Is There Any Difference Between Data Capture And Data Entry?

Document management in an organization involves diverse processes such as document conversion, imaging, scanning, indexing, data entry and capturing. Often there’s confusion between data entry and data capture, whether they serve different functions or the same.

Data entry refers to entering or transferring data such as text and numbers from manual records to a digital database or an electronic system. Even with the availability of advanced technologies and software products, this process mainly relies on human intelligence. Even though software can be deployed to read and convert data, the final stage of quality checking is done by humans. As this task comes in bulk, most companies prefer data entry outsourcing to get the process done on time and without any errors.

Though data capture is very similar to data entry, it is the process of collecting and transforming information from paper or electronic documents into data that can be understood by computers. but used mostly on data sources that contain basic response types. This process in mainly useful to capture data from multiple choice forms and documents and similar survey forms. This task which is done by software and automated data capture, is the process of extracting information from a scanned or digital document and turning it into data that is readable by a system.

The data capture process involves document scanning and converting the file to the required format and using data capture software to automatically capture the information within seconds into a compatible digital format. Once this process is done, the data is easily exported to a spreadsheet or other indexing format based on the storing or sharing requirements. There are numerous data capture methods that can be used to capture key information from surveys, invoices, claim forms, unstructured documents and other document types.

Some of the most common data capture methods are –

• Manual Method – This method is ideal only for low volume data, as the job is time-consuming and labor-intensive.
• Optical Character Recognition (OCR) – This method helps in capturing low to high volumes of data – image files, PDF or any scanned paper documents and converting them into editable data.
• Intelligent Character Recognition (ICR) – This method works better for high-volume invoice processing and helps capturing handwritten printed characters from image files.
• Voice-Recognition – This automated data capture method converts speech into text. Now many applications and devices like Apple (Siri) and Google (Google Assistant) are available for voice data capture in businesses.
• Optical Mark Reading (OMR) – This method is used to capture data through boxes that are checked manually on documents such as forms and surveys.
• IDR (Intelligent Document Recognition) – This method interprets and indexes different documents such as invoices, letters and contracts based on the document type, meta data and other elements of the document identified.

For choosing the right data capture method for your business, consider – identifying your business’ data collection requirements and choosing the right method, implementing multiple methods based on the data you handle, making sure that the chosen method keeps your data safe and secure, and ensuring that the method chosen helps avoid duplication.

When implementing a data capture strategy, you may face diverse challenges including fundamental issues such as missing pages, spelling mistakes, blank fields, wrong variables and any issues with the setup of the forms. Any error during capture can lead to collection of inaccurate data.

We’ll discuss some key tips for optimal data capture in our next blog.