Automated Data Capture for Businesses: Benefits and Methods
With continuing advancements in technology, digitization has penetrated all spheres of business. The amount of data in the world is growing exponentially, but the majority of data being created every day is unstructured. Whether it’s text, audio, or video, big data, if well collected, recognized, and processed, can be utilized to drive business success through leveraging modern technologies.
However, no matter how intelligent a machine is, it cannot absorb and interpret data the way humans do through the senses. Data is needed in digitized form for AI-based solutions to comprehend and process it.
What is Automated Data Capture?
Automated data capture involves extracting data from documents using machines and then transforming it into data readable by a computer. Machine learning and AI programming allow the software to read and translate images and paper files and turn them into easily accessible digital files. Automated data collection allows businesses to streamline their document management, among other benefits.
Benefits of Automated Data Capture
- Faster turnaround times
Processing speed is probably the most important benefit of automated data capture. Imagine the time it would take to manually process, proofread and mail out medical claims, or how a nightclub bouncer would have a difficult time trying to verify the age of a customer by looking at them. With ID scanning software, such a process would take a few seconds.
- Reduced errors
There is the danger of inevitable human error when entering data manually. No matter how good a person is, mistakes can still happen. However, during automated data processing, optical character recognition and artificial intelligence help to alleviate these mistakes. Data collection software can swiftly scan through documents and compare them to templates and other files to ensure data is complete and things like names, gender, and date of birth are accurate on sensitive documents.
- Enhanced efficiency
Another benefit of automated data collection systems is that they simplify complex tasks, which helps to increase efficiency. Replacing physical files with digital files also serves to eliminate clutter in the workplace and makes all files accessible to authorized persons at all times and from any device.
- Cost savings
Many businesses and organizations have turned to automation due to its cost-saving benefits. With automation, you can eliminate costs related to ongoing training, equipment maintenance, extra labor, document storage, and system updates. For instance, the U.S. Treasury says it uses 35 cents to process an electronic tax return, while a paper tax return costs up to three dollars.
- Improve employee satisfaction
Outdated manual processes such as prolonged data entry are mentally and physically taxing, and it is difficult for employees to focus on such arduous tasks for long periods of time. Automating these processes helps employees to focus on useful and more engaging tasks.
Methods of automated data capture
There is no one-size-fits-all automated data capture system. They come in different methods and forms that change depending on the unique needs of a business. Also, the level of automation and character recognition can change to meet certain requirements. Below are the most common automated data capture methods.
- Optical character recognition (OCR)
Optical character recognition was the first revolutionary technology in automated data capture. It is used to convert typed documents, images, PDF files, or scanned documents into searchable, editable digital documents.
Since the 1990s, OCR has helped businesses and organizations in various sectors, including logistics, healthcare, finance, and governments, to digitize their files accurately. Optical character recognition is extremely useful for sectors dealing with sensitive information such as medical claims and patient information.
- Optical mark recognition (OMR)
Optical mark recognition is another excellent way to manage documents. This technology does not recognize characters but scans documents for marks such as checkmarks and filled-in bubbles. OCR is commonly used to accelerate and facilitate capturing of human-marked details like multiple-choice tests, consumer feedback or survey, symptoms checklists, and poll results.
- Intelligent character recognition (ICR)
ICR technology focuses on solving complex challenges. It uses machine learning to teach machines to comprehend handwritten documents. While the accuracy is not that high, ICR can save plenty of time processing handwritten documents.
- Intelligent document recognition (IDR)
Intelligent document recognition (IDR) is like a complex type of optical character recognition (OCR). It is a highly sensitive and accurate method of capturing data from any part of a document, including the meta description. IDR is used to extract data from unstructured documents such as delivery notes, medical forms, and invoices. This method is capable of interpreting tables, patterns, and content in both electronic and paper formats, recognizing the start and the end of a document, and sorting documents according to their category. IDR is commonly used in mailrooms, legal, logistics, and accounting companies.
- Voice recognition
If you have Cortana, Google Assistant, Siri, or Alexa, you are already using some type of voice recognition. Voice recognition technology uses natural language processing (NLP) and deep learning algorithms to recognize and comprehend voice patterns. Voice recognition technology has countless applications, especially when combined with smart chatbot technologies. They can provide excellent customer support, services, and security.
- Face recognition
Face recognition has been a revolutionary technology with a wide range of applications. From simple applications like tagging your friends on social media to security applications like unlocking phones and airport security checks, this technology is incredibly useful. Face recognition comprises three steps which include detection, capture, and matching. Businesses can use face recognition technology to enhance building security, match databases, biometric identification, and sentiment analysis for retail.
- Magnetic ink character recognition (MICR)
Magnetic ink character recognition technology is used to recognize specially formatted characters printed in magnetic ink. It is commonly used in banks to accelerate the processing of checks and other documents. The good thing with this technology is that people can read the data as well.
Checkout about Machine Learning: Everything you Need to Know
Among the benefits of automated data collection include faster turnaround times, cost-saving, minimal human errors, improved consumer experience, and improved employee satisfaction. Businesses should adopt automated data collection systems to realize these benefits and help them generate business value and improve profits in today’s competitive business environment.
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