Intelligent Document Processing Explained: What It Is and What It’s Not

Businesses across all sectors are under constant pressure to adopt a digital transformation strategy to stay relevant and competitive. This includes investments in automation, workflow optimization and analytics technologies to reduce costs, streamline services, and improve customer experiences. These technologies fundamentally rely on good, actionable data. Intelligent Document Processing (IDP) plays a critical role in making that happen. In this in-depth blog post, we’ll cover:

• Why there’s a need for IDP
• The definition of IDP  
• How IDP works
• The problems IDP solves
• A deeper dive into the role AI plays in IDP
• Docufree’s human-led IDP technologies and services at work
• The benefits you can expect from IDP at your organization
• Steps to get your company started with an IDP project

Why IDP? Unstructured Data is Exploding

We all use our phones and computers every day, sending emails, signing digital forms, and sharing photos. Now imagine a business dealing with this kind of information but on a huge scale. Documents are constantly pouring in from a variety of sources in different layouts and formats—whether it’s emails, paper documents, scanned images, PDF files and pictures that don’t fit neatly into tables. This is what we call unstructured data, and it makes up 80- to 90-percent of data found in an organization. It’s also growing super-fast, so much so that by 2025, we’ll have over 180 zettabytes of it.

Manually wrangling all this data is time-consuming, error-prone, costly, and quite simply,  unsustainable in today’s world of work. It often requires employees to scan, sort, type information by hand, copy and paste, and jump between different systems. Additionally, the shift to remote and hybrid work environments with employees scattered across locations makes it even more challenging to implement standardized and efficient document processing workflows. This is why businesses are increasingly turning to Intelligent Document Processing to handle this data efficiently. A Grand View Research report estimated the global IDP market will reach $11.6 billion by 2030.

What is Intelligent Document Processing (IDP)?

Intelligent Document Processing (IDP) is a solution that combines artificial intelligence (AI) technologies like optical character recognition (OCR), natural language processing (NLP) and machine learning (ML) with process automation to automate the extraction, processing and integration of data from documents. It’s like a super-smart assistant that can read and understand all kinds of documents like a human would—but faster and at scale. It then extracts the important information from those documents and organizes it into an accessible format that can be easily used by other systems, technologies and people to automate processes and make informed decisions.

What’s the Difference Between IDP, OCR and RPA?

IDP is often confused with other technologies but it is fundamentally different. OCR converts scanned documents or images into machine-readable text, which is the first step in IDP. IDP goes beyond OCR by understanding the context and meaning within documents, taking document processing from simple text recognition to intelligent, context-aware information extraction. Imagine the difference between reading a grocery list (OCR) and comprehending a recipe (IDP).

IDP is also different from Robotic Process Automation (RPA). While both technologies aim to streamline business processes through automation, they serve different purposes. RPA is designed to automate repetitive, rules-based tasks without the need for interpretation or decision-making. It excels in environments that require high-speed, routine task execution based on clear guidelines. However, RPA operates on structured, clear data, which it needs to function effectively. This is where IDP plays a crucial role.

IDP acts as the “brain” that interprets documents and unlocks and prepares the data into a structured format, making it usable for RPA. RPA then acts as the “hands,” using the structured data to perform automated tasks such as populating forms, triggering predefined workflows or approvals based on extracted data, routing and uploading documents, or sending notifications. The combination of IDP and RPA, often referred to as Intelligent Document Automation (IDA), is a powerful way to streamline and automate document-centric processes.

How Does IDP Work?

The IDP process typically involves the following steps:

1. Document Capture: Documents are digitized through scanning, digital mailrooms and/or receiving digital files through email, webforms, corporate systems and applications, etc.
2. Document Classification: Documents are categorized based on their content and structure (e.g., invoices, purchase orders).
3. Data Extraction: Relevant data is then extracted from those documents. Key information can include names, addresses, dates, dollar amounts and other structured data. Advanced IDP solutions use OCR, NLP and ML to more accurately pull data from unstructured documents.
4. Data Validation and Verification: Extracted data is then validated and verified for accuracy by cross-referencing with existing databases or business rules to identify discrepancies or errors.
5. Data Integration: Validated data is integrated into downstream business applications such as enterprise resource planning (ERP), customer relationship management (CRM) and human resources information systems (HRIS).
6. Automation: With these systems’ integrations in place, data can be used to automate repetitive tasks, such as data entry or workflow approvals.
7. Continuous Improvement: IDP solutions can learn from repetitive tasks, user interactions and feedback to improve their accuracy and efficiency over time.

Types of Documents Analyzed by Intelligent Document Processing

IDP solutions can analyze a wide variety of document formats making it highly valuable across multiple industries and business segments. Here are some of the main document types it can efficiently process:

• Financial: Invoices, receipts, bank statements, purchase orders.
• Legal: Contracts, legal briefs, case files.
• Human Resources: Resumes, application forms, employee records.
• Government: Tax forms, licenses, registrations.
• Healthcare: Medical records, insurance claims.
• Education: Admission forms, academic transcripts, certifications.
• Real Estate: Lease agreements, sales agreements, surveys.

Business Problems Solved by Intelligent Document Processing

Manual document handling and processing creates inefficiencies for companies, especially as the global economy embraces digital operations. An IDP solution can address these key problems:

• Data Entry Errors: Manual data entry is time consuming, error prone and costly and can lead to the classic “garbage in, garbage out” problem of faulty data being fed into processes. IDP mitigates this through automated extraction and validation, improving data reliability and accuracy while minimizing staffing needs.
• Large Document Volumes: Processing large volumes of documents can overwhelm staff. IDP automates the tasks, enabling organizations to digitize high volumes of documents more efficiently and accurately at scale.
• Unstructured Data Formats: Extracting data from unstructured documents like scanned images, PDFs, and handwritten forms is challenging. IDP leverages OCR, NLP and ML to reliably extract relevant data.
• Processing Delays: Manual processing often causes workflow delays, resulting in slower decision-making and response times. IDP feeds validated data into business process management and automation solutions faster which in turn automates tasks such as routing documents for approval, populating forms and sending notifications. This reduces manual intervention, speeds up approval processes, and ensures greater accuracy and compliance.
• Noncompliance with Regulations: Federal, state and industry regulations often require companies to accurately store and maintain information from various documents. Manual document handling and processing increases the risk of noncompliance along with the potential for regulatory penalties. IDP automates these tasks to ensure proper information storage, accuracy and integrity.
• Need for More Visibility and Control: Manually stored documents in file cabinets or storage centers are hard to track and manage. IDP enhances visibility into document workflows, enabling organizations to easily monitor document status, track reviews and approvals, and enforce process controls.
• Staffing Limitations: Limited staffing and budgets means companies must do more with less—while trying to maintain peak operations. IDP helps companies optimize staffing resources by automating repetitive, manual-laden tasks, freeing up personnel to focus on more strategic activities.

A Starring Role for AI in Intelligent Document Processing

AI performs a crucial function in IDP, playing the catalyst that enables automation, efficiency and accuracy when it comes to handling various types of documents. It’s key contributions include:

• Document Classification: AI analyzes document structure and content to classify them into different categories, streamlining the handling process, reducing manual intervention, and aiding in routing to relevant workflows.
• Optical Character Recognition (OCR): As mentioned earlier in this blog, OCR is focused on converting images of text into machine-readable data. AI powers OCR by giving the technology the ability to accurately recognize characters in scanned or handwritten documents and images in order to extract text for further processing.
• Natural Language Processing (NLP): This technology allows machines to understand and interpret human language, including text contained within documents. AI-driven NLP extracts meaning, sentiment, entities (i.e. names, dates, dollar amounts, addresses, etc.) and relationships from textual data, allowing for the processing and deeper analysis of document content.  
• Data Extraction and Entity Recognition: Machine-learning capabilities built within AI are used to pull useable and relevant information from various forms of documents. This allows the technology to automate the identification and extraction of key entity information.
• Data Validation and Verification: AI technology can perform validation and verification activities to ensure the accuracy and integrity of extracted data. This can be accomplished through predefined rules, referenceable data sets or historical patterns to help identify errors, inconsistencies or anomalies. 
• Document Understanding: AI allows machines to understand the context and meaning of information contained in documents. Advanced AI solutions can analyze the structure and content of documents to identify patterns, infer relationships between different pieces of information, and extract valuable insights.
• Automation for Workflows: AI-powered IDP solutions can deliver end-to-end document-processing workflows. The AI acts to dynamically adjust workflow parameters, allocate resources and route documents based on business rules, priorities and performance metrics.
• Continuous Learning and Improvement: It is AI that allows IDP platforms to continuously learn and improve over time through feedback and iterative training. Machine-learning functions depend on things like user interactions and document-processing outcomes to optimize the platform’s performance. 

Business Benefits of IDP

IDP provides a full spectrum of benefits to organizations across various industries and operational functions. Below are eight key business benefits:

1. Increased Efficiency: Organizations can process documents quicker and more efficiently, leading to faster turnaround times and improved productivity.
2. Boosted Cost Savings: Companies save on the expenses associated with hiring and training staff to handle documents as well as any costs associated with information errors, such as those for reworks and compliance penalties.
3. Added Accuracy: The ability to validate extracted data from documents reduces the risk of errors associated with manual data entry and processing, helping to ensure the reliability and integrity of the information.
4. Improved Compliance: With the automation of compliance-related tasks, such as data validation, verification and auditing, businesses can reduce the risk of non-compliance and regulatory penalties.
5. Quicker Decision Making: The automation of document-processing tasks combined with real-time access to information gives leadership teams the ability to make faster, more informed business decisions. 
6. Better Customer Service: By reducing document processing times, minimizing errors and having the ability to make quicker operational decisions, companies can enhance their overall customer service and satisfaction.
7. Added Scalability and Flexibility: Whether processing a few documents per day or thousands of documents an hour, organizations can rely on IDP solutions to scale to meet their changing business needs. The ability to customize the various types of documents that are handled as well as integrations with existing corporate systems and workflows give companies even more flexibility.
8. Deeper Insights and Analytics: The ability to extract valuable insights from documents, such as trends, patterns, and correlations, empower organizations to gain a deeper understanding of their operations and customers.

Docufree: A Human-Led Approach to Intelligent Document Processing

While IDP is designed to take the manual tasks related to document processing out of the equation, there is still a significant place for human interaction.

Today’s business problems are becoming increasingly more complex and challenging. These problems need to be examined from every angle. Part of that analysis will require human experience, passion and creative thinking to be combined with AI technology.

With a human-led approach, Docufree is in a solid position to deliver the full potential of IDP’s AI capabilities, while respecting the critical role people must play to avoid any misperceptions and to help build trust in the technology. Through this approach, we can help clients unlock the information and value in their documents’ data in a way that not only delivers productivity gains, but also doesn’t disenfranchise their existing workforce.      

Docufree is committed to investing in our people in ways that allow them to use the company’s technologies and services—combined with their own experiences and understandings of industries and their innate business problems—to provide greater efficiencies, deeper insights and more intelligent business outcomes for clients. 

Docufree believes in selling solutions and true partnerships…not just products. We pride ourselves as a company in offering new, creative ways—led by teams of experts—to apply AI technology to deliver sustainable outcomes and help clients solve their most important business challenges.

Steps to Get Your Company Ready for an IDP Project

Starting an IDP project involves several steps to ensure successful implementation and adoption within your organization. When researching potential IDP vendors, not only look for those that offer a full suite of technology capabilities, but also those with a dedicated services and support team. Working hand-in-hand with IDP experts will help make the process as seamless and pain-free as possible. Take these key steps into consideration before embarking on your IDP project:

1. Define objectives and desired outcomes
2. Assess current processes and document flows
3. Develop an implementation strategy
4. Prepare documents and data for processing and integration
5. Identify areas for configurations and customizations
6. Prepare for user training and adoption
7. Plan to monitor, measure and optimize

Overall, when partnering with the right solutions provider, IDP can offer significant operational benefits, making it a valuable technology investment for companies looking to streamline their document-centric processes and drive better business outcomes. Contact us to find out how IDP can benefit your organization.