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How Is Artificial Intelligence Reshaping Global Supply Chains In 2021?
How has AI impacted the global supply chain today?
From ongoing work with autonomous ships to product tracing for orders and raw materials, artificial intelligence is shaking up multinational networks in huge ways.
When traditional supply chain management tactics come up short, AI technology can automate iterative tasks like warehouse sorting, enabling companies like Amazon to offer same-day delivery to customers hundreds of miles away.
That said, can AI really make a difference for businesses or is it just hype?
Well, a McKinsey analytics report estimates that companies incorporating AI into their global supply chains could gain between $1.3 to $2 trillion annually. So the benefits are most certainly very real, and promising.
While all that sounds all well and good, the question remains: how exactly can AI make global supply chains more profitable?
In this article, we’ll be discussing how AI is reshaping global supply chains via three, practical real-life applications.
1. Content Intelligence
What is the biggest problem facing global supply chains today?
The answer is as complex as data silos, yet the solution is as simple as an AI-powered content intelligent software like Adlib.
Data and its availability across all the individual branches of a supply chain is one of the most important factors for a seamless multinational workflow.
However, when data in one arm of the company is hidden from the rest of the network (data silo), several supply chain problems arise including:
- Lost opportunities for improving transportation and logistics
- Costly supply chain mistakes that require expensive corrective actions.
- Poor customer experience from delayed shipping and misplaced orders
In recent times, the US Food industry is one of the biggest casualties of a poor data management system.
It is estimated that the industry loses 40% of its food production annually, according to a report by the NRDC. Limited data leads to bad decisions that result in spoilage, thereby increasing expenses for consumers, shippers, and farmers.
With a content intelligence platform such as Adlib, for example, companies can break down data silos, for better data availability across organizational branches, and to avoid costly supply chain errors.
This AI-driven software scans files and data in all types of formats across the individual systems of an organization. That includes word documents and pdfs among many other file types.
If some of the data is still in printed format or other hard copy versions, the intelligent content management platform converts them into a digital form using optical character recognition (OCR) technology.
Once all data is electronically available, the content intelligent platform offers cloud storage to ensure the constant availability of precious supply chain information. Via natural language processing and machine learning, the software can pick out duplicate files as well.
When data needs to be drawn from this system, Adlib uses advanced algorithms to extract the specific data attributes requested.
In the long run, an AI-powered content intelligent system facilitates supplier selection, inventory management, and regulatory compliance, among many other benefits.
2. Warehouse Management
Many companies today have huge warehouse facilities the size of football fields, which means efficiency in storage and sorting is a tremendous challenge.
But why is warehouse efficiency important to a global supply chain in the first place?
Well, with good warehouse efficiency, companies are able to provide faster product processing of client requests.
Consequently, that means more organized and faster-dispatching processes, leading to increased delivery speeds and better customer satisfaction.
In step intelligent warehouse assistants.
Warehouse support robots can work alongside human workers to ease huge sorting and transportation demands in large warehouses. They can automate tedious, iterative chores while their human counterparts turn attention to more intelligent jobs.
Amazon, for example, the biggest eCommerce company in existence, is using AI-powered drive units in their fulfillment centers.
Now, across the globe, Amazon has over 170 fulfillment centers, which goes to show how large and intensive their warehouse processes are.
The company uses what’s known as a mobile robotic fulfillment unit, which does the heavy lifting to get products to a warehouse worker for sorting.
Initially, products are stored on liftable pods. So when an order comes into the system, the database activates the nearest bot for duty and maps the path to the item.
Using AI-driven optical character recognition, these bots find their way by scanning bar-codes on the tracks. An intelligent object detection system enables them to avoid collisions with warehouse structures, and other units performing similar tasks.
In a nutshell, the drive unit can retrieve products and take them to specified employees. As a result, shipping is faster and easier as opposed to the human worker manually going in to find the item.
3. Product Tracing
A global supply chain network involves shipping thousands of miles across international borders.
Therefore, keeping track of where products have been, and where they’ll be, can be challenging. Even more so when businesses rely on traditional milestone systems that depend on human diligence for updates.
AI-powered product tracing solutions can help a company keep better track of its products. With this information, businesses can easily trace defects and provide accurate estimates for delivery periods.
Companies can ensure accurate and timely product tracing by using AI-driven tracing software.
And it doesn’t end there.
Another application aside from chain traceability is internal traceability. This entails being able to track raw materials within the company networks, wherever they may span.
Manufactures now implement tracing through radio frequency technologies, but AI-powered bar code tracking is fast becoming popular.
In AI-based tracking systems, items are fitted with distinct bar codes entailing product details, and a machine learning OCR technology can decrypt this information. Then, via an intelligent content system, displays the details to a remote output device.
When paired with an alert system, point-of-sales managers can get real-time notifications of raw materials or productions in a large supply chain network.
Consequently, it becomes easy to conduct recalls for defective or damaged products, as soon as they are discovered. It, therefore, becomes easier to carry out corrective action before the company spends more on transportation.
German technology company Logivations, are providing AI-powered tracing solutions to large supply chain organizations.
The company uses deep learning software to analyze QR codes, find barcodes and also count products before. Additionally, the software can determine as well the size of items through computer vision.
Can companies make it without AI software in their digital supply chain transformations?
The short answer is yes.
However, the long answer is not as straightforward. While companies can get by with traditional supply chain management methods, they can thrive to new heights with the aid of AI technology.
Companies are able to drastically increase revenues with the adoption of AI into their networks, finds a McKinsey global survey. From 33 separate use cases, the study established that over 63% of businesses were able to grow revenue, while 44% lowered expenses.
So not only is AI enabling businesses to increase what they’re making but it is also reducing operating costs for an even larger profit margin.
Therefore, it is evident that artificial intelligence is an excellent solution to a profitable supply chain management system.
The results have been instrumental, spanning various components of the supply chain network. From contract analysis to inventory management, AI-powered solutions are impacting supply chains in crucial ways.