Key Takeaways
- Extracting data manually from scanned PDFs is time-consuming, error-prone, and inefficient.
- OCR technology significantly automates data extraction, improving accuracy and productivity.
- Parseur provides advanced AI-powered OCR tools that handle diverse document formats efficiently.
- Choosing the right PDF parser depends on your document complexity and data needs.
What are Scanned PDFs?
Scanned PDFs are image files that contain visual representations of text and graphics. Unlike regular PDFs created digitally, scanned PDFs require unique technology to convert their content into editable or searchable text. This conversion process, Optical Character Recognition (OCR), transforms static documents into actionable data
The Challenge of Extracting Data from Scanned PDFs
Extracting data from scanned PDFs can be challenging, especially if your business handles large documents. According to a report by McKinsey, employees spend nearly 20% of their workweek searching for internal information or tracking down colleagues who can assist with specific tasks, which can significantly reduce productivity. Scanned PDFs, typically images of text, present unique challenges as they cannot be edited or searched directly. Manual data extraction from these files often leads to costly errors and inefficiencies.
Manual PDF Data Extraction: A Real-Life Scenario
Consider a real-world example of a medium-sized accounting firm receiving hundreds of scanned invoices monthly from various clients. Typically scanned into a PDF format, each invoice must be manually processed by employees who read the scanned document and manually enter critical details, like invoice number, date, vendor name, payment amount, and due date, into an accounting system or Excel spreadsheet.
This manual process involves several steps:
- Opening each scanned PDF individually.
- Carefully reading each document line by line.
- Manually entering data into the desired system.
- Verify the information entered multiple times to correct inevitable errors.
According to Symatrix (2019), the probability of human error when manually entering data into simple spreadsheets ranges between 18% and 40%. In practical terms, this means that out of 500 invoices processed manually, as many as 25-50 could contain errors, causing payment discrepancies, incorrect financial records, strained vendor relationships, and delayed workflows.
Challenges Using Non-Parsing Tools: A Common Pitfall
Businesses sometimes use basic OCR tools that convert scanned images into editable text. However, these tools frequently struggle with varied or complex layouts. For instance, a logistics company may receive scanned shipment forms from multiple partners using different layouts. Non-specialized OCR tools often produce unstructured and messy outputs, forcing employees to spend extra time reorganizing the data, thus negating any potential productivity gains from automation.
A recent case study from Jumio (2019) found that leading OCR solutions achieve accuracy rates of 79%- 88% under ideal conditions but drop to 28%—62% with blurred or skewed images, highlighting their struggle with complex layouts and poor-quality inputs.
The Real Cost of Manual and Non-Parsing Solutions
The cumulative impact of manual or inadequate automated processes results in substantial productivity losses and significant financial costs. According to Sprout HR Solutions’ study, the expense of manual data entry alone amounts to $4.65 per entry. These costs can accumulate significantly; for example, manual processes in HR and payroll management can lead to annual revenue losses of 20-30% due to inefficiencies.
The indirect costs, including employee frustration, increased staff turnover, and client dissatisfaction due to errors, are equally substantial and can negatively affect a company's reputation.
The role of AI and advanced OCR in PDF data extraction
These technologies recognize text from scanned images and interpret, structure, and organize extracted data intelligently, surpassing traditional OCR methods in accuracy and efficiency.
But what is the best tool for scanning PDFs?
With so many online tools available on the market, it can be difficult to choose the right application for your needs.
You'd want to invest in a tool that can:
- Support any format and layout
- Handle large amounts of data
- Extract table data without losing its original formatting
- Send that data to any other application in real time
Why Parseur is the Best Tool for Extracting Data from Scanned PDFs?
Parseur combines advanced AI-powered OCR with robust data parsing technology, making it ideal for automating PDF data extraction. We understand that this may sound like a biased claim, but hundreds of customers agree with us.
Benefits of Using Parseur:
- High Accuracy: Parseur’s AI-driven OCR technology achieves accuracy levels exceeding 98%, significantly reducing manual intervention.
- Flexibility: Easily adapts to various document formats, including invoices, forms, receipts, and contracts.
- Integration: Seamlessly integrates with numerous apps via Zapier and Make, enabling automated data flow directly into your workflows.
- Scalability: Ideal for handling both small and large volumes of documents without compromising accuracy.
How do I extract data from a scanned PDF to Excel?
Follow these steps to automate your scanned PDF data extraction:
Step 1: Sign Up and Create Your Parseur Mailbox
Visit Parseur to sign up and start your free trial.
Step 2: Upload Your Scanned PDFs
- Upload your scanned documents directly to Parseur.
- You can also forward scanned PDFs via email.
Step 3: AI extracts data automatically from the scanned documents.
- The AI-powered OCR technology automatically recognizes text and data patterns.
- You can also create a custom template with the ready-made fields provided.
Step 4: PDF to Excel
- Follow the instructions here to send PDF data to any application instantly.
Extracting data from scanned PDFs doesn't have to be complicated or time-consuming. By leveraging advanced OCR technology, specifically tools like Parseur, businesses can significantly enhance productivity, accuracy, and efficiency in their data extraction processes.
Frequently Asked Questions (FAQs)
Q: Can we extract data from scanned PDFs?
A: Yes, use a PDF parser to extract data from scanned documents.
Q: Can Parseur handle handwritten text in scanned PDFs?
A: Parseur’s advanced OCR capabilities can handle well-written handwritten text with impressive accuracy.
Q: Is data extraction secure with Parseur?
A: Absolutely. Parseur complies with GDPR and employs strict encryption and secure cloud storage to keep your data safe.
Q: Can I integrate Parseur with my existing software?
A: Yes, Parseur integrates seamlessly with numerous applications through Zapier, Make, and robust APIs.
Q: Can ChatGPT read and extract data from scanned documents?
A: ChatGPT can do only simple data extraction from PDFs.
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