Optical Character Recognition (OCR) is an automated process that converts text-based images into computer-ready text that you can then edit and manipulate. It’s a faster way of capturing data that works by scanning documents and converting them into text, and pushing extracting data directly into a database or third-party software.
What is OCR? How is it better than manual data entry? Are there any better alternatives to this technology? - We’ll answer all the questions in this article.
So, let’s jump right into it:-
Processing documents manually is slow, tedious, and extremely expensive - businesses must continually develop innovative ways to combat costs and streamline operational processes. Great deal of text-based information is locked in physical formats that are not easily accessed for analytics. That is until you unleash the power of Optical Character Recognition (OCR). OCR is revolutionizing how companies collect data from physical documents and making the data accessible.
Traditional data capture is slow, tedious, and expensive. It's also prone to human error. Companies that OCR technologies primarily serve well are process payroll and admin tasks. They can reduce the number of forms they have to fill out and speed up their submission process.
Manual data entry is the process of entering information from a paper document or image file into a computer application. The manual way of sorting through and data entry can quickly become a bottleneck for companies that are trying to scale their operations.
There are many challenges associated with manual data entry including:=
On the other hand, automated OCR data capture can identify, extract, and classify useful information from documents. Amongst other advantages of OCR over manual data entry, the most significant benefit is speed. OCR is fast, accurate, and more reliable to handle your data entry needs.
Automated OCR software is more convenient as it does not require any intervention on the user's part for its operation. Compared with manual data entry, automatic OCR systems are more economical because of the same reason.
Automated OCR data entry can instantly turn your product information into computer-readable text that shopping carts and other online systems can use. OCR software reads the text directly from images of items and then converts it into usable information, allowing you to quickly and easily upload it.
OCR is far from perfect, and even the most basic text recognition software isn't infallible. For instance:
While OCR may be adequate for an occasional task, IDP offers the ability to manage high volumes of complex documents with greater efficiency and accuracy.
Here are the reasons why IDP is a better alternative than OCR:
When it comes to accuracy, OCR systems don't come close to what IDPs can do.
Here is an overview of the comparison between OCR and IDP:-
Automated data capture is a core strategy for improving your conversion rates. If you're interested in automating your form processing, you'll want to take a look at Docsumo's software. It's a powerful tool that can help you leverage OCR (Optical Character Recognition) and Machine Learning(ML) technologies to extract and process data from forms automatically.
Automated form processing can save you hours of manual data entry, lower your costs, and more.
You can upload documents that contain information about your customer profiles, like customer names and addresses.
To ensure accuracy in your data entry, remember to double-check all fields for accuracy. For example, if the parser classifies a data field incorrectly, make sure to fix it.
If there are any errors in the information you are capturing on the form, be sure to fix them before moving on to the next step.
Once you have captured every piece of information on your form, it's time to review and approve it before moving on to the next step. This ensures that every last part of the information is accurate and there are no errors before uploading it.
Docsumo lets you download the data in CSV/Excel/JSON formats for post-processing and analytics.
Automated data capture is beginning to gain traction and is helping businesses around the world deal more effectively with their ever-increasing workloads. With so many data capture solutions available in the market, it can be overwhelming to choose the right one for your business. We hope that this resource provides you with a better understanding of OCR so that you can make an informed decision about the technology for your next implementation.
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
Optical Character Recognition (OCR) is the technology to convert an image of text into machine-readable text. It is the underlying technology for various data extraction solutions including Intelligent Document Processing. However, OCR is not smart enough to figure out the context in a document - it works simply by distinguishing text pixels from the background and finding a pattern. This limitation could cause inaccuracy in captured data that could directly impact the output of your data extraction model.
Accounts payable is a key financial function for any business. Corporations can have thousands of suppliers; even for relatively smaller businesses, the number of suppliers could be in hundreds. All the invoices they receive from these suppliers come in multiple formats, layouts, and templates - some semi-structured, some unstructured. Therefore, firms expend time and resources to capture invoice information through manual data entry and verification of accounts payable. Manual data entry is not feasible in the long run, definitely not on a large scale. Before we talk about how intelligent invoicing solves the problems associated with manual invoicing, let’s discuss the challenges in much detail.
As most of an organization's information is available in an unstructured format, processing it requires an automated system that can handle documents with minimum human interaction. OCR is one such technology, but its scope is limited as it requires human interaction and is highly dependent on the layout and structure of the document to be processed.These limitations are overcome by Intelligent Data Extraction.Using artificial intelligence, the Intelligent Data Extraction technology extracts data from documents and transforms it into useful information through the extraction process. It functions as a singular tool for extracting information from any type of document and aids in optimizing company operations.