What is robotic process automation software, and how does it work?

For most organizations, Robotic Process Automation, or “RPA,” has become an industry standard and a “first step” into digital transformation.

It also offers an exciting opportunity for business leaders and their teams to dip their toes into the many benefits of automation.

May 19, 2023 by Automation Hero

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RPA has helped with this for the past decade, but there are limits to this legacy technology.

To understand these limits, it is crucial to understand how RPA works and how new, more advanced tools are building upon the original promise of RPA. In this comprehensive guide, we delve into the world of RPA and how it differs from its evolved version—Intelligent Document Processing (IDP).

What is Robotic Process Automation?

Robotic Process Automation is a technology that employs software robots, or “bots,” to automate routine, “rules-based” business tasks. RPA bots are like a computer program that can copy the actions of a human worker. 

How RPA Software Works

RPA mimics the manual click work and keyboarding performed by human knowledge workers to carry out tasks on its own without needing humans to intervene or manage them.

“RPA bots are like a computer program that can copy the actions of a human worker.” 

RPA involves a series of steps or rules (also called a “script”) to accomplish its more complex screen tasks and requires a Graphical User Interface (GUI) or a developer window to operate. 

The technology runs on top of computer software systems, where users can then record simple mouse movements and keystrokes that perform screen automations without supervision.

RPA Capabilities

RPA is a legacy technology with a broad spectrum of applications. It can automate tasks ranging from simple to more complex. For instance, it can handle tasks like data entry and form filling, which, although simple, are time-consuming when done manually. 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. 

Additionally, RPA can automate some more complex tasks that involve multiple software systems, such as triggering responses in accounting software to automate transactions and migrating or updating data into another database.

Applications of RPA

RPA can automate repetitive, rules-based tasks, regardless of the industry. Some common applications of RPA include:

  • Data migration
  • Trade execution
  • Data validation
  • Data updates

Moreover, RPA is industry-agnostic, finding applications in sectors as diverse as finance, healthcare, retail, and more. For example, RPA is great for: 

  • Automating routine, rule-based tasks that previously required human intervention including data entry, filling out forms, and automatically moving files and folders to other database systems. 
  • Connecting different systems that were not initially designed to interact with each other, enabling automated data transfer and synchronization. 
  • Managing complex tasks involving any “swivel chair,” or copy/paste interaction with multiple systems.

These capabilities are scalable and can be adjusted to handle increased workloads, providing companies with more flexibility to manage their operations.

Benefits of RPA

Automation through RPA offers several benefits. One of its primary advantages is increased efficiency. By automating repetitive tasks, RPA reduces the time taken to perform these tasks and helps enhance accuracy by reducing human error. This can lead to significant cost savings as companies can achieve more with fewer resources.

“By automating repetitive tasks, RPA reduces the time taken to perform these tasks and helps enhance accuracy by reducing human error.”

Moreover, RPA is scalable. Bots can be easily replicated to manage an increased workload during peak periods. RPA is also non-invasive. This enables RPA to work on top of existing systems and applications, reducing the need for complex IT projects and minimizing disruptions to existing operations.

The limits of RPA

While Robotic Process Automation offers immense potential, it is not without its limitations. The primary one is that RPA can only handle rules-based, repetitive tasks. It also has limitations with tasks that require judgment, creativity, and complex decision-making. 

For example, RPA would not be suitable for tasks requiring strategic decision-making, handling unstructured, ambiguous information, or those that involve human emotions. RPA is also limited in its ability to learn from experience; the bots can only do what they are programmed to do and do not improve or adapt over time without human intervention.

“RPA can only handle rules-based, repetitive tasks.”

The most important limitation to consider is RPA’s dependency on stable environments and structured processes. Any change in the layout of a document or a webpage , or modifications in the underlying systems it runs on top of, can disrupt an RPA bot’s operation, requiring reconfiguration or redesign. This also extends to process changes; if the steps in a process change, even slightly, the bot will need to be re-programmed. 

“Any change in the layout of a document or a webpage, or modifications in the underlying systems it runs on top of, can disrupt an RPA bot’s operation, requiring reconfiguration or redesign.”

This inherent lack of adaptability can potentially increase maintenance costs and limit the long-term effectiveness of RPA solutions. Additionally, while RPA is useful for reducing manual labor for repetitive tasks, it doesn’t contribute to process optimization. Instead, it can sometimes lead to the automation of inefficient processes without addressing the root cause of the inefficiency.

Finally, with so many documents required for compliance regulations, the need for capturing data accurately and quickly—especially unstructured data—is rapidly growing. Unfortunately, this is the most significant area where 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.

How AI and RPA Relate

Artificial Intelligence (AI) and RPA, although separate technologies, can form a powerful duo. While RPA handles routine, repetitive tasks, AI adds a layer of intelligence to the automation process. 

In the early 2000s, RPA was quite literally slapped on top of existing software like a “bandage” 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. 

“Artificial Intelligence (AI) and RPA, although separate technologies, can form a powerful duo. While RPA handles routine, repetitive tasks, AI adds a layer of intelligence to the automation process.” 

As an older technology, RPA on its own will struggle to keep up with the needs of today’s business environments. But AI technologies, such as those already built into next-gen intelligent document processing (IDP) solutions, are extremely useful for augmenting RPA’s limited capabilities.  

Machine Learning (ML), Natural Language Processing (NLP), and Optical Character Recognition (OCR) can be integrated with RPA to create Intelligent Process Automation (IPA) workflows. This combination of AI and RPA allows for the automation of not just simple, rules-based tasks, but also tasks that require understanding, reasoning, and learning.

Differences between RPA and IDP

While RPA and Intelligent Document Processing are both forms of software automation technology, they serve different purposes and have distinct capabilities. RPA is primarily used to automate routine, rules-based tasks. Since RPA users record what they do in their day-to-day job, the RPA robot handles all the clicking and mouse movements to complete the task. As a simple screen automation, it interacts with digital systems in a similar way a human would, performing rote tasks such as data entry, form filling, and triggering responses in other software.

IDP, on the other hand, takes automation a giant leap further. IDP reads, interprets, extracts, and processes data from unstructured sources such as photos, emails, PDFs, invoices, and other semi-structured document types. IDP leverages advanced technologies such as AI, ML, and OCR to understand, categorize, and process this data. 

“RPA is primarily used to automate routine, rules-based tasks…IDP, on the other hand, takes automation a giant leap further.”

RPA can be difficult to update in an ever-changing business environment and is often seen as a “brittle” and unreliable technology relative to the pace of modern business. Savvy organizations take an understanding of RPA and build upon it with newer, more adaptable tools like Automation Hero’s IDP platform.

In essence, IDP can handle complex, unstructured data and capture all of the potential value from it, thereby making IDP more flexible and scalable than traditional RPA. IDP doesn’t just automate tasks; it brings a level of intelligence to the process, enabling it to understand documents at the semantic level.

Read our other article to learn more about the differences between software automation and AI

RPA and hyper-automation

When organizations upgrade their current RPA with AI-driven automation, such as intelligent document processing, they can unlock data stuck in unstructured documents that goes well beyond the limits of traditional RPA.

Hyper-automation represents the future of automation. This involves the application of advanced technologies that use AI, ML, and NLP, in conjunction with RPA to automate complex tasks. 

“Hyper-automation represents the future of automation.”

Hyper-automation goes beyond simply automating tasks and aims to create an orchestration of interconnected technologies working together to automate end-to-end business operations with above-human accuracy. This level of automation not only increases efficiency but also enables businesses to adapt quickly to changing business needs and market conditions.

Why is IDP better than RPA?

It’s important to consider that while RPA is a powerful tool, it’s not a one-size-fits-all solution and often fails to grow or adapt as a business’s needs change. 

In many cases, Intelligent Document Processing (IDP) will offer a more comprehensive solution, especially when dealing with unstructured data and complex processes. Understanding the capabilities and limitations of RPA vs IDP is key to making an informed decision about which technology is the best fit for your organization’s unique needs.

How RPA Factors Into the Future

As an outdated technology, Robotic Process Automation software is still a useful tool with the potential to streamline business operations across industries. By mimicking human interactions with digital systems, it can automate repetitive, rule-based tasks, leading to significant improvements in efficiency, accuracy, and productivity. 

Unfortunately, this outdated approach is limited to only automating simple screen-related tasks. Script-based approaches like RPA have real-world limitations that pervade the industry today, which is why agile enterprises will need modern AI to drive their business processes in the future.

“Script-based approaches like RPA have real-world limitations that pervade the industry today, which is why agile enterprises will need modern AI to drive their business processes in the future.”

The implementation of RPA involves identifying suitable processes for automation, defining the automation workflow, configuring the RPA bot, integrating it with existing systems, and ongoing monitoring and maintenance. While the initial setup may require a certain level of expertise, the return on investment can be significant, especially when you add AI-driven automation with next-gen intelligent document processing to overcome the traditional challenges of RPA. 

Some IDP solutions include automation features to manage the output into a workflow, while other IDP vendors only focus on the intelligent data extraction step. With these more limited IDP products, automation engineers and designers must take the output elsewhere and manage it themselves. 

Automation Hero offers an end-to-end full-service hyper-automation IDP platform that plays nicely with your existing automation software—with benefits that include cost savings, time savings, error reduction, and the ability to free up human resources for more strategic tasks.

Join the hyper-automation revolution with Automation Hero

To learn more about how IDP can fit into your organization, contact our team at Automation Hero. Our expertise in AI-driven hyper-automation and intelligent document processing platform means we can customize the right automation solution to fit your needs, your budget, and your strategic plans. Click here to schedule a demo of Automation Hero today.