How OCR and NLP are Transforming the Supply Chain Industry to Automate Data Extraction
Jul 7, 2022
In today’s stiffly competitive world of business, utilizing the right technological solutions has become a necessity. More the business processes are automated, better the overall business performance, making businesses inclined toward digital transformation. There are countless ways, a business can automate business processes and digitally transform the processes. But one of the remarkable ways to digitally transform any business is by knowing the capability of the business to extract data from the physical world and input it into digital systems.
There are businesses and industries that generate hundreds of thousands of documents every day, and the supply chain is no exception. There’s a lot of valuable information that needs to be captured and used in analysis and for various other purposes. Thanks to some advancement in technologies such as OCR and NLP, extracting and sourcing data from multiple files has become easier than ever before. This, in turn, has completely changed the way supply chain and other industries used to operate, almost eliminating the human effort, and streamlining the data extraction process.
Creating Meaning out of Extracted Data
Over the years, the focus of the supply chain industry has changed from simple data extraction to an intelligent and meaningful one. It takes care of various aspects, a lot more than just simply extracting the data from the source. It helps in carefully analyzing the data, and more importantly, creating some meaning out of it. Intelligent data extraction in supply chain helps in extracting the data from various digital assets such as scanned images, documents, text files, and more. This unstructured data can be converted into usable formats through data extraction templates and defined rules.
As most of the data that is generated by businesses is unstructured, there’s a need for a robust technology that can allow businesses to transform this data into a structured and usable one. Intelligent data extraction makes the entire data extraction process streamlined while transforming the data into reliable and useful information.
How do OCR and NLP Work?
Contextually understanding the meaning of the data and optimal usage of inputs (including texts, numbers as well as special characters) has become possible with the help of Artificial Intelligence techniques such as Machine Learning (ML), Natural Language Processing (NLP) and Optical Character Recognition (OCR). This empowers systems with the capabilities to map the values of their keys and organize the data into structured formats. The final result is a structured and organized ocument that is all set for analysis, and it hardly takes 20-25% of human intervention. It works wonders in two different ways, it automates the processes that contain unstructured data, and it also allows you to run rich analytics on this structured data.
Empowering the Supply Chain in Various Ways
Making it easy to convert your documents into structured data.
This structured data is then utilized to automate the business processes.
Without asking for too much human effort, you get data analytics and actionable insights on top of your unstructured data.
Context and sentiments can be analyzed with the help of automated rich text data analysis.
Let’s Eliminate the Challenges
Most of the documents are available in image formats, and this is where information extraction becomes a little difficult. There are randomly occurring black and white grains, pen scribbles, dark backgrounds, watermarks, and faded inks, all these are a few of those various data extraction challenges.
There may be or may not be some grid lines in the table, again can be difficult with merged and split cells. There can be some unclear boundaries and some clear character separations can make it difficult to extract data from the documents that are handwritten.
In numerous ways and cases, you can find NLP and OCR being implemented in the supply chain. The benefits of which can be easily identified in various departments of the supply chain including procurement, warehouse, and logistics to manufacturing, and inventory management.
How UBIAI can Help?
Organizing these semi-structured documents and feeding them to the system can take hours of human effort. This is where UBIAI comes out to play. With very little human power, intelligent data extraction with the help of OCR can help in capturing the data from invoices and other documents, reduce the chances of human errors and improve the quality of overall work.
When you have a bunch of disorganized data such as invoices or contracts, UBIAI helps train the high-performance model by preserving the document layout.
UBIAI significantly improves the performance of your NLP model. It combines computer vision as well as NLP, enabling you to perform relation extraction, and NER while classifying annotation directly on native PDF documents, all without losing any vital information.
From Japanese, and Spanish to Arabic and Russian, UBIAI supports annotation for more than 20 languages.
The Bottom Line
How to create efficiency in supply chain management is one of the most common questions asked by suppliers, distributors, and manufacturers. This key question is what UBIAI answers with total accuracy.
The bottom line here is to create efficiency and smoothness in the supply chain management processes with the help of the right tools and solutions.
So, now that you have realized that UBIAI’s tool can be implemented in the supply chain in various ways and it has countless benefits to offer, it’s time to connect with the dedicated professionals who will help you from concept to completion. If you want to make the most out of your supply chain management processes, then connect with UBIAI and discuss all your needs with them so that they can help you deal with your business challenges and do the right implementation.
What are you waiting for? Visit Ubiai.tools now.