性以及对采用新技术犹豫不决等问题都是造成这一问题的原因。供应链中新出现的挑战背后的原因是,当前的库存和计划系统运行于固定的交货期和需求预测,而现实世界的功能是动态的交货期。它导致了采购领导和财务主管的糟糕决策和糟糕规划,最终导致港口拥堵。领导者必须保留计划的主动性,并积极地管理他们的发货,以纠正这种情况。在运输货物时,只要运输媒介发生变化,就会出现排长队的情况,使问题更加严重。虽然一种新的交通工具似乎可以缓解拥堵,但这并不是一个真正的和实际的解决方案。因此,如果没有大量的投资,瓶颈就无法繁荣起来,因此要修复港口基础设施的限制。零售商需要整个企业的实时库存可见性,以便更精确地进行计划。通常情况下,配载图信息与出港码头和第三方物流公司作为一个价值链共享。它提高了先进先出流程的效率。人工智能可以帮助供应链尽早确定运输或路线的变化,以确保关键项目的准时和无缝交付。尽管人工智能在供应链管理中还很新鲜,但早期采用者已经开始利用这项技术。根据麦肯锡&采用人工智能供应链管理的公司物流成本提高了15%,库存水平提高了35%。随着人工智能技术的发展,越来越多的公司被它吸引,从它的潜力中获得巨大的利益。因此,2017-2023年期间,物流和供应链市场的人工智能预计将以约42.9%的复合年增长率扩大。随着人工智能的日益普及,它有很大的机会可以增强和使供应链过程无缝衔接。让我们看一下一些关键用例:客户期望在几天内收到他们订购的货物。不过,世界经济论坛(World Economic Forum)的数据显示,美国和欧洲的交货时间将继续延长。此外,目前的环境表明,增加的时间框架仍将是未来的一部分。事实上,在不可预见的情况下,如自然灾害或恶劣天气,客户希望公司有应对这些情况的备份,并按时交付订单。人工智能可以帮助公司利用过去的数据提前预测及时、完整的交货,了解供应商履行订单的方式。它允许公司为创造最大利润空间的客户设定转换运输方式的最后期限。此外,AI还提供了跨越整个价值链的材料的全可见性,使其易于及时发现和消除瓶颈。 加纳预测,到2025年,75%的企业将放弃体质不佳的客户。然而,有些公司可能无法终止与高成本客户的关系。这些损失领导者不应该是他们优先考虑的对象。对企业来说,发现这些客户似乎是一个巨大的挑战。通过排序算法,人工智能可以大规模自动识别那些不够优秀、无法获得市场份额、耗尽宝贵产能的客户。此外,人工智能可以发现新的改进机会,并发现这些机会将如何影响底线。在不了解消费者需求的情况下,企业往往会冒险销售需求不大的产品,造成数百万美元的损失。人工智能驱动的预测可以帮助企业尽快发现需求变化,使他们能够优化产品,获得最佳的利润空间。人工智能驱动的供应链管理可以减少65%因缺货产品造成的销售损失。在销售方面,AI可以支持销售团队为关键客户识别追加销售和交叉销售机会。通常情况下,公司对应该向谁推销知之甚少。然而,销售团队不断地收集数据,因为大多数销售任务都是数字化的。人工智能可以利用这些信息来支持团队更有效地销售。在一项由传达公司进行的调查中,28.6%的消费者表示,他们喜欢向那些能尽快或在订单后一周内发货的公司下订单。这是一个非常短的时间窗口,这意味着如果公司想吸引客户,更快的运输是重要的。在这种情况下,AI还可以找到减缓供应链的托运人。一旦被发现,公司可以解雇那些跟不上节奏的员工,用效率更高的员工取而代之。类似地,供应商也可以使用人工智能根据瓶颈和中断创建模拟。一旦人工智能识别到供应链的特定部分遇到瓶颈,它就可以根据库存水平或交货时间的延长,预测公司何时可能出现短缺。解决供应链大中断可能需要数年时间。如果企业希望无缝交付产品,他们必须改变计划。采用人工智能技术将为企业提供缓解当前供应链挑战所需的重要信息。
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