Is OCR Really What You’re looking For?

We’re talking brick-shaped device vs smartphone. Both able to make phone calls. But, worlds apart. When optical character recognition – OCR – arrived on the scene, it was revolutionary. A miracle drug. For businesses running data entry and data capture processes, OCR automated data entry by scanning documents and converting the text into a machine-readable format. Hours were saved. Humans were freed from tedious, repetitive tasks. Manual data entry errors became a thing of the past. But, there are flies in the OCR ointment. Multiple types of data, lousy source material, etc. OCR vs IDP. Are you sure OCR is what you need?

What’s your automation story?

Let me guess.

I’ve worked in this industry for a year now and there are three scenarios that pop up regularly…

If it ain’t broken, don’t fix it, right?

First up, while swamped with paperwork, there’s a reluctance to take the leap to automation. Will I have to let go of my team? The cost is too high. I can’t convince my boss. So, your team is stuck doing manual data entry. Accuracy levels aren’t consistent. Productivity and efficiency are low. 

“The direct and indirect costs of manual, paper-based invoice processing amounts to $2.7 trillion for global businesses.”
2018 Goldman Sachs report

In the long term, the cost of doing nothing is high.

My OCR doesn’t live up to the hype

You invested in an automation solution because you were promised the moon. 100% accuracy and automation end to end. Regrettably, you’ve been sold a lemon. A sales rep in a shiny suit with an equally shiny smile blinded you with stats, jargon, and bullsh*t. Resulting in you owning a costly solution that doesn’t meet your automation needs. You’ve been burned.

OCR not working!

I think I know what OCR is, but…

You’re not fully confident in your understanding of what’s on offer. 

You’ve made the decision to splash the cash and invest in an automated document processing solution. You know that many businesses use OCR. Been around for decades so it must be good, right? It revolutionized data capture, saving companies bundles of money, time, and resources. So, it must tick all the boxes. What’s stopping you from taking the leap?

Optical character recognition = intelligent document processing? No. Keep reading.

OCR definition

Optical character definition is a process that scans an image of text and produces a machine-readable version. For example, if you scan a receipt, your computer saves the scan as an image file. You can’t edit or search the words in the image file. But, a software like Adobe Acrobat that uses OCR technology, converts the image into a text document with its contents stored as text data.  

OCR isn’t the bad guy in this. It does exactly what it was designed to do. And it does it well. Businesses have benefited hugely. But… it does have limitations. Limitations that are becoming more apparent as our eyes are opened to the power of artificial intelligence

OCR struggles with unstructured data. It doesn’t ‘get’ scanned data. The context. This means end-to-end document automation isn’t possible. And, to be brutally honest, if it’s not end to end, you can’t claim to have automated your document processing.

AI is advancing in leaps and bounds. Casting a shadow over OCR. If your business invested in OCR, you’re losing out. Time to examine how you use OCR and what you expect it to do. If you’re looking for end-to-end automation of your business processes, OCR can’t tick that box. If you’re looking for a document processing solution that learns from user feedback, improving over time. You’re gonna make OCR cry.

That said…

When OCR is the right choice

Don’t get me wrong. I don’t mean to rubbish OCR. There’s a reason it’s been around for so long. Its underlying principle remains the same – capturing data from images, text, and other sources and converting it into a machine-readable format. Using complex algorithms to analyze and identify characters in an image. Map them to their matching symbols. Then convert the scanned document into editable and searchable PDFs.

The advantages of OCR are not to be sniffed at…

  • Accuracy – OCR scanners are accurate and produce high-quality images
  • Speed – the scanning is fast, with large volumes of text processed quickly
  • Cost – it’s cheaper than employing a team to manually input data
  • Efficiency – OCR has transformed business operations

But…

Character matching is a simplistic form of automation. With matching often missing the mark. Introduce semi-structured or unstructured data and you’ll hit a brick wall. In case you’re unfamiliar with the different types of data…

  • Structured data has a standardized format for access by software and humans. Typically tabular, with rows and columns that clearly define data attributes.
  • Semi-structured data is a form of structured data, but doesn’t conform to a rigid schema or data model. It can contain elements that aren’t easy to categorize or classify. But, it contains tags and metadata to separate semantic elements and determine hierarchies of records and fields.
  • Unstructured data doesn’t have a predefined structure, i.e., it doesn’t sit in a row-column database. Text heavy, it’s found in emails, images, audio files, social media posts, web pages, video files, PDFs, and more. Why is it important? It’s packed with trends and insights that drive business-critical decisions, financial projects, and customer engagement.

Disadvantages of OCR

If OCR is so great, why is OCR so bad?

It’s not. It has many advantages. It’s just not enough of a solution on its own if you’re looking to automate your document processing. It must be part of an automation solution. Not the solution. 

OCR is clumsy when processing unstructured documents. It stumbles when trying to scan a document of dubious quality – faded, creased, watermarked, blurred – meaning accuracy levels are low. If your results are below par, you’ll need to bring the humans in to correct and validate the data. Those savings you made going for basic OCR software will be lost.

And the biggie… it doesn’t get the context of the document.

Yes, it converts text into a machine-readable format. If you want to automate the entire document processing workflow, you’ll need other tech. Robotic process automation – RPA, AI, IDP – intelligent document processing…

In a world where automation and integration are key, OCR is showing its age. Hindering businesses from achieving end-to-end automation.

Until… machine learning technology showed its face. ML-enhanced OCR – AI powered – ups its game. The AI OCR software can read the data, while the ML translates and brings context to the data. It can work with semi-structured and unstructured data. Becoming more accurate over time.

  • Accuracy is increased as the software learns to recognize characters better
  • Machine learning can be trained to understand data points and where they’re found on a document
  • Machine learning is able to control how a data point relates to other data points, bringing better results

What’s IDP got that OCR hasn’t?

OCR vs IDP?

With OCR as the starting point, IDP uses artificial intelligence and machine learning algorithms to process and extract data from multiple types of documents – different formats and structures. It can work with complex data, including semi-structured and unstructured data. 

An IDP solution then uses natural language processing – NLP – to extract relevant data from the document. The data is validated against predefined business rules and uploaded to a database or ERP system.

Wait! It doesn’t stop there. Yes, automated data extraction is a cinch,  but it can also understand data in context. IDP can achieve accuracy levels of up to 99%. So if your business passes a high volume of complex documents, and needs them processed fast, accuracy remains high. Cherry on the cake. IDP is easy to implement and integrate with your existing systems.

Seriously… you need IDP to remain competitive

AI is the future. There’s no getting away from it. It’s here. It’s happening. It’s not going away.

Embrace it and it’ll be your work buddy. Ignore it and your business will fall behind your competitors.

While OCR is great, it has serious limitations. When the first mobile phones landed – yep, talking about the brick again – they were phenomenal. They changed our lives. Compare the originals to what we have in our pockets now. We’re talking space age.

Adopting intelligent document processing gives you the advantages of OCR, alongside the additional benefits of artificial intelligence…

Unmatched productivity and accuracy

  • Faster data entry, verification, and validation
  • Minimized error rates 
  • Maximum scalability and agility
  • Talent retention as people released from boring, repetitive tasks

Protection against document-based risk

  • Fraud and anomaly detection
  • Transaction matching
  • Streamlined approval workflows
  • Compliance monitoring

Improved relationships with business partners

  • Minimized delays
  • Fast issue resolution
  • Document status visibility
  • Seamless collaboration with internal and external stakeholders

Strategic insights to fuel business transformation

  • Real-time transaction visibility
  • Operational insights
  • Strategic insights
  • Opportunities for optimization and consolidation

Making the move to IDP

Let’s recap…

  • You don’t think automation is worth the cost
  • You’ve a solution that’s not pulling its weight
  • You’re considering going the automation route but OCR vs IDP, which way to go?

Legacy OCR is tired. Around for decades, it’s done a cracking job. What’s the alternative?

Intelligent document processing is the alternative. The only alternative. And – so cute – it doesn’t diss OCR. It takes its advantages, addresses its limitations, and improves it.

IDP uses OCR to convert text into a machine-readable format. Then, using AI, machine learning, and deep learning, it captures, classifies, and extracts data.

Boom!

You’ve got yourself an automated document processing workflow… end to end.

We’ve taken a quantum leap with Rossum Aurora

To conquer the nightmare that is document chaos, we have a dream. To enable one person to effortlessly process one million transactions in a year. And it’s a dream that’s fast becoming a reality, thanks to Rossum Aurora.

The availability of new technological advancements in large language models and generative AI have enabled us to raise the performance bar of processing documents within intelligent document processing. Building on OCR technology and taking document processing to another level.

Rossum Aurora – our advanced AI engine – is powered by our proprietary large language model. It has all the positives of LLMs but none of the negatives, such as hallucinations. It achieves human-level accuracy, fast and boasts the easiest and smartest data capture on the market. Next-generation AI for improved document understanding and end-to-end automation.

Yep. End-to-end automation.

Features include…

  • Aurora for Instant Learning – accuracy is rapidly increased for new document formats and custom fields. Learning from user feedback, you don’t need technical expertise to train the AI.

“We tested Rossum Aurora, it was amazing, it got the first invoice 80% correct, then the next 100%. I would never ever change Rossum for anything else.”
Ondrej Beranek, Executive Director, Veolia Support Services
  • Aurora for Complex Tables – zero issues when capturing pages worth of complex line items.

“Rossum’s Aurora for Complex Tables offers an improvement in how data is captured by speeding up the processing of tables for our team, saving us time.”
Laurent Laeheb, Business Intelligence Analyst, Bolloré Logistics
  • Aurora for Email Communication – save time and task our AI with composing your emails for you, when addressing discrepancies.

“The power of Rossum Aurora getting visibly smarter after each document, combined with a Gen-AI feature to automate supplier communication, makes it incredibly easy to demonstrate value in a PoC and deliver fast time to value for clients.”
Benedikt Anselment, Co-founder, Noa Technologies

Boasts…

  • Accuracy – 37.6 % reduction in error, compared to previous generation
  • Speed of learning – 10x fewer training examples needed to reach the desired accuracy
  • Trustworthy automation – without traditional LLM risks thanks to our Discriminative Decoder
Graph showing the speed of learning from Rossum Aurora, compared with previous AI generation. OCR vs IDP = Settling for OCR when IDP is what you need.

Rossum Aurora average speed of learning based on the results of our Early Adopter program.

Now you know OCR isn’t what you need, what next?

I think you know where I’m coming from. OCR was great. But, for tackling today’s document chaos – the variability, volume, and velocity – it falls short. 

Whichever intelligent document processing solution you choose, ensure you go with an understanding of the technology. Here are a few Rossum resources that’ll help you get a clear picture of what you need…

  • How Rossum Works walks you through our free trial. Put our platform to the test and you’ll have something to compare with other IDP vendors.
  • IDP Definition Glossary includes all the terminology that’ll be thrown at you by a vendor. Be prepared.
  • Rossum Aurora, our launch blog. It explains in more detail, how we’re pushing the boundaries of IDP and the technology behind.
  • Cost Of Doing Nothing eBook. If you’re undecided about automating your document processing, our eBook shows you the long-term impact on your business, the benefits of automation, and questions you should ask your IDP vendor. 

If you’d like to chat with a human to discuss your business requirements, frustrations, confusion, whatever you like, sign up for a free demo. We’re here to listen and help.

Want to see what you should really be looking for?

We've built on OCR technology and taken document processing automation to another level.