How AI Can Help Overcome the “Great Supply Chain Disruption”

by Editorial Team

As the mayhem at ports persists with no end in sight , a troubling realization is sinking in: This chaos will not subside with time alone, and the impacts of the “ Great Supply Chain Disruption ” are being felt across the country. For example, about 30% of baby […]

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As the mayhem at ports persists with no end in sight, a troubling realization is sinking in: This chaos will not subside with time alone, and the impacts of the “Great Supply Chain Disruption” are being felt across the country. For example, about 30% of baby formula brands could be sold out soon, causing retailers to ration how many containers customers can buy and leaving parents worried that they won’t have enough food to feed their babies. This issue spans industries, impacting automotive, healthcare, hospitality, IT, manufacturing, apparel, and more.

So, what’s the problem? Infrastructure and a lack of truck drivers are often blamed. U.S. trucking companies experienced a record deficit of 80,000 drivers in 2021. It’s a logical explanation because truck drivers move a considerable portion of American freight. However, it’s not the only cause of the supply chain issues.

Reasons for Supply Chain Challenges

Current inventory and planning systems operate on fixed lead times and demand forecasting, while the real world operates on dynamic lead times. As a result, poor decision-making and bad planning by procurement leaders and financial executives are driving the port congestion. To correct this, leaders must forgo planning initiatives and actively manage their shipments.

Every time a transportation medium is changed when shipping goods, there are long queues due to changeover, further aggravating the problem.

Although it might seem logical to think new means of transportation can help alleviate the congestion, this isn’t a practical solution.

Choke points can’t grow without a significant investment, so the port constraints are fixed from an infrastructure perspective. For retailers to change how they plan and prioritize shipments, however, they’ll need help.

How to Plan Shipments More Accurately

Retailers need real-time inventory visibility across their enterprises to plan more accurately. Ideally, stowage plan information can be shared with terminal and third-party logistics companies exiting the gate as one value chain. This helps improve the efficiency of the first-in, first-out process.

AI can help determine changes in transportation or routes early enough to ensure on-time delivery for critical items.

Although AI implementation is still new to supply chain management, early adopters see success. According to McKinsey & Co., enterprises that utilized AI-enabled supply chain management improved logistics costs by 15% and inventory levels by 35%. As AI technology continues to improve, more companies are interested in benefiting from its capabilities. As a result, Infoholic Research predicts that AI in the logistics and supply chain markets will grow at a compound annual growth rate of 42.9% until 2023.

Use Cases for AI to Overcome Supply Chains Disruption

As AI adoption increases, there’s hope that it can help ease supply chain issues. Here are a few critical use cases

1. Predict on-time, in-full rate drops.

Customers are used to receiving purchased goods in a matter of days. However, World Economic Forum data shows that delivery times across the U.S. and Europe will hit record highs toward the end of 2021. Moreover, the current environment indicates that those increased time frames will likely continue.

Even amid unforeseen circumstances such as natural disasters and poor weather conditions, buyers expect that the companies they purchase from will have backup plans to ensure timely deliveries.

AI can help companies predict on-time, in-full drops early using historical data to identify how vendors fulfill orders. This allows companies to set deadlines to switch modes of transportation for customers who generate the most significant profit margins. Furthermore, AI provides full visibility of materials across the entire value chain, making it easy to identify and eliminate bottlenecks quickly2. Deprioritize high-cost, poor-fit customers.

Not all business relationships are a great fit. Gartner predicts that 75% of companies will drop poor-fit customers by 2025.

Although some companies might not be ready to break up with costly clients, these loss leaders shouldn’t take up space at the top of their priority lists.

However, it can be challenging for businesses to identify these customers. With the help of sorting algorithms, AI can automatically identify customers at scale who are bad for market-share gains and drain precious capacity. Additionally, AI can identify new opportunities for improvement and uncover how these opportunities will impact the bottom line.

3. Increase profit margins.

Without a clear understanding of consumer demand, companies risk pushing products that don’t sell, costing businesses millions of dollars.

AI-powered forecasting can help companies sense demand changes early, allowing them to optimize products for the best profit margins.

According to McKinsey, AI-enhanced supply chain management provides a 65% reduction in lost sales caused by out-of-stock products. On the sales side, AI can help sales teams identify upsell and cross-sell opportunities for key accounts. Often, companies have limited knowledge of whom they should be upselling. However, because most sales tasks happen digitally, sales teams constantly collect data. AI can leverage this information to help teams sell more efficiently.

4. Ship faster

In a survey by Convey, 28.6% of respondents said they are more likely to place an order with companies that can deliver products within a week of purchase. That’s a pretty small window of time, so faster shipping is critical if companies want to encourage consumers to shop with them.

AI can identify shippers who slow down the supply chain. Once identified, companies can remove the players who aren’t keeping the pace and replace them with someone more efficient. Furthermore, suppliers can use AI to create simulations based on bottlenecks and disruptions.

Once the AI knows that a specific portion of the supply chain is bottlenecked, it can anticipate when companies can expect a shortage based on inventory stock levels or extending lead times.

It will take more than time to move past the “Great Supply Chain Disruption.” If businesses truly want to deliver products efficiently, they’ll need to change how they plan. By implementing AI technology, companies will be better equipped with the information necessary to ease today’s supply chain challenges.

Ali Hasan R. is the co-founder and CEO of ThroughPut Inc.the artificial intelligence supply chain pioneer that enables companies with predictive replenishment for complex supply chains.

Image Credit: thisisengineering; Unsplash; Thank you!

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