RPA vs IDP: Which One Should You Choose in 2024?

Whether it’s the straightforward efficiency of RPA or the advanced capabilities of IDP, understanding these technologies is key to unlocking new levels of productivity and accuracy in your business processes.
October 28, 2024
RPA vs IDP: Which One Should You Choose in 2024?

Looking for a way to streamline your business processes but not sure whether to go with RPA or IDP? While RPA offers straightforward efficiency by automating repetitive tasks, IDP provides advanced capabilities for handling complex data. Understanding the differences between these advanced technologies is crucial to enhancing productivity and accuracy in your operations.

According to Gartner Automation Trends Report 2023, 75% of large enterprises will leverage at least four automation technologies to drive efficiency and growth by 2025. RPA and IDP are expected to spearhead this transformation. 

But what exactly are these technologies, how do they differ, and which is right for your business? Let’s dive right in.

What is Robotic process automation (RPA)?

Robotic process automation (RPA) is a technology that uses software robots or "bots" to automate repetitive and rule-based tasks typically performed by humans. These bots can handle tasks such as data entry, processing transactions, generating reports, and managing routine communication. 

A study by SMR shows that businesses receive a typical return of USD 6.74 for every USD 1 invested in RPA technology.

Examples of RPA Use Cases

  1. Finance: RPA is used to automate tasks like invoicing, accounts payable and receivable, bank reconciliations, and financial reporting. For instance, many businesses use RPA to process thousands of invoices per day, improving speed and accuracy over time while reducing manual processing.
  2. Human Resources (HR): RPA can manage tasks like employee onboarding, payroll processing, and benefits administration. This technology can significantly reduce the time it takes to onboard new employees, automating paperwork and information updates across systems.
  3. Supply Chain Management: Streamlining inventory management, order processing, shipment tracking, and vendor management can be done by RPA. This enables real-time updates in inventory systems, improving supply chain efficiency.
  4. Customer Service: RPA can automate responses to common queries, routing complex issues to human agents, and processing customer data. By handling standard questions, RPA helps customer service teams focus on more complex processes.
  5. Small and Medium Enterprises (SMEs): SMEs have started adopting RPA for cost-effective automation, reducing human error, and improving overall productivity. 

The Robotic Process Automation Market is estimated to reach USD 22.14 billion by 2030, growing at a CAGR of 35.9%. — IndustryARC Forecast Report 2024

The rise in cloud-based RPA solutions, such as RPA as a Service (RPAaaS), has enabled SMEs to access automation tools without large upfront investments, fostering rapid growth in this segment.

Limitations of RPA

While RPA is highly effective for routine tasks, it has its limitations:

  1. Limited to Structured Data: RPA works well with structured data that follows a predictable format, like spreadsheets or databases. It struggles with unstructured data, such as free-form text in emails or documents, limiting its applicability in more complex workflows.
  2. Rigid Processes: RPA operates based on predefined rules. If a process involves variations or exceptions not accounted for during setup, RPA may fail, requiring human intervention.

Lack of Learning Ability: RPA bots cannot learn or adapt independently. Any change in the process requires reprogramming, which can become costly and time-consuming as business needs evolve.

What is intelligent document processing (IDP)?

Intelligent document processing (IDP) enhances data extraction by combining AI, machine learning, and natural language processing to understand and process complex documents. 

The global intelligent document processing (IDP) market is expected to grow from USD 860 million in 2021 to USD 4.15 billion in 2026 at a CAGR of 37%.— Valuates Reports

Imagine analyzing large volumes of contracts or research papers to find specific information. IDP can automate this by recognizing patterns, context, and the structure of the content in minutes. It understands the context, making the data extraction more accurate and reliable.  

Unlike traditional methods that rely on manual data entry or basic automation, IDP can read, interpret, and extract information from unstructured data like emails, invoices, contracts, and even handwritten notes. 

Examples of IDP use cases

Intelligent document processing software is transforming document-heavy industries by automating complex document processing tasks:

  1. Finance: IDP can automate invoice processing, loan applications, and expense management. In a finance department, IDP can quickly extract data from thousands of invoices and transactional documents, significantly reducing manual labor and speeding up payment cycles.
  2. Legal: With IDP, Automating the review and management of legal contracts, compliance & legal documents, and case files becomes easy. Law firms use IDP to process and organize large volumes of documents in litigation cases, saving time and reducing errors.
  3. Healthcare: Managing patient records, insurance claims, and medical forms is now a piece of cake with IDP. This technology helps healthcare providers efficiently process patient intake forms, insurance documentation, and medical records, improving accuracy rates and compliance with healthcare regulations like HIPAA.
  4. Supply chain: IDP helps in Processing purchase orders, shipping documents, and inventory records. It streamlines procurement processes by automatically extracting data from supplier contracts and shipping records.
  5. Human Resources: Organizations using IDP in HR have reduced the time spent on resume screening and onboarding processes by 50-60%, leading to faster hiring cycles and improved candidate experiences.

Limitations of IDP

Despite its many advantages, IDP has its limitations:

  1. Initial setup and training: Implementing IDP requires a significant upfront investment, particularly in training the AI models to understand specific types of documents. 

Depending on the complexity of the data and the variability of the document formats, it may take time before the system reaches optimal performance.

  1. Data security concerns: Handling sensitive documents, like contracts or medical records, can raise data privacy and security issues. Businesses must ensure that their intelligent document processing solution complies with relevant data protection regulations.

IDP vs. RPA: 9 Key differences

RPA automates repetitive and time-consuming tasks across systems, while IDP focuses on extracting and interpreting data from unstructured and semi-structured documents using AI and natural language processing. While both are incredible tools, they serve different purposes. 

Let’s understand the differences in detail:

Let’s understand the differences in detail:

RPA (Robotic Process Automation)

Definition

RPA automates repetitive, rule-based tasks by mimicking human interactions with digital systems.

Primary Function

Executes predefined processes by interacting with software applications.

Data Type

Structured data (e.g., databases, spreadsheets)

Technology Used

Basic automation tools, often rule-based.

Customization

Requires specific rules or scripts to be set up for each task.

Complexity of Tasks

Best suited for simple, repetitive tasks.

Learning Capability

Static; does not learn or improve over time.

Integration

Integrates with existing systems via APIs and UI interactions.

Industry Focus

Applicable across industries for back-office operations, IT, and customer service.

IDP (Intelligent Document Processing)

Definition

IDP automates the extraction, interpretation, and processing of data from unstructured and semi-structured documents.

Primary Function

Extracts and interprets data from various document types, often using AI and ML techniques.

Data Type

Unstructured and semi-structured data (e.g., invoices, contracts, emails)

Technology Used

Advanced AI/ML algorithms, natural language processing (NLP), optical character recognition (OCR).

Customization

Learns and adapts to new document types with training and AI models.

Complexity of Tasks

Handles more complex tasks involving data interpretation and contextual understanding.

Learning Capability

Dynamic; improves accuracy over time with machine learning.

Integration

Integrates with document management systems, ERP, CRM, and other enterprise software.

Industry Focus

Widely used in finance, healthcare, legal, HR, and insurance industries for document-intensive processes.

IDP or RPA: Which is right for you in 2024?

Still on the fence? The answer might not be a straightforward one. When deciding between RPA and IDP, think about what you need to achieve. If you’re facing repetitive tasks that follow a clear set of rules, like entering data into a system or processing standard transactions, RPA is your best bet. It automates these routine activities, freeing your time for more strategic work. 

On the other hand, if you need to handle data from paper documents that aren’t as straightforward, like invoices, contracts, or medical records, IDP is the ideal choice. IDP excels at extracting and interpreting data from unstructured or semi-structured documents, using advanced AI to make sense of varied formats and information. 

In 2024, the demand for IDP and RPA will continue growing as organizations seek to optimize their operations. While RPA remains valuable for automating structured tasks, IDP is becoming increasingly important for businesses that deal with diverse document layouts and need to streamline their document processing efforts.

Bottom line?

RPA is great for automating those repetitive, rule-based tasks that bog you down and making your processes more efficient and accurate. However, when it comes to handling complex documents, IDP takes the spotlight. It leverages AI to analyze unstructured data, pulling out and interpreting the information you need for intelligent automation. 

When deciding between RPA and IDP, it’s all about matching the right tool to your needs. By understanding these distinctions, you can select the technology that aligns best with your business goals, ensuring that your operations are streamlined and optimized. 

Now, you can experience the power of IDP with Docxster for FREE! Start with our "Forever Free" plan and experience how Docxster ensures your documents are processed quickly and accurately. Try it today and see the difference for yourself!

RPA vs IDP FAQs

1. What is IDP vs RPA vs OCR?

IDP (Intelligent Document Processing) uses AI to extract and analyze data from unstructured documents, RPA (Robotic Process Automation) automates repetitive, rule-based tasks by mimicking human actions, and OCR (Optical Character Recognition) converts scanned or printed text into digital text for easier processing and analysis.

2. In which scenarios is IDP more effective than RPA?

IDP is more effective than RPA in scenarios involving unstructured or semi-structured data processing, particularly when dealing with the variety and volume of documents. It excels in tasks requiring intelligent automation like data extraction, interpretation, and analysis from complex sources like invoices, contracts, or handwritten forms.

3. How does IDP complement RPA in automation processes?

IDP enhances RPA by handling data from unstructured documents, emails, PDF files, and images. It can extract relevant information from these sources, which RPA can use to execute further automated processes.

4. What are the common use cases for IDP? 

Common use cases for Intelligent Document Processing (IDP) include automating data extraction from invoices, contracts, and forms, where the content and layout can vary significantly. 

IDP is used to streamline processing by converting unstructured data into structured formats for easier management and analysis. It also enhances workflows in industries such as finance, legal, and healthcare, where handling large volumes of paper documents is crucial.

5. What’s Docxster’s “Free Forever” plan all about?

Docxster’s “Free Forever” plan lets you access all the core features at no cost for as long as you need. You can streamline your document processing tasks efficiently without hidden fees or time limits. It’s all about giving you a chance to experience the benefits of Docxster’s technology without any financial commitment.