What is Intelligent Document Processing?

Organisations today are so interconnected that the flow of data between them (in the form of documents) is always rising. Processing said data into meaningful information is an important task. Without this step, finance, sales and supply chain would be paralysed or operating blind. However, with the sending and receiving of business data on the rise, processing them is only going to become more difficult in terms of maintaining quality and efficiency. This is why many organisations are taking the smart approach and addressing it with Intelligent document processing.

 

Intelligent Document processing is an advanced workflow automation technology that automates the extraction of data from unstructured or semi-structured documents, utilising Artificial Intelligence (AI), Machine Learning (ML) and Natural Language Processing (NLP). IDP works by analysing document content, identifying key data elements and accurately extracting them for integration into digital business processes.

 

Through continuous learning and adaptation, IDP improves efficiency, accuracy, and insights, transforming manual document workflows into streamlined, intelligent systems. Not to mention that document processing is one of the less enjoyable tasks to perform when manually undertaken. AI is yet again helping to improve colleague satisfaction levels but reducing time spend on these tedious tasks.

 

Document processing vs intelligent document processing

The goal of both regular document processing and intelligent document processing is the same, they are both achieved by different methods, as is distinguished below.

 

Document processing is the manual systematic conversion of physical documents into digital formats via manual extraction methods for structuring into various formats.

 

Intelligent Document Processing (IDP) utilises AI, ML or NLP to automate the extraction and analysis of unstructured or semi-structured data from documents. It enhances accuracy, efficiency and insights.

 

In short, the difference is the means used to extract information from the documents. One is manual and the other utilises automation workflow technologies.

 

Common misconceptions about intelligent document processing

To get a better idea of what IDP actually is and its potential, it’s important to distinguish it from similar technologies which it can be grouped with, but nevertheless, is not.

 

What is the difference between OCR and intelligent document processing?

Similarly to IDP, Optical Character Recognition enables the conversion of different types of documents, such as scanned paper documents, PDF files, or images captured by a digital camera, into editable and searchable data. Essentially, OCR allows machines to recognise printed or handwritten text characters within these documents and convert them into machine-readable text. Whilst IDP can use OCR for capturing data, OCR is very much its own field and is much more complex than IDP, requiring a more specialised skill set to and levels of verification on results.

 

Robotic Process Automation

Intelligent Document Processing (IDP) and Robotic Process Automation (RPA) differ in their focus and capabilities within automation. RPA primarily automates repetitive, rule-based tasks by mimicking human actions in digital systems, making it suitable for streamlining structured processes like data entry and form filling. On the other hand, IDP specialises in extracting and processing information from unstructured documents such as invoices, contracts, and emails, leveraging technologies like OCR and NLP to understand and extract data from diverse document formats. While RPA excels at structured tasks, IDP handles the variability and complexity of unstructured documents, making it ideal for automating processes that involve handling diverse types of documents and extracting meaningful data from them.

 

Chat GPT

Workflow automation technologies often get grouped into the same basket when it comes to functionality, but there are specific differentiators which are worth noting.  Chat GPT is a Gen AI natural language processing model, meaning its primary function is to produce content that mimics a human. IDP solutions like Documait utilises Gen AI in some aspects- such as forming email drafts for suppliers, but mainly utilise AI to extract data from various types of documents, including invoices, purchase orders, contracts, and more.

How accurate is intelligent document processing?

The accuracy of Intelligent Document Processing (IDP) can vary depending on several factors, including the quality of the documents being processed, the complexity of the data extraction task, and the capabilities of the IDP solution itself. Generally, modern IDP systems can achieve high levels of accuracy, often exceeding 90% accuracy rates for data extraction tasks from structured documents. However, accuracy may decrease for more complex or unstructured documents due to factors like handwriting variability, poor document quality, or ambiguous content. Continuous improvement through machine learning algorithms and human validation processes can further enhance IDP accuracy over time, making it a reliable solution for automating document-centric workflows.

 

 

How does intelligent document processing work?

Intelligent Document Processing (IDP) works by employing a combination of advanced technologies such as Optical Character Recognition (OCR), Natural Language Processing (NLP), and Machine Learning (ML) to extract and process information from various types of documents. Here’s how it typically works:

 

1. Document Capture: The process begins with capturing documents in digital format, either through scanning, uploading digital files, or receiving documents electronically.

 

2. Pre-processing: The documents undergo pre-processing to improve readability and consistency. This may involve tasks like image enhancement, noise reduction, and de-skewing to ensure optimal OCR performance.

 

3. Optical Character Recognition (OCR) is applied to convert the scanned or image-based text into machine-readable text. OCR technology identifies individual characters within the document and converts them into digital text, preserving the layout and formatting of the original document.

 

4. Document Classification: Once the text is extracted, the IDP system may classify the document based on its type or content. This step helps determine the appropriate processing steps and workflows for each document category.

 

5. Data Extraction: Using techniques like pattern recognition, keyword matching, and semantic analysis, the IDP system identifies and extracts relevant data from the document. This could include information such as names, dates, amounts, addresses, and other structured or unstructured data.

 

6. Data Validation and Verification: Extracted data is validated against predefined rules or compared with existing databases to ensure accuracy and consistency. Human validation may also be employed to resolve any discrepancies or ambiguities in the extracted data.

 

7. Integration and Workflow Automation: The extracted data is integrated into downstream systems or workflows, where it can be used for further processing, analysis, or decision-making. IDP solutions may also automate subsequent actions based on the extracted data, such as updating databases, triggering notifications, or initiating business processes.

 

8. Continuous Improvement: IDP systems often incorporate machine learning algorithms that learn from user interactions and feedback to improve accuracy and efficiency over time. This iterative learning process helps refine the extraction models and adapt to changing document types or formats.

 

What are the benefits of intelligent document processing?

Intelligent Document Processing (IDP) offers a multitude of benefits across various aspects of business operations:

 

1. Operational Efficiency: IDP streamlines document processing workflows, reducing manual effort and accelerating tasks such as data extraction and validation. This efficiency improvement leads to faster turnaround times, increased productivity, and cost savings.

 

2. Improved Governance: IDP ensures compliance with regulatory requirements and internal policies by automating document review and validation processes. This helps organisations maintain consistency, accuracy, and transparency in their operations, reducing the risk of errors or compliance breaches.

 

3. Improved Supplier Relationships: By automating procurement processes and streamlining communication with suppliers, IDP enhances collaboration and responsiveness. Automated invoice processing and purchase orders improves supplier satisfaction and fosters stronger relationships, leading to better terms and conditions.

 

4. Scalability: IDP solutions can handle growing volumes of documents and data without significant increases in resources or costs. This scalability enables organisations to adapt to changing business needs and accommodate expansion without compromising efficiency or performance.

 

5. Optimised Employee Usage: IDP automates repetitive and time-consuming tasks, allowing employees to focus on higher-value activities that require human expertise and creativity. This optimisation of employee time and skills improves job satisfaction and overall organisational effectiveness.

 

6. Improved Transparency: IDP provides real-time visibility into document processing workflows, enabling stakeholders to track progress, monitor performance, and identify bottlenecks. This transparency enhances decision-making, accountability, and trust within the organisation.

 

7. Enhanced User Experience: By streamlining document processing and reducing manual effort, IDP simplifies tasks for employees, suppliers, and customers. This improved user experience fosters engagement, loyalty, and satisfaction, driving positive outcomes for all stakeholders involved.

 

Use cases for intelligent document processing

 

Pharmaceutical Industry:

Intelligent Document Processing (IDP) streamlines pharmaceutical operations by automating regulatory compliance tasks, such as extracting critical data from drug approvals and clinical trial documents. This ensures faster approvals and adherence to regulatory standards. In finance, IDP accelerates invoice processing and payment cycles, optimising cash flow management. Ledger clerks benefit from reduced manual effort in data entry and reconciliation tasks, allowing them to focus on strategic financial activities. Suppliers experience streamlined invoice submission and payment processes, improving collaboration within the supply chain.

 

Manufacturing Industry:

In manufacturing, IDP enhances quality control and compliance by automating data extraction from inspection reports and compliance documents. This ensures product quality and regulatory adherence. Finance departments benefit from automated invoice processing and purchase order matching, optimising financial operations. Ledger clerks experience increased productivity through reduced manual effort in accounting tasks, enabling them to focus on financial analysis and cost optimisation. Suppliers enjoy simplified procurement processes, leading to improved collaboration and efficiency within the supply chain.

 

Retail Industry:

Intelligent Document Processing (IDP) transforms retail operations by automating inventory management tasks, such as extracting product information and pricing data. This optimises inventory levels and enhances customer satisfaction. In finance, IDP streamlines invoice processing and financial reporting, improving efficiency and accuracy. Ledger clerks benefit from reduced manual effort in accounting tasks, enabling them to focus on strategic financial activities. Suppliers experience simplified procurement processes, fostering better collaboration and efficiency within the retail supply chain.

 

How to choose the right intelligent document processing software?

To choose the right Intelligent Document Processing (IDP) solution, start by understanding your business needs and identifying the types of documents causing slow processing. Assess the volume and complexity of these documents. Then, look for an IDP solution that offers features like OCR, NLP, and ML to handle diverse documents efficiently. Consider factors such as scalability, integration capabilities, and vendor support. By aligning the solution with your requirements, you can streamline document processing and improve overall efficiency.

 

The future of document processing

As far as document processing goes, the future HAS arrived. With the rollout of intelligent technologies like AI and ML across the business landscape, it was a matter of time before this typically tedious process was transformed. The future will see Leger Clerks and other document processing roles be empowered as less time spent processing documents means more time focusing on tasks of strategic value.

 

For Financial Managers, the future is more streamlined as automated document processing removes the need for manual reporting and meetings with Clerks. Instead, this will become accessible from a single interface.

 

Finally, the future can be expected to be an even faster pace than it is now. As AI and ML continue to involve and improve, they will only become faster and more efficient at their job. This could fuel an arms race for even faster business operations as AI-fuelled efficiency becomes the new norm.

 

How Bluestonex can help

Bluestonex are experts in process automation. We are also massive advocates of automating the tedious, inefficient and boring processes many businesses still carry. To do just this for document processing we developed Documait- an intelligent document processing software that’s the first of its kind as a cloud-based SAP native solution. Click here for more about Documait.