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7 Things to Consider When Choosing an OCR/IDP Solution

Apr 27, 2021 | 5 min read

Intelligent Document Processing (IDP) is an Intelligent Automation concept that many businesses are familiar with, and it is something that corporate functions have been doing regularly for many years.

It’s a method of converting unstructured files, such as scanned invoices, forms, surveys, hand-written prescriptions, images, and unstructured PDF documents, into accessible structured data. Document processing activities are typically manual and tedious, and because of the high number of documents obtained, they become labor-consuming and frequently unrewarding for workers.


In remote systems, robots have a hard time interpreting objects like buttons and text fields. That is why some robots have Optical Character Recognition (OCR) and Intelligent Document Processing (IDP). With these, RPA can read, extract, and process data from several different unstructured document formats, allowing it to be used in automated business processes without the need for human intervention.

This is especially important as most organizations receive herculean amounts of semi-structured and unstructured files, such as invoices, sales orders, policy forms, and customer communications, that basic rule-based automation software can’t completely process.

RPA’s success today is largely due to sophisticated cognitive layers such as optical character recognition, NLP, and other AI-based applications. In recent years, robots have become more perceptive, but we are still years away from robots that can make highly complex decisions without human intervention.


With a variety of OCR/IDP solutions in the market, we bring you the 7 most important things to consider when looking for the solution best suited to your business:

1. Find a solution that can handle different types of documents

Find an OCR/IDP solution that reads documents in phrases to understand the underlying content and meaning, and tests precision at the field level, in addition to processing a variety of documents and text inputs as well as images of differing quality as they reach the device.

Make sure the solution you’re implementing can handle different languages and different types of text, like handwritten, cursive, printed, and mixed entries. Also, that it can improve image quality so it can extract data from low-resolution or distorted images. Don’t forget to review the rate of accuracy it has for different document types.

2. Look for a solution that is easy to set up and use

Look for an OCR/IDP system with a user interface that makes it easy for non-technical workers to set up and customize use cases, build new formats, and monitor organizational success metrics. Users should be able to easily build templates and describe and add new fields for extraction at any time with the right solution.

Make sure the solution has been put through user testing during its development,take into non-technical account users, and that is easy for the admin to create new groups and other frequent tasks.

3. Your solution needs to be within your existing infrastructure

When it comes to implementing new technology, one of the most common issues is how much of the existing infrastructure will need to be adapted, as well as whether workers will need to be educated in completely new technologies and workflows.

Prioritize procedures and projects that can have the most effect in the shortest amount of time, and then assist you in scaling up from there. It must be simple to set up, configure, and manage, with a scalable and stable API for integrations. Find a supplier who can help you fit the solution into your existing infrastructure.

Note that the solution should be simple to set up, execute, and manage. Do look at the available assurance tools to ensure consistency from the beginning and in the long term.

4. Look for a partner that has a vision for the future

The perfect solution provider will actively get involved in the real issues and suggest ways in which intelligent automation can fix the immediate problem whilst being mindful of potential issues in the future. Look for a vendor that will continue to invest in the research and development and remember that a future-proof vendor should have a robust product roadmap that they can share with you. Book a meeting with one of our automation experts and find out how we can help.

5. Find a solution that helps you improve your customer satisfaction

Better customer service is also the single differentiator that can make or break the retention and acquisition metrics in today’s ever-changing and highly challenging market environment.

Look for an OCR/IDP approach – and a technology provider – that can link data from extraction to conversion rates. Investigate whether there is evidence that payout rates match or surpass consumer needs as a result of the pace and accuracy of back-end record preparation and retrieval. Inquire about vendors’ rates of correct data entry automation and how their systems stop procedural errors from reaching consumers’ mailboxes and inboxes.

6. Look for a partner who understands the importance of delivering results

Work with suppliers to determine all the possible financial advantages of adopting their approach. A full ROI calculation can contain both obvious data points such as cost savings from fewer mistakes and manual operations and less obvious advantages such as lower churn rates. Learn how each IDP/OCR solution will link the product to faster response times, better customer experience, and more sales.

Finding opportunities to cut expenses, collect more data, and raise sales and benefits are among the objectives. The best IDP/OCR solution should show you how their product affects these KPIs with simple metrics.

7. Consider native integration and other capabilities that will help with your automation program

It’s no surprise that OCR and RPA are a winning match when it comes to automating a company’s everyday operations. Although OCR is used to identify and read data from a variety of sources, RPA aids in the proper distribution of the data to the appropriate organizational structures – Email, CRMs, ERPs, and other business applications.

The quality and accuracy of text recognition and native integration with RPA are critical factors that influence a project’s final performance. Machine Learning is also used in more sophisticated and complex OCR solutions, allowing the efficacy of text recognition to increase over time as the load of document processing grows.

Organizations that still rely heavily on scanned paperwork should use OCR with RPA to simplify their processes and boost operational efficiency for a larger portion of their business needs. As a result, when contemplating business process automation, it’s essential to explore vendors with strong integration capabilities into RPA platforms.

What tools are there?

See below the comparison of the features and performance areas for the top IDP/OCR tools we identified in the market, to help you make the best choice when implementing OCR capabilities into your business:

Businesses spend a significant amount of time interpreting, learning, and processing documents daily. OCR technologies can save companies money and resources, as well as reduce cost and increase productivity when combined with RPA.

Roboyo’s technology partner network includes ABBYY, UiPath Document Understanding, and Hyperscience – the world’s leading OCR and Intelligent Document Processing (IDP) platforms to ensure we can leverage the best data capturing and processing solutions for our customers throughout their digital transformation journey.

Speak to one of our Automation Engineers today and find out more.

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