Many enterprises have embraced digital technologies within their business practices and processes. And since digital technologies rely on technology and data, they can transform traditional processes, improve customer experience, and reduce costs.  

Data is becoming very important to the growth and success of a business. Thus, an enterprise must have accurate and quality data. Various tools can help an enterprise collect and analyze different kinds of data to help organizations. Below is a short overview of data capture:

What Is Data Capture?

Data capture refers to extracting information from various data sources and converting them into data that a computer can read. This process typically involves scanning documents – both physical and already in digital format in order to provide businesses with standardised and digitised data that can be stored more securely and accessed more efficiently. Data capture is becoming increasingly important as enterprises embrace digital transformation within their organizations.

To keep up with the increasing need to improve customer experience and access to accurate data, enterprises use various data capture technologies to help simplify the process of collecting data. For example, some enterprises use document scanners for mid-sized businesses to upload the documents that need to be digitized. Companies today are driven by data, and any technology that makes it easier to capture data is always invaluable.

Data Capture Technology

Data capture technology (also called data capture solutions) can help transform how an enterprise collects and analyzes data. Some data capture solutions leverage Artificial Intelligence capabilities to help gain insight and identify patterns in the data. An intelligent data capture technology can also handle different formats, such as XLS, PFD, TIF, DOC. 

A system like this means you can receive document images from various sources your company receives from partners, whether they use their delivery method or the more standard FTP (file transfer protocol), fax, or email.

Automated Data Capture Technology

Automated data capture leverages AI and machine learning (ML) capabilities to capture, translate, and manage data. The automated data capture technologies can help a business reduce inaccuracies and costs associated with collecting and analyzing data. Some of these automated data capturing technologies are discussed below:

Optical Character Recognition (OCR)

Optical Character Recognition (OCR) technology reads and converts text in documents into data that a computer can read. The technology can read text documents like text, images, etc. OCR can make data processing easier, more accessible, and faster. With OCR, there’s no need for manual data entry. The OCR technology is best suited for businesses that deal with a high volume of data.

Intelligent Document Recognition (IDR)

Intelligent Document Recognition (IDR) uses OCR and AI technology to detect and interpret different documents. IDR reads a document and uses its layout to determine which type of document it is. The IDR technology will then extract the content and identify the patterns in the document and classify them. The essential data from the document is then released within the organization’s systems for various purposes. 

IDR, in short, sorts your data for you. With this technology, you can scan any document type, and IDR will categorize it for you.

Intelligent Character Recognition (ICR)

Intelligent Character Recognition (ICR) is quite different from the OCR and IDR technologies. ICR scans handwritten documents and converts them to computer-readable data. The ICR software can detect and scan handwriting in any font and style.

The Optical Mark Reading (OMR)

Optical Mark Reading (OMR) technology uses a beam of light to detect answers on paper. It determines the markings on a document based on the amount of light that reflects the optical sensor. OMR can read markings made in pen or pencil on documents like surveys, exams, ballots, questionnaires, and tests. The technology has a high accuracy rate, and it can scan thousands of documents in an hour.  

These technologies provide more accurate information, making capturing data fast and effective. Data capture technology reduces the time and costs associated with manual data capture.

How To Choose The Right Data Capture Technology

Data capture technologies have different capabilities that could add value to an enterprise. Before selecting a data capture technology, an organization should consider several factors. First, they need to consider whether the technology is compatible with the business. Ensure that the technology selected can process the type of content in various formats. 

Choosing the right technology can save time and money in the long run. Moreover, think about the volume of data the business needs to process and convert before selecting a data capture software. And think about the cost associated with using a particular technology.

Benefits of Data Capture Technology

• Cost-effective. 
• The technology can provide insights from the data that can help improve business processes. 
• The process of collecting and analyzing data is easier and more accurate. 
• The technology makes editing, searching, and retrieving data easier.
• The technology can provide accurate data that can help make informed decisions. 
• Data capture technology can help determine the return on investment (ROI)
• The technology can help improve productivity and use fewer resources to process data faster.

Conclusion

As enterprises embrace digital transformation, many are moving away from manual to automated data capturing for improved accuracy, greater data accessibility, and reducing inaccuracies. Automated data capture technology creates an opportunity to improve productivity and eliminate redundancies within an organization. The different technologies are increasingly becoming tools to add value to an enterprise and change how they use data.