How to extract data from a Purchase Order?

Purchase Order (PO) is a legal contract/agreement of a transaction between a buyer and a seller. If any errors occur while capturing data from this document, it can have a significant impact on the business. With various departments submitting their purchase requirements, accounts payable teams often have to handle a huge number of POs. Processing all these documents accurately is nearly impossible when done manually.

However, automated tools for PO data extraction make accurate processing achievable. These tools can handle a vast number of documents simultaneously, reducing errors by 90%. They also increase processing speed by a factor of five by minimizing manual data entry by 80%. Increased efficiency leads to better productivity overall, which results in revenue growth.

In this blog, we will learn more about the concept of PO data extraction, its benefits, and how it can be effectively implemented using KlearStack.

What is Purchase Order Data Extraction?

Purchase order data extraction is transferring information from documents into the system, facilitating further processing. This task can be done manually or automatically through automated software and tools available for this process.

Data extraction process through automated tools is crucial for documents like purchase orders. There is a high level of accuracy required in capturing this data which can be achieved through automated tools.

Manual PO Data Extraction vs Automated PO Data Extraction

Manual data extraction

Manual PO data extraction is the process of entering the information in the system from the documents manually. This involves checking each field and entering the corresponding information into whichever system the organization is using for further processing. 

Automated data extraction

Automated PO data extraction relies on Intelligent document processing (IDP) to process purchase orders. Using Artificial Intelligence (AI) and Machine Learning (ML), these tools convert data into digital formats for easier processing. By accurately extracting data from documents, they minimise errors and decrease the need for manual tasks. This results in the better adoption of Enterprise Automation, which leads to faster and more efficient operations.

How does Purchase Order data extraction software or tools work?

The Purchase Order data extraction tools make use of advanced technologies available, such as Artificial Intelligence (AI) and Machine Learning (ML). Additionally, Optical Character Recognition (OCR) is used which ensures better results in data capture. KlearStack stands out as a comprehensive solution for the data extraction process from various documents, including crucial ones like purchase orders. It accurately collects and enters all the sensitive information with high precision.

Here is the process to understand how data extraction is done with KlearStack:

Pre-processing

Pre-processing gets a scanned or photographed PO image ready for further analysis. This step involves reducing noise, enhancing the image, and aligning it for clarity and uniformity. These improvements ensure accurate character recognition and data extraction in subsequent stages.

Document Classification

Document classification is a process where the categorization of documents is done. It involves identifying the document type such as receipts, invoices, and purchase orders, etc., and putting them in the correct category. Machine learning algorithms are often employed to recognize patterns and features unique to each document type. Proper classification ensures the correct extraction rules and templates are applied for accurate data processing.

Automated Capture & Digitization

Automated capture and digitization is a step where a physical purchase order gets converted into a digital format using OCR technology. This process scans the document to create a machine-readable text version, which can then be stored and managed electronically. The digitized data serves as the foundation for further processing and analysis.

Intelligent Data Extraction and Analysis

Intelligent data extraction and analysis involve identifying and extracting key details from digitized purchase orders, such as dates, amounts, shipping information, and delivery terms. Advanced algorithms and machine learning techniques ensure accurate identification and interpretation of these fields. The extracted data is then analyzed to verify its completeness and accuracy.

Validation & Integration

Validation and integration ensure the extracted data is accurate and ready for use in other systems. In this process extracted data is verified against existing databases, to identify errors and ensure that the data meets predefined business rules.After validation, this data is integrated into enterprise resource planning (ERP) systems, accounting software, or other platforms that the organization might be using.

RESTful API Integration

RESTful API (Application Programming Interface) integration allows the purchase order OCR system to communicate and exchange data with other software applications online. By providing a standardized connection method, APIs enable smooth integration of OCR functions into existing workflows. Due to this automation, data is transferred automatically. This minimizes manual efforts and increases overall efficiency.

Benefits of using Automated Data Extraction From Purchase Orders

Purchase Orders have legal implications; hence, any errors in their processing result in serious consequences for businesses. Therefore, finding a reliable method to prevent these issues becomes crucial, and that’s where purchase order automation comes into play. The advanced technologies used in these tools manage the entire process very well. AI, ML, and OCR are crucial in automating this process with minimal human intervention.

Automated data extraction benefits organizations in the following ways:

• Improved Accuracy and Compliance: 

Automated systems reduce the risk of errors in PO processing, ensuring that all details such as item quantities, prices, and delivery dates are accurately captured. This precision helps maintain compliance with contractual obligations and regulatory requirements, reducing the likelihood of disputes and financial penalties.

• Cost Reduction:

By minimizing manual data entry and associated labor costs, automated PO processing leads to significant cost savings. Additionally, the reduction in errors and the ability to process POs more quickly help avoid costly delays and corrections.

• Enhanced Supplier Relationships: 

Accurate and timely processing of POs fosters better relationships with suppliers. Automated systems can quickly generate and send POs, ensuring that suppliers receive clear and accurate orders, which can lead to more reliable and efficient supply chains.

• Scalability:

As businesses grow and the volume of POs increases, automated systems can easily scale to handle the additional workload. This scalability ensures that the PO processing remains efficient and effective, regardless of the number of orders being managed.

Step-by-Step Guide to Extract Data from Purchase Orders Using KlearStack

Features of KlearStack’s PO OCR

1. Template-less Solution:

Invoice OCR by KlearStack has a template-less solution, which means that it can extract data from any new PO layout accurately. Model retraining is not required every time. It can handle varied types of designs and adjust to new layouts as required. This saves time and resources.

2. Multi-lingual Support:
KlearStack provides support for 50 languages for PO data extraction. Languages supported include English, Hindi, Marathi, French, German, Chinese, Japanese, and more. When businesses have operations with overseas suppliers, this feature becomes of great importance. Multi-lingual support ensures that language barriers do not hamper efficient PO processing.

3. Bulk Purchase Order Processing: 

With this feature of KlearStack’s PO OCR, multiple POs can be processed at once. 

This increases the speed of the overall process and a large number of POs can be processed in one go with better efficiency and in less time.

4. Line-item Data Extraction:

This ensures all the crucial line items are extracted correctly from the POs. These items include product descriptions, quantities, unit prices, total amounts, etc. This accurate data extraction is crucial for financial analysis and inventory management. It is also important to ensure that the items on the PO match the invoiced items and received goods.

5. Multi-page Data Extraction: 

KlearStack’s PO OCR offers support for multi-page data extraction. This ensures data is extracted with precision across all pages. This feature is specifically essential for large POs or those with extensive itemized lists, ensuring that no critical information is overlooked.

6. Self-Learning Algorithm:

KlearStack has a continuously learning AI and it keeps improving its accuracy over time. As it processes more POs, it becomes better at identifying and extracting relevant data points. This feature eliminates the need for constant manual intervention.

7. Seamless Integration:

KlearStack’s Invoice OCR can be easily integrated with your existing ERP and accounting systems. Because of this integration, extracted and validated invoice data directly gets transferred into financial management systems. This cuts down on the need for manual data entry. This boosts the overall productivity and efficiency of the processes.

8. Document Classification: 

In document classification, it becomes possible to categorize the document based on its content. KlearStack’s PO OCR is trained to identify  the documents as purchase orders, invoices, receipts, or other relevant categories. This helps in better organization of documents and streamlines the process for all the relevant departments.

9. Automated Document splitting

Because of this feature provided by KlearStack, it becomes possible to separate a PO from other documents that may be attached to it such as an invoice or receipt. When it is essential to analyze the data from each page, this feature proves to be a boon.

10. Rich Document Audit Engine: 

Audit Engine provides you with an option to set rules for auditing or checking the extracted data against it. If the data meets the rules or conditions that are set it is processed further, if it does not meet then that particular case is flagged for review.

11. Rules-based workflows: 

Rules-based workflows are a systematic way to route a particular bunch of data or documents to the appropriate team or member. Here you can set up criteria based on different specifics, such as the total amount, the name of the supplier, or any other relevant condition. Based on these criteria your documents will be automatically processed without the need for human intervention.

Schedule a demo with us to know more!

KlearStack is a one-stop solution for your PO data extraction requirements. It extracts the data with precision and categorizes it properly for further processing. You can upload POs in any format, semi-structured or unstructured, and KlearStack will process them with significant accuracy. It supports over 50 languages and expertly trained models extract data seamlessly.

Curious about how KlearStack achieves this? We invite you to test our system in a demo with any PO format, structured or unstructured. Experience KlearStack’s exceptional data extraction capabilities. Yes, we’re ready to undertake this blind test.

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