Whether it’s CRM software used to track sales, ERP software for streamlining production, email software for tracking communication, advertising software used for marketing (Meta ads, LinkedIn ads, Google ads, Bing ads, etc.), or other third-party apps for streamlining business operations—organizations have customer data dispersed across a myriad of platforms.

According to Statista, the total amount of data created, copied, and consumed globally had already reached 64.2 zettabytes in 2020. The same is expected to reach more than 180 zettabytes by 2025. Organizations tapping into data-driven decision-making to pull ahead of the competition have to collect these vast amounts of data produced and extract intelligence using data analysis.

As evident, the amount of data being produced in the world is growing exponentially, but the majority of it is unstructured which makes it unfit for business consumption. Keeping a record of all the differences and working on extracting information can be extremely time-consuming.

Whether it’s the image, audio, video, text, or big data, when well collected, organized, and processed can be used to drive business success and growth through leveraging modern technologies such as Robotic Process Automation, Artificial Intelligence, and Machine Learning. Growth-focused companies understand that data collection lays the foundation for the data processing and analysis stage; thus, they automate their data aggregation process to accelerate their time to value.

The Automation Advantage

Remember cash registers where each product had to be entered manually by employees? Take another example of supply chains where passing an item from one level to the next of the chain meant filling in a ridiculous amount of paperwork. These manual tasks were made easy with the help of barcode scanners—one of the first examples of data capture systems that accelerated item identification and processing.

However, the world has now moved beyond data collection devices such as RFID readers or barcode scanners into fully automated data collection systems and smart data capture solutions. These automatic data capture platforms take all of a company’s data sources such as CRMs, ERPs, advertising software, emails, accounting software, etc., and extract valuable information without the need for a programmer to do the coding-decoding.

Smart data transformation solutions combine human expertise with AI, ML, and RPA. Hence, whether you have public or proprietary data in a raw unorganized format, automatic solutions can help you transform them into tagged and schema-compliant structured XML for data products, analytics, and AI/ML applications.

Automated Data Capture Methods

Automated data capture systems come in different methods and forms that change based on the unique needs of a business. Additionally, the level of automation can be changed to meet certain character recognition requirements. Listed below are some of the most common automated data capture methods:

• Optical Character Recognition (OCR)

As the first revolutionary technology in automated data capture, Optical Character Recognition is used to convert typed documents, PDF files, images, or scanned documents into editable, searchable, digital documents.

Since the 1990s, OCR has helped companies across multiple sectors including healthcare, finance, logistics, and governments, to digitize their files accurately. It is extremely helpful for sectors dealing with sensitive information such as patient information and medical claims.

• Optical Mark Recognition (OMR)

This is another excellent way to manage all the documents. Optical Mark Recognition not only recognizes characters but also scans documents for marks such as filled-in bubbles and checkmarks. OMR is commonly used to expedite and facilitate capturing of human-marked details including consumer feedback or surveys, multiple-choice tests, symptoms checklists, poll results, etc.

• Intelligent Character Recognition (ICR)

Intelligent Character Recognition technology leverages Machine Learning to teach machines to comprehend handwritten documents and focuses on solving complex challenges. Though the accuracy offered is not that high, ICR can save significant time processing handwritten documents.

• Intelligent Document Recognition (IDR)

Intelligent Document Recognition is a highly sensitive and accurate data capture method from any part of a document, including the tags and meta description. It is more like a complex type of Optical Character Recognition, which is used to extract data from unstructured documents such as medical forms, delivery notes, and invoices.

Additionally, IDR is capable of interpreting patterns, tables, and content in both paper and electronic formats, recognizing the start and the end of a document, as well as sorting documents according to their category. This method is commonly used in legal, logistics, mailrooms, and accounting companies.

• Voice Recognition

If you have Siri, Alexa, Cortana, or Google Assistant, you are already using some type of voice recognition algorithm. Voice Recognition technology leverages Natural Language Processing (NLP) embedded in Deep Learning algorithms to recognize and comprehend different voice patterns. It has countless applications when combined with smart chatbot technologies as they can provide excellent customer service, support, and security.

• Magnetic Ink Character Recognition (MICR)

Magnetic Ink Character Recognition Technology is used to identify specially formatted characters printed in magnetic ink. This is commonly used in banks to speed up the processing of checks and other documents. One of the good things about this technology is that people can read the data as well.

Benefits of Automated Data Capture

• Faster Turnaround Times

Processing speed is one of the unavoidable benefits of automated data capture. Imagine how a nightclub bouncer would have a difficult time trying to verify the age of a customer by looking at them or the time it would take to manually process, proofread and mail out medical claims. With ID scanning software, this process would take a few seconds.

• Minimized Errors

Manual data entry includes high chances of human error. However, you can easily avoid these mistakes with automated data processing as the smart data collection software can swiftly scan through documents. They can compare these documents to templates and other files to assure data is complete and things such as names, gender, and date of birth are accurate on sensitive documents.

• Boosted Efficiency

With automated data collection systems at your disposal, you can simplify complex tasks that in turn help you to increase efficiency. Besides, replacing physical files with digital files serves to eliminate workplace clutter and makes all files accessible to authorized persons from any device and at all times.

• Cost Savings

Numerous organizations have turned to automation because of its cost-saving benefits. You can eliminate costs related to ongoing training, extra labor, equipment maintenance, document storage, and system updates with automation.

• Greater Employee Satisfaction

Outdated manual processes like prolonged data entry are both mentally and physically taxing, which makes it difficult for employees to focus on such arduous tasks for a long duration. Automating such processes facilitates employees to better focus on more engaging tasks or core competencies.  

Endnote

Among the benefits of automated data capture solutions include faster turnaround times, cost-optimization, reduced human errors, enhanced customer experience, and greater employee satisfaction.

The Statista reports proved the same as most respondents agreed that automation reduced the risk of equipment failure, performance issues, data breaches, and regulatory compliance violations, as of 2021. At the same time, 50 percent of respondents agreed that automation processes give more space to the IT staff to focus on strategic initiatives. Hence, you already know what to do next.