Purchase Orders OCR: Guide to Improving Purchase Orders Data Extraction and Accuracy with OCR

Using OCR to process purchase orders can significantly boost the efficiency and precision of data extraction. This guide discusses how this technology enhances workflow, integrates smoothly with current systems, and scales effectively with your business needs.

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Purchase Order OCR (Optical Character Recognition) simplifies how businesses handle purchase orders. It automatically converts the data from these documents into a digital format. This technology helps businesses speed up their operations by reducing manual work, minimizing errors, and improving the accuracy of data entry.

This article will explore Purchase Order OCR's advantages for boosting business efficiency. We'll also tackle its challenges and offer practical advice on implementing OCR technology effectively in your workflow. 

Let's get started.

What is purchase order OCR?

Purchase order OCR is a technology designed to read and convert purchase order information into digital form. It automatically extracts details like suppliers' names, quantities of items, prices, and other important information. 

OCR technology scans the document and recognizes the text it contains. It converts this text from the purchase orders into a format easily edited and stored in computer systems. This helps reduce mistakes from typing the information manually and speeds up how businesses handle these orders.

How does OCR help in purchase order data extraction?

OCR technology scans purchase orders, whether paper documents or digital files, and reads the text written on them. This includes details like supplier names, item quantities, and prices. OCR converts all this information into digital data that business systems can easily manage and analyze.

The old way of manually putting data from purchase orders into computers is slow and often leads to mistakes. When people type information into systems, they can make typing errors or get the data wrong. It also takes a lot of time, which can slow down other work and make the whole business less efficient.

OCR technology makes this process much easier by automatically reading and turning text from scanned or digital purchase orders into data that can be edited and searched. This speeds up the process, reduces mistakes, and helps businesses manage their purchase orders better.

Key benefits of using purchase order OCR

Efficiently managing purchase orders is essential for maintaining smooth business operations. Purchase Order OCR technology automates this task. This enhances both accuracy and speed in processing these important documents.

Key benefits of using purchase order OCR

Here are a few benefits of using this technology:

  • Efficiency: OCR technology can significantly reduce the time required to process purchase orders. For instance, a business that used to manually enter data from each order can now automate this process, reducing the time from several minutes per order to seconds.
  • Accuracy: Typing in data by hand can cause errors, but OCR helps a lot by getting the information right from purchase orders. This means there are fewer mistakes when filling orders and keeping track of inventory.
  • Cost savings: OCR technology reduces labor costs by eliminating manual typing. This allows companies to use their resources for more important tasks, increasing efficiency and reducing costs.
  • Faster processing: Faster order processing through OCR means quicker service delivery. For example, a supplier can process incoming orders more swiftly. This leads to faster dispatch and delivery, thus improving customer satisfaction.

  • Integration: The technology integrates well with existing ERP and CRM systems, facilitating seamless data flow and management. This integration helps maintain data consistency across all business platforms and enhances operational efficiency.
  • Scalability: As your business grows and document volumes increase, OCR solutions can scale up their capabilities. This scalability ensures that your data processing can keep pace with your expanding order volumes, effectively supporting your growth.
  • Audit trail: Using OCR provides a digital trail of documentation, which is crucial for audits, compliance, and data analysis. Record-keeping is vital for maintaining transparency and tracking historical data.
  • Compliance: OCR is useful because it helps companies follow the rules by accurately extracting and tracking data. This is super important for businesses that adhere to strict rules about managing data and keeping information private.

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Challenges and limitations of Using Purchase Order OCR

While OCR technology offers clear advantages for automating data extraction from purchase orders, several challenges and limitations exist. Let’s explore some of the main issues you might face.

Challenges and limitations of Using Purchase Order OCR

1. Accuracy issues with handwritten or poorly scanned orders

Handwritten text and poor scans can compromise OCR accuracy. To counter this, businesses can adopt pre-processing methods such as image enhancement, which helps clean up and sharpen the images, making them easier for OCR systems to read.

Encouraging digital or typed purchase orders over handwritten ones can also reduce errors.

2. Incompatibility with non-standard formats

Purchase order OCR systems may have difficulty recognizing and processing non-standard purchase order formats. This may lead to data extraction errors.Developing customizable OCR templates or using advanced OCR solutions to learn and adapt to various formats can help manage this issue.

3. Handling variations in language and format

The technology may falter with documents with multiple languages, diverse layouts, or unusual fonts.

Employing multilingual OCR systems and training them with various fonts and layouts can significantly improve their accuracy and versatility. This makes them better equipped to deal with various text types and styles.

4. Limited data capture from non-text elements

OCR is primarily designed to read text, which means it can miss information contained in tables, images, or other non-text elements.

Integrating OCR with other technologies like Intelligent Document Processing (IDP) systems, which are better equipped to understand and extract information from complex structures and visual elements.

5. Dependence on input image quality

The performance of such technology heavily depends on the quality of the input images; poor quality can lead to poor output.

Ensuring high-quality scanners and taking steps to standardize the capture process can greatly improve the input quality. Regular maintenance of scanning equipment and training staff on optimal document preparation techniques can also help.

Fields that can be extracted from purchase orders using OCR

OCR technology can significantly streamline the procurement process by automating the capture of critical information. Here’s a look at the typical fields that OCR can accurately pull from purchase orders:

  • Supplier name: This field captures the name of the company or individual providing the goods or services. Accurate capture helps maintain vendor relationships and ensures correct invoicing.

  • Purchase order number: Each purchase order is assigned a unique identifier. It is crucial for tracking orders throughout the procurement cycle and referencing in communications.
  • Date of issue: The issue date is when the purchase order was officially created or sent out. This date is important for tracking order timelines and ensuring timely fulfillment.
  • Item description: This section lists the complete details of each item, including model numbers, sizes, and any other key features. Ensuring the right items are shipped and useful for inventory checks is essential.
  • Quantity: This indicates how many units of each item are ordered, which is essential for stock management and for verifying that deliveries match the ordered amounts.
  • Unit price: The cost per individual unit of each item necessary for financial calculations and cost management.
  • Total cost: This field provides the total expenditure for the items ordered. It is automatically calculated by multiplying the quantity by the unit price, and it is crucial for budget tracking and financial reporting.
  • Delivery date: This field tells you the day your items may arrive. It helps you plan better and keeps things running smoothly by preventing delays in receiving necessary products and items. 
  • Billing address: This is the address to which the seller needs to send the bill. This field must be extracted accurately to ensure financial documents reach the correct department or office for payment processing.
  • Shipping address: This is the destination where the ordered items should be delivered. It is especially important for companies with multiple locations or when ordering items for direct customer delivery.

  • Terms of payments: It mentions detailed terms that outline the payment conditions. This includes due dates, early payment discounts, late fees, or installment plans. Accurate extraction and understanding of this field are essential for managing cash flow and financial obligations.

How to extract data from purchase orders using OCR

Implementing OCR for the purchase order system involves several steps. Each step is critical to ensuring the data is accurately captured and integrated into your systems.

How to extract data from purchase orders using OCR

Here’s how to implement OCR for purchase orders:

  • Image capture: Use a scanner or a smartphone camera to take high-quality pictures of the purchase orders. The pictures must be clear, and the text on the purchase orders must be easy to read.
  • Pre-processing: Once the image is captured, you should enhance its quality. Try making the text more visible by changing the contrast. Remove any fuzziness or distortions affecting text reading, and ensure the image isn’t tilted. This makes it easier for the text recognition software to do its job.
  • OCR recognition: Use OCR software to turn the cleaned-up images into text that computers can read. The software looks at the image and picks out letters and numbers. How well this works depends on the OCR software's quality and your initial image cleanup.
  • Text extraction: The next step is to extract relevant data fields after converting the image to text. This involves identifying and segregating specific information such as vendor name, purchase order number, item descriptions, quantities, and prices. Advanced OCR systems can be configured or programmed to recognize these fields based on their positions or surrounding keywords.

  • Data validation: Once the data is extracted, it must be validated for accuracy and completeness. This step might involve comparing the extracted data against predefined rules or templates, such as checking if the format of extracted dates or prices matches the expected format. Validation ensures that the data is reliable and ready for use.

  • Data integration: The final step is integrating the validated data into your purchasing or accounting systems. This allows the extracted information to be processed further. Effective integration often requires customizing the interface between the OCR output and your business systems to ensure seamless data flow.

Docsumo’s purchase order OCR API to enhance the data extraction process

Docsumo offers a robust platform designed to streamline the handling of unstructured documents by leveraging advanced OCR and machine learning technologies. It specializes in intelligently processing various documents to extract valuable data efficiently and accurately.

Docsumo's OCR API is highly effective for business use. It can extract important data from purchase orders, including purchase order numbers, dates, item descriptions, quantities, and prices. The API works well with many platforms and systems, making transferring and syncing data easy.

Because of this integration capability, data from purchase orders can go directly into ERP, accounting, or other management software. This helps make workflows automatic and reduces the need for manual data entry.

Docsumo boasts high performance and accuracy metrics. It can process documents swiftly and with a high degree of precision. Its intelligent algorithms are tailored to adapt to and learn from new document types. This enhances accuracy over time and provides reliable data extraction for critical business processes.

For businesses interested in significantly improving their document processing efficiency, considering Docsumo's OCR solutions is a smart move. Explore Docsumo’s OCR solutions and book a demo today!


OCR technology for processing purchase orders greatly increases efficiency, lowers errors, and speeds up workflows. By automating data extraction, businesses can reduce manual data entry. This leads to more accurate data handling and frees up resources for other important tasks. 

Advanced OCR solutions like Docsumo's API further enhance these benefits, making procurement processes smoother and improving overall business performance.

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Written by
Karishma Bhatnagar

Karishma is a passionate blogger who comes with a deep understanding of Content Marketing & SEO tactics. When she isn’t working, you’ll find her in the mountains, experiencing the fresh breeze & chirping sounds of birds.

What are purchase order documents?

Purchase orders are official documents issued by a buyer committing to pay the seller for the supply of specific products or services at agreed prices. They detail the purchase items, quantities, prices, and payment terms.

What is purchase order OCR API?

It automatically uses optical character recognition technology to pull information from purchase order documents. It transforms data from images or PDFs into formats that can be edited and organized. This technology enhances accuracy and speeds up the data capture process.

How accurate is OCR technology in extracting data from purchase orders?

OCR technology typically offers high accuracy, often exceeding 95%, depending on the quality of the source documents. Accuracy is influenced by document clarity, layout consistency, and the OCR solution's capabilities. Advanced OCR solutions like Docsumo continually improve accuracy through machine learning.

What is PO matching, and how do we automate it?

It compares purchase orders with corresponding invoices and receipts to ensure transaction accuracy. Automating PO matching involves using software to automatically detect discrepancies and validate details across documents. This reduces manual workload, speeds up reconciliation, and enhances financial compliance.

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