Logistics and supply chain companies constantly strive to ensure prompt delivery and consumer satisfaction amidst rising competition. In addition, the logistics and supply chain industry needs to handle large volumes of data that must be processed amid tight deadlines.
Document processing is a crucial yet tedious and costly task in logistics operations. Traditionally, the process involves manual data extraction and paperwork.
However, it is a complex method and also vulnerable to errors if handled manually. Moreover, industry regulations make it practically hard to systemize document processing end-to-end through traditional methods.
Using AI-powered OCR in the supply chain helps the industry to make document processing easier and more accurate.
OCR technology expedites the supply chain workflow with accurate information. From commercial invoices to bills of lading and customs documents, OCR helps handle the high data volume and format complexity.
The research report by Transparency Market Research states that the global OCR market is estimated to grow at a CAGR of 15.2% from 2020 to 2030. It also mentions that the increased use of OCR tools in the logistics industry is driving the significant market growth.
Overall, OCR significantly minimizes human intervention in document processing. As a result, it minimizes downtime as well as reduces operational costs. Furthermore, automation streamlines critical document processing and accelerates tedious tasks, saving both time and money.
In the upcoming sections of this article, you will get a brief outlook on OCR in the supply chain. We will also discuss the implications, benefits, and use cases of OCR technology in the logistics and supply chain industry.
First, let us understand what OCR is in the supply chain.
OCR is an acronym for Optical Character Recognition. It is primarily a tool with text recognition technology backed by AI capabilities.
The tool flawlessly extracts text from images, handwritten or printed copies. It also converts the data into searchable, machine-readable, and editable formats that can be processed to gain insights.
OCR reads everything from the scanned material, such as characters, letters, words, phrases, and patterns.
However, OCR captures the data following the below four steps:
OCR can help businesses across all industries in optimizing their supply chain and logistics operations.
Undeniably, warehousing, shipping, trucking, transportation, and other industries involving large volumes of paperwork can benefit from OCR and AI-based tools.
OCR in supply chain management allows businesses to effortlessly overcome the gridlocks of document processing:
OCR improves document processing in the supply chain industry by creating high-quality digital versions of essential documents. In addition, it makes data access and sharing easier for all stakeholders.
The key benefits of using OCR in supply chain and logistics businesses are:
According to a case study by Deloitte, DHL Supply Chain increased productivity by automating their invoice processing for 124 vendors. The technology helped extract 98.9% of characters from Dutch and English documents correctly.
OCR uses AI and cognitive technology for automatically reading and capturing data from logistics documents. It streamlines various processes, including generating accurate reports, tracking shipments, and even processing payments.
The typical applications of OCR in the supply chain and logistics industry are
When the seller creates the invoice, it is a crucial tool for confirming the packages are in line with the order placed.
It serves as a binding legal agreement between the shipper and the carrier. According to the terms and circumstances of this legal agreement, the shipment must arrive at its destination.
POD documents typically include information such as the date and time of delivery, the name of the recipient, and a description of the items that were delivered. Some POD documents may also include signatures from both the sender and the recipient and witnesses.
Customs authorities require it before they allow the shipment to enter the country. In addition, COI may be mandatory for a few specific categories of products like industrial equipment, perishable goods, and meat.
The certificate serves as a declaration by the exporter to satisfy trade or customs requirements, as well as a declaration of the product's nationality.
The insurance firms or authorized brokers that provide the required risk insurance coverage issue the insurance certificate as proof of coverage.
An ASN is used to inform the receiver when shipping occurs and to provide physical details about the cargo. The recipient can then get ready to accept the delivery that is on the way.
A delivery docket gives the seller a better understanding of the shipped goods and enables buyers to verify if they have received the goods for which they have made payment.
By signing the Dangerous Goods Declaration, the shipper certifies that the packaging complies with all local, state, federal, and international regulations regarding the transportation of dangerous goods.
OCR tools can automate document processing in the logistics industry and improve data handling. Several OCR tools are available in the market, each of which fulfills a specific purpose.
Depending on your business needs, you can pick from the best OCR tools for the supply chain industry:
Butler Labs combines OCR and AI to make it feasible to extract information from any logistics document reliably. The tool accurately extracts data from printed text and even scans handwriting using recent developments in NLP and computer vision.
Butler Labs offers the best tool with OCR in the supply chain to easily manage files with many variations and those containing tabular data.
Klippa is an Intelligent Document Processing (IDP) system that blends cutting-edge AI technology with OCR. It can extract, classify, anonymize, and scan data from logistics documents.
Klippa DocHorizon helps extract data, categorize documents, anonymize sensitive information, and turn documents into searchable files.
Amazon Textract transforms handwritten papers into electronic format and matches handwritten notes with digital alphabets and characters.
It automatically extracts data from scanned papers using the Amazon Textract machine learning service.
Document AI (DocAI), one of the products in the Google Cloud AI suite, is a document processing interface. It utilizes machine learning to identify, extract, and enrich data from documents automatically.
Users can get insights, apply data validation, add human reviews, and use custom parsing features to increase the precision of data extraction for AI models.
OCR in the supply chain brings automation to document processing and helps logistics and supply chain companies witness exponential growth. It allows faster processing of semi-structured and unstructured documents.
Besides saving resources, the high levels of precision lead to more satisfied customers and lesser compliance issues.
The innovative technology offers a competitive advantage by automating end-to-end management and minimizing human efforts.
Leverage the cognitive abilities of OCR to bring about significant improvements in your supply chain business. Try Butler Labs Document AI tool for free today.