A global supply chain faces many challenges according to its size and structure.
However, several bottlenecks in the global supply network trace down to poor and manual handling of data, which results in numerous mistakes.
From delivery mix-ups because of loading errors, to inventory mismanagement due to human data transfer inaccuracies, many problems stem from dark, siloed and unstructured data.
All these issues lower profit margins and chip into the increment of operational costs.
If left unchecked, chain bottlenecks can cripple and bring down an entire supply chain network in the long run.
Artificial intelligence applications in supply chain management can prevent supply chains from collapsing.
You can track your company’s products better throughout the chain with AI data management, and also better coordinate deliveries, transportation, and returns where needed.
1. Product Tracing
If you’ve been in a multinational business for a while, especially regarding foodstuff, you’ll know that product tracing is an important requirement of EU law.
With poor or inaccurate tracking, your company is left vulnerable to certain blind spots. For example, it becomes hard to pinpoint contamination sources should such a problem arise later. Instead, you might have to resort to blanket recalls to solve the riddle. What’s more, a lack of transparency in product tracing can interfere with public opinion of brand integrity. That, in turn, affects customer loyalty which directly influences your profits.
Solve product tracing issues by using AI-powered OCR tools.
Optical character recognition (OCR) software can easily track items through a process of character verification via barcodes or other labels/markings. An OCR software can extract information from these codes and labels, to not only figure out the contents of the package but also establish where it’s been.
As goods reach certain milestones, OCR barcode scanners can confirm a product’s location. More and more milestones are flagged down as the item makes its way across the chain and the respective scanning points. Consequently, a digital trail is created which can provide tracking data.
This information can be updated in real-time, and customers can get the data on their devices. That is very important because, according to a ProShip study, 97% of customers expect to be able to trace their product throughout the shipping process.
Additionally, scanners can confirm codes are in good shape throughout the supply network. That enables early identification of defects, and where they occurred in the chain for better accountability.
2. Inventory Management
How does the inventory management system work in your company? In many businesses, sorting workers tick off items on a checklist and fill in the quantities received by hand. They later hand over this information to another department or manager, who in turn digitizes these records. But therein lies the problem.
Human inventory managers are prone to errors.
In a bid to get tasks done quickly, an extra zero can pop up unintentionally every now and again. The number “7” can also be jotted down as a “1” amidst this hurry, among other mistakes.
Illegible handwriting alone, for one, is a huge problem. A survey by Correlated.org revealed that 69% of people have bad handwriting. In other words, for every 100 employees in your global supply chain network, 69 of them have illegibility writing issues.
OCR software recognizes handwritten or printed texts and digitally converts them.
The process begins with a pre-processed image, where the OCR “looks” at the document, and then enhances it to reduce visual distortion. Afterward, a process called feature extraction takes its course.
Feature extraction entails the OCR software being able to only extract important characters in the document and leaving out what is considered redundant or unimportant. An example of unimportant details would be the lines on an inventory page, for instance.
The next step that follows entails error correction in post-processing. To guarantee the accuracy of the recognition process, the data output is checked against a lexicon.
In a nutshell, the result is clearer inventory outputs, and reliable data for you to make managing decisions.
3. ESG Compliance
Compliance with ESG, which stands for Environmental, Social, and Corporate Governance, is currently a complex and challenging regulatory environment for most businesses to navigate.
The effects of selecting the wrong vendor with unethical practices or practices that don’t align with your corporate values can have a significant impact on your brand reputation and customer loyalty.
But since ESG guidelines are contained within supplier contracts and agreements, your organization needs to be able to surface ESG data as part of the contract negotiation phase to determine applicability.
This becomes an erroneous, error-prone task for humans to review. Think about a company that needs to onboard 100 or more different suppliers and review their contracts for multiple items of which ESG is one and one contract can be 50 or more pages.
AI-driven OCR software can digitize manual contracts and proposals, enhancing searchability.
With Adlib’s Content Intelligence Cloud for Supply Chain, we can automate and deliver a high level of efficiency and productivity to; supplier discovery, supplier proposal and evaluation, supplier selection, contract negotiation, and supplier management.
An onboarding employee can then easily sift through countless pages by looking up keyword phrases in line with ESG requirements. You can quickly extract labor policies, sourcing details, tax strategies, political affiliations, and more, about a prospective partner company. That means processing up to 100 physical contracts or proposals rapidly and accurately.
4. Language Barrier
A global supply chain has roots in multiple countries. That means different cultures, speaking different languages, coming together to achieve common objectives.
Without a uniting language, a global supply chain can tumble like a pile of rocks or experience major delays.
A network involving less-English proficient countries like Japan, for example, can have huge issues working data up and down its ecosystem. In an EF EPI survey ranking countries according to proficiency in English, the country came in 55th out of 100 participants. Only 30% of the population knows English at any level.
In such a case, there would be a need for a translator at many data intake points, which inflates your company’s expenses.
Foreign language OCR software can solve data handling in a multinational chain.
Some OCR software are blending AI and supply chain management for utmost language convenience. These tools can read work text or images in Korean, Japanese, among other languages, and transfer the data to a universal format.
The translation algorithm can work through either one of statistical MT or rule-based machine translation. In statistical MT, which is the most common type, each sentence is broken down into parts. These segments are then compared to a data source, which contains a collection of source language phrases and their translations. After the translation of each part, the text is then stitched back together to get the desired output, which is the new language.
The software gets better and better at translation as it gains more data through machine learning. Some companies are already utilizing foreign and specialized OCR software to break down language barriers, and improve their productivity charts.
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5. Product Returns
If you’ve managed a global supply chain for a while, you know that product returns are as certain as taxes.
Customers may not be happy with what they’ve received for a variety of reasons. Perhaps the product was damaged during handling in the supply chain. Maybe, what the customer order is not what he received at all.
Whatever the reason, customer-triggered product returns will come up.
Product returns are especially high in an e-commerce network that is fueled by online purchases, which is what most global supply chains rely on. According to an Invesp survey, more than 30% of online products are returned.
Artificial intelligence solutions not only manage product returns but also prevent them in the first place.
OCR software, through machine vision, can detect what’s inside a package.
If an item that needs to be in the package is not, the OCR technology, working with a larger audio or visual notification system, can bring this to the attention of an overseer.
This problem is detectable when the OCR algorithm output varies from the preceding results. The change in output then triggers a system response, could be flashing lights or alarm bells, etc. Additionally, your workers can use OCR scanners to check the condition and details of returned items.
This information helps to return the item to its point of shipping for restocking, repair, or replacement.
6. Transport Co-ordination
Does your company buy all the trucks and shipping freights to facilitate global transportation?
Probably not. Most businesses use third-party transportation options to coordinate the movement of goods from the warehouse to the customer, across borders.
You probably rely on outside containers, trucks, and drivers for transportation.
Outbound deliveries can get mixed up, the same goes for loading information as well, leading to deliveries in the wrong vehicles. Invesp survey findings show that 23% of people who return products do so because of receiving the wrong order. Most of the time, you can pinpoint the mix-up to poor loading and transport coordination.
Therefore, implement AI for supply chain management by OCR plate tracking.
The software can scan vehicle registrations ensuring goods are loaded onto the right trucks.
Typically, multiple cameras are mounted at a scanning point to capture vehicles coming in from different positions. First, the still image is captured by a front-end device like a closed-circuit television. Then, using computer vision, the individual characters that make up the registration plate are separated or segmented. Each character is then processed into a machine-readable language for analysis, as guided by an OCR algorithm.
After processing, the data is then reworked back into an alphanumeric text, which is displayed on an output device, usually a monitor. At this point, the vehicle’s plate is automatically linked to the details of the driver or the goods in transit. This personally identifiable information is sourced from a pre-existing database.
AI-driven, plate-tracking OCR systems are already in implementation in various business sectors.
Conclusion
Do any of these supply chain problems sound familiar?
If they do, it’s time to seriously consider artificial intelligence application in supply chain management.
Relying heavily on human effort and accuracy in supply networks is risky.
People make mistakes sooner or later. Data is transferred inaccurately to a central system that you, and many other managers, reference when making crucial budget-influencing judgments.
You can get around supply chain headaches by using Content Intelligence Cloud for Supply Chain Management equipped with optical character recognition technology.
The applications of AI and supply chain success go hand in hand.
Make your global supply chain smoother, better, faster, and more reliable by implementing Content Intelligence Cloud for Supply Chain Management
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About Adlib Software:
Adlib Software unlocks insights hidden within unstructured data to accelerate digital transformation. Our purpose is to create intelligent data that amplifies human potential and maximizes business performance. Adlib’s AI powered Contract Analytics platform elevates unstructured data into business intelligence
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