The Practical Applications of OCR in Business

Automatic document processing is a field of technology that focuses on the analysis and management of documents in electronic or paper form. The main goal of this technology is to improve the efficiency of work in organizations by optimizing processes related to documentation.

Document processing is based on advanced algorithms that allow for the recognition, classification and extraction of information and the transformation of data from paper documents into digital form.

There are several document processing technologies that are used for different purposes and tasks. Among them, we can distinguish two key approaches to processing data in documents: OCR (Optical Character Recognition) and IDR (Intelligent Document Recognition).

Both technologies have evolved with technological progress and the changing needs of enterprises, becoming an integral part of many document management systems.

In this article, we will look at OCR technology and its practical applications especially in business.

What is OCR?

OCR is a technology that uses advanced algorithms to recognize characters found on a digitized file. The abbreviation OCR comes from the English expression optical character recognition, meaning optical character recognition.

The program reads text from electronic documents, changes the data into digital form, and then imports it to the system available on the device. Thanks to this, scans and photos can be transformed into an editable text document.

OCR Software

The possibilities offered by this technology make it a popular choice for many office programs. The system that uses it enables intelligent electronic recognition, description, categorization, and digitization of documents.

For these reasons, it is useful, for example, when scanning and reading accounting invoices. What’s more, it recognizes not only printed but also handwritten writing, as well as tabular data or data placed in footers.

Thanks to such functionalities, OCR programming can recognize:

• full text of the entire document;
• data from structured documents;
• specific types of documents – systems collect data using artificial intelligence.

Key Benefits of OCR in Your Business

OCR software has many advantages.

First of all, it allows to significantly improve the work of many different departments of the organization – including accounting, HR, administration and finance. Thanks to this, employees save valuable time, which they can spend on performing key tasks.

The system allows for much faster entry of invoices into the system. By eliminating manual data entry, it leads to automation of document circulation and its acceleration. The system also allows for easy and convenient data entry and reduction of costs related to the use of equipment.

Thanks to the option of converting text in many different languages, OCR software can be used in various environments, such as convert PDF to DWG file. This technology improves the quality of data and reduces the number of errors in documents.

A big advantage of OCR in business is also the security of documents. Since they are stored in the clouds or on external drives – they cannot be lost or damaged.

OCR Use Cases in Business Processes

• Submitting Documents: OCR can be used in the process of converting paper documents into digital versions. This is especially useful in companies that store a large number of documents in paper form and want to organize them.
• Archiving and Indexing: In the process of archiving and indexing documents, OCR helps to convert paper documents into digital ones and automatically index the content, which facilitates later searching and access to documents.
• Invoice Processing: In finance departments, OCR is used to automatically recognize and process invoice data, such as invoice numbers, amounts, and dates. This speeds up the payment process and helps reduce the risk of human error.

In practice, OCR can be used in any industry, in our experience OCR is particularly useful in the following sectors:

• Financial: By supporting invoice processing and recognizing data on financial documents, OCR saves time spent on manual data rewriting into systems.

OCR Best Practices

Correctly formatted documents, error-free texts and seamless integration mean less pressure on all parties involved, creating an environment conducive to innovation and collaboration.

Achieving this level of quality requires care and consideration, but the results are worth the effort.

1. Before you start OCR, you need to prepare your document properly. A bad document condition can not only make it difficult for the software to work, but also lead to frustration during further processing.
2. Assess the quality of the source document. If it is in poor condition, work on improving it or request a better copy. Make sure the pages are flat, clean, and free of creases or stains.
3. Give the document a logical structure if it is missing. Number the pages, add headers and remove any unnecessary elements. A consistent presentation of the document significantly facilitates the work of OCR software.
4. Each OCR software has its own unique strengths and weaknesses. It’s crucial to analyze the specific needs of the project. Tools like SwifDoo PDF are excellent at PDF editing and converting – ideal for managing PDF documents. Simpler applications, on the other hand, can provide fast results but lack precision when dealing with complex text layouts or multiple languages.
5. OCR proofreading requires precision and patience. OCR inevitably makes mistakes; some letters or numbers may be incorrectly recognized, and punctuation may need to be corrected.
6. The best practice is to compare the original document with the OCR result, page by page. This may seem tedious, but neglecting this step can result in costly errors, especially in technical or legal documents.

In Conclusion

Digitization of business resources is currently a common practice. OCR is a solution to the problem of having to manually copy the content of often extensive documents when entering them into the system.

With OCR, characters and whole words, and even sentences, are recognized when uploading scanned documents, regardless of whether we are dealing with an image/photo or PDF format.

Thanks to this, we can easily obtain the entire text of the document, but also its automatic classification or extraction of detailed data.