What’s the difference between RPA and IDP?
Businesses are always looking for technology that can make their teams more efficient. For the past decade, robotic process automation (RPA) has helped with this — but there are limits.
Intelligent document processing (IDP) brings advanced technologies such as AI and machine learning (ML) to the table to handle the most challenging areas of modern business that RPA cannot reach.
Dec 15, 2022 by Craig Woolard
With so many documents required to operate and adhere to compliances, the need for capturing data accurately and quickly — especially unstructured data — is rapidly growing. Unfortunately, this is one area traditional RPA falls short.
As a result, businesses are looking at sophisticated data extraction solutions like intelligent document processing (IDP) to “unlock” valuable data in unstructured documents.
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What is robotic process automation (RPA)?
Robotic process automation (RPA) is legacy software that mimics the keyboarding and manual click-work performed by human knowledge workers. RPA records simple mouse movements and keystrokes that perform autonomous tasks without supervision or intervention using the UI.
Until recently, most automation software has been robotic process automation. Since the user records what they do in their day-to-day job, the RPA robot handles all the clicking and mouse movements to complete the task.
What can RPA do?
RPA involves a series of steps or rules (also called a “script”) to accomplish its more complex screen tasks. Robotic process automation requires a GUI or developer window to operate. This outdated approach limits RPA to only automating simple screen-related tasks.
These tasks include data entry, data processing, and triggering responses in other software tools. In the early 2000s, screen scraping software was one of the first use cases of RPA. It also served as a “bridge” or a “band-aid” between newer and incompatible legacy systems.
In these early use cases, RPA was quite literally slapped on top of existing software like a bandaid to automate user interface clicks. Consequently, the earliest investments in RPA were driven by the need to integrate legacy systems that didn’t have APIs.
Unfortunately, script-based approaches have real-world limitations that still pervade the industry today. This is what drives so much disillusionment about RPA as a “brittle” and unreliable technology.
Tasks RPA can automate:
- Data migration
- Trade execution
- Data validation
- Data updates
- Any “swivel chair” — or copy/paste function
Today, RPA still allows users to configure one or more scripts to replicate specific keystrokes and repetitive mouse movements. These scripts are “rules-based” templates that automate each task. Scripts can operate in isolation as a single task — or overlaid on top of multiple software applications to support a more complex workflow.
Where does RPA fall short?
RPA has several shortcomings. For one, it is a legacy tool. RPA is built for “bots” that use a graphical user interface (GUI) to work. Therefore, it only mimics movements and clicks.
Here are three major weak points RPA has:
1. RPA is not built for modern system-to-system integrations. Deploying RPA to integrate different systems is a lot like setting up a bucket brigade to put out a fire instead of using a firehose. The bot approach makes things much harder to build, manage, and price. There are even companies out there that sell tracking solutions for all of your RPA bots, so you can check if you have too many.
2. It breaks easily. When there is a change in the GUI or when an update changes the user interface design for a software application that an RPA template is built on top of — the entire automation breaks.
3. It’s outdated. RPA relies on a legacy Optical Character Recognition (OCR) that can only follow input rules and commands. Each only adds a patchwork solution on top of the already existing patchwork. These all break just as easily as GUI-based approaches.
Their solution? Slap on an ineffective AI “bandaid.”
RPA vendors are aware of the limitations of RPA technology. As a result, they are looking to expand their capabilities to include some “off-the-shelf” OCR and artificial intelligence (AI) solutions made by third-party vendors. But these are tacked on like “duct tape” to an already brittle RPA implementation.
Like most off-the-shelf AI solutions out there — not all OCR solutions on the market are created the same. Since the 1980s, legacy OCR technology still lacks the sophistication to recognize handwriting accurately. Even with the best scanners and document quality, you will be lucky to get 60% accuracy with legacy OCR before it eventually hits the wall.
These technological limitations block 82% of enterprises from accessing their most valuable asset. While RPA frees people from performing the most mind-numbing work behind critical business processes, the technology’s most significant road blocker is the lack of native AI document understanding needed to unlock unstructured data.
What is intelligent document processing (IDP)?
Enter IDP. As a next-gen automation technology, IDP has evolved from the need to go beyond RPA’s limitations.
Intelligent document processing (IDP) is a new type of business workflow automation that uses state-of-the-art AI to read documents the same way as humans. IDP technology reads, extracts, categorizes, organizes, converts, and outputs information into practical formats from streams of data (usually documents) that different databases and departments can use.
IDP solves business problems that need hard-to-reach data. Since IDP does not follow traditional rules-based approaches, it’s flexible, cuts down on more costs, and unlocks the hard-to-reach unstructured data that RPA cannot reach.
How does intelligent document processing work?
IDP consists of three fundamental elements—classification, extraction & validation.
First, IDP uses cutting-edge AI technologies to classify, extract and validate essential information from unstructured documents. For this, IDP combines Optical Character Recognition (OCR), machine learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) — to unlock valuable data inside unstructured documents and related document workflows.
Then, IDP turns the information it extracts into workflows for other automation tools and data analysis. When IDP scans documents, it understands context — with above-human accuracy — which helps organizations streamline the entire document process and the flow of essential information between different database systems, software applications, and departments.
Check out the intelligent document processing (IDP) guide for more.
RPA vs. IDP
In the automation world, we often refer to RPA as “the hands” and AI as “the brains.”
The most important thing to understand about RPA vs. IDP is that robotic process automation does not have native AI intelligence. As standalone technology, RPA cannot read, understand, or interpret data on its own. It is outdated technology that still needs humans (or sophisticated AI) to transform data into practical actions.
By mimicking the tedious, repeatable actions we perform on computer screens with a keyboard and a mouse, RPA removes the “heavy lifting” of everyday processes — but, unfortunately, this limits RPA to tasks that do not involve high-level decision-making.
Intelligent document processing, on the other hand, takes automation to the next level, and this is where the market is heading. IDP not only automates documents — it ingests and understands data — making it actionable.
What are the differences between IDP, OCR, and RPA?
RPA is a “rules-based” technology that relies on an outdated template approach and other technologies, including legacy OCR, to help compensate for RPA’s weak points. In the early days, legacy OCR was used to build templates as a “pre-AI” solution for document extraction problems.
Templates (or scripts) are helpful for tasks with a well-defined structure — but once a design element in the user interface (UI) or the documents themselves change — the template breaks. The changes mean you have to re-design the automation all over again.
Unlike RPA and OCR, Intelligent document processing is flexible. Since IDP has AI, rules-based approaches do not limit IDP’s ability to extract data. IDP reads the contents of documents and even learns from their contents just like humans — so it improves with every use. IDP can complement legacy point-and-click RPA tools for tedious screen tasks. However, with an AI engine at its core, end-to-end IDP platforms like Automation Hero can replace the RPA robots.
What are the benefits of automated document processing?
Intelligent document processing transforms unstructured content into data that is easy to use. IDP automates content that lacks structure and turns it into structured data for other business processes. Here are a few high-level tasks intelligent document processing can do:
1. IDP can read documents in every format
Business documents come in every format — including paper forms, PDFs, images, and email. IDP reads them all with clear understanding of every word.
2. IDP transforms unstructured documents
Unstructured documents do not follow templates, fixed layouts, or rules — which is why RPA doesn’t cut it. Instead, IDP takes the data captured by OCR and applies rules to contextualize and route it for further processing. IDP platforms like Automation Hero’s Hero Platform_ utilize advanced deep learning and machine learning AI to do this accurately, even if the document’s layout changes.
3. IDP understands handwriting & signatures
Object, or Optical Character Recognition (OCR), is the technology that recognizes characters, letters, and numbers — regardless of font. OCR also recognizes cursive handwriting. But legacy OCR does not recognize handwriting very accurately. Automation Hero has a patent-pending Context-aware OCR that converts text — even handwriting — 281% more accurately.
4. IDP drives orchestration, natively
IDP can streamline an entire document-centric workflow (without needing anything else).
Some IDP solutions include automation to manage the output of data streams into workflows. Other IDP vendors only focus on intelligent data extraction. With some of the more limited IDP tools, automation designers will have to figure out how to manage the outputs themselves.
Most automation vendors charge extra for orchestration capabilities that can add intelligence to their automation. However, end-to-end automation platforms like Automation Hero’s Hero Platform_ already have orchestration and workflow integration built-in — no extra charge.
4 Benefits of enhancing RPA with intelligent document processing (IDP)
When Henry Ford was asked about customer input in the development of the Ford Model T, Ford famously answered — “If I had asked people what they wanted, they would have said faster horses.” Similarly, if you ask most automation designers and RPA users what they want today, they’d probably ask for a better-performing RPA. Adding advanced AI to RPA is more than just the faster horse.
Here are four reasons why you should augment your current RPA with IDP:
1. Unlimited integrations
The use of multiple software systems and different databases is often the result of mergers and acquisitions. Any attempt to streamline operations with a single (or upgraded) solution could be disruptive. Whatever the reason for inefficient back-end processes, intelligent automation is a viable option.
After IDP captures information from documents, it processes it into structured data for software applications, micro-services, and even third-party digital workflow services (via API).
Automation Hero can connect with virtually any API and seamlessly transfer data without formatting or oversight. This can provide one of the most significant productivity boosts since it enables full end-to-end automation for nearly any process. The possibilities are unlimited.
2. IDP hyper-automates
IDP technology operates standalone but also integrates with existing workflow automation tools. Even though IDP can stream an entire automation workflow, IDP integrates seamlessly with existing RPA — augmenting it with new abilities without changing its core functionality.
For example, intelligent document processing could integrate as a sub-process that augments existing RPA tasks with AI/cognitive capabilities — an excellent solution for organizations limited on resources to make sweeping changes.
When combined with legacy automation tools such as RPA, intelligent document processing brings next-level AI intelligence to critical business processes — creating the most advanced hyper-automation solution to navigate the global challenges of rapidly growing unstructured data.
3. More capabilities — less IT
Legacy RPA systems have long and costly implementation timeframes. This process requires months of planning and testing by IT experts to ensure templates and workflows are programmed just right. With a modern end-to-end IDP platform like Automation Hero’s, any user can design new patches and workflows wherever there’s a gap in the RPA performance. In fact, the Hero Platform_ is so intuitive there is no need for coding experience or IT support.
4. Improved KYC processes
Even when it’s tied to the limits of an old RPA system, IDP can help users see the potential of holistic enterprise AI. For example, financial institutions can’t know their customers if most of the data they have about them is stuck in inaccessible documents. Automation Hero’s API can serve as the IDP “fabric” connecting every process and system it’s a part of.
As an end-to-end IDP platform, Automation Hero’s API is flexible — connecting all workflow services with other business process automation systems to extract hard-to-reach data from unstructured documents. You could integrate multiple APIs into a unique KYC process that preps the information for data analysis — helping to further refine and streamline critical business processes.
How to hyper-automate RPA with IDP
Leaving behind an institutionalized technology like RPA can be daunting, but thanks to the versatility of IDP, companies don’t have to delete their old software to reap the benefits.
Hyperautomaton with IDP will rapidly automate documents plus many business processes simultaneously — streamlining the entire data intake process across departments and augmenting people’s roles more than ever.
When shopping for an intelligent document processing solution to augment a current RPA implementation, choosing the right IDP that will fit your organization’s needs is critical.
How to get started hyper-automating today:
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