Extracting data from your documents is one of the most important steps in the document scanning process. It determines how searchable your digital files will be and can impact how you interact with your digital files on a day-to-day basis.
People tend to overlook the importance of data extraction because it isn’t nearly as exciting as other aspects of digitization. However, understanding the options available and how they can help you enhance your digital records is crucial.
Whether you’re preparing for a large-scale bulk scanning project or are simply curious about how data extraction works, this article will provide an in-depth look at the importance of this process, as well as the various methods used to achieve it.
From Optical Character Recognition (OCR) to manual data entry and automated extraction, we’ll explore the benefits and drawbacks of each method, helping you make informed decisions for your document scanning needs.
Why Extracting Data from Documents During Scanning is Important
The data extracted from your documents during the scanning process is essential for making your digital files truly useful. Without it, you’d be left with a sea of digital image files with no way to find the one you’re looking for without manually opening each one. Talk about inefficient!
Typically, the most important information is extracted from the document and attached to the digital version as metadata. This metadata is then exposed and made searchable within a document management system, allowing you to look up any file with just a few keystrokes.
These “identifiers,” as they are called, are unique to a particular set of documents, enabling you to quickly and accurately locate specific files. ID numbers, names, invoice numbers, or a unique combination of data give each file its own unique index within your system, making your digital library much more efficient.
Using metadata to categorize and organize your files is particularly helpful when dealing with large volumes of records. This means less time spent searching for documents and more time getting work done.
Accurate data extraction also ensures that critical information is not lost and provides a dependable digital backup of your physical documents. This is crucial for industries such as legal, medical, and financial sectors, where accurate record-keeping is mandatory.
How is Data Extracted During The Scanning Process?
There are a few methods that scanning companies use to extract data from documents, each with its own advantages and disadvantages depending on the situation. Below is a quick summary of each method and how it is used.
Optical Character Recognition (OCR)
Optical Character Recognition (OCR) is software that analyzes written or printed text within a scanned document and converts it to digital text. OCR uses various methods to digitize text, examining the shape of individual characters, the words themselves, and even the context of the sentence to produce a fairly accurate transcription of the information inside the document. It handles the entire process of extracting and embedding the data into the digital file and requires no manual intervention.
The Pros of Using Optical Character Recognition:
- It is incredibly efficient: OCR can extract the text inside a document much quicker than manual methods, allowing you to quickly convert large quantities of printed text into digital format all at once.
- It makes the entire document editable: OCR extracts all of the text from within a document, allowing you to search for specific terms found anywhere in the document and even edit the text if needed.
- It’s inexpensive: Because there is no manual labor involved in the process, OCR is typically the most affordable way to extract information from scanned documents en masse.
The Cons of Using Optical Character Recognition:
- It can be inaccurate: OCR is generally good at recognizing and extracting text from printed documents. However, it often struggles with handwritten text, which can be a deal breaker in many cases. It can also struggle with extracting text from damaged documents or lower-quality scans, resulting in less accurate text conversion.
- It may require manual correction: If you need very high accuracy, manual review and correction by a human operator might be necessary, which diminishes some of the time savings of using software in the first place.
When is OCR a Good Choice?
OCR is commonly used for large-scale digitization projects where the documents are in relatively good condition and have consistent formatting, such as books, reports, and printed records. Scanning technicians can train OCR to extract data from specific fields in a form, making it an invaluable tool when digitizing a large number of records all at once.
Manual Data Entry
Manual data entry involves human operators reading and inputting data from documents into digital systems. This method is often used for complex or unstructured documents where automation might not be feasible.
The Pros of Using Manual Data Entry:
- High accuracy for complex documents: Human operators can accurately interpret and enter data, especially for varied and complex documents that may confuse automated systems.
- Can handle diverse and unstructured data: Manual data entry is flexible and can manage documents that do not follow a consistent format, ensuring all necessary information is captured.
The Cons of Using Manual Data Entry:
- Time-consuming and labor-intensive: This method requires significant time and effort, making it slower compared to automated methods. Each document must be carefully reviewed and entered by a human operator.
- Higher cost: Due to the manual effort involved, this method can be more expensive. The need for skilled operators to perform the task adds to the overall cost.
When is Manual Data Entry a Good Choice?
Manual data entry is typically used for documents that are highly varied or complex, such as handwritten notes, historical records, and forms with inconsistent layouts. This method is especially valuable when dealing with documents that require a high degree of accuracy and attention to detail. Double-blind data entry, where two operators independently input the same data, can significantly improve accuracy by flagging and resolving discrepancies, resulting in an incredibly high rate of accuracy.
Automated Extraction
Automated extraction uses software to identify and extract data from documents. This method is ideal for documents with consistent layouts and predefined fields. It combines the efficiency of automation with the precision of human oversight when necessary.
The Pros of Using Automated Extraction:
- Fast and efficient for structured data: Automated extraction can quickly process large volumes of documents that follow a consistent format, significantly reducing the time required for data entry.
- Reduces manual labor and errors: Automation minimizes the need for manual data entry, reducing the risk of human error and freeing up staff for other tasks.
The Cons of Using Automated Extraction:
- Less flexible with unstructured documents: This method is less effective for documents that do not have a consistent layout or contain varied information, limiting its applicability.
- Initial setup can be complex: Setting up automated extraction systems requires initial configuration and fine-tuning, which can be time-consuming and may require specialized knowledge.
When is Automated Extraction a Good Choice?
Automated extraction is best suited for documents such as invoices, forms, and surveys, where fields are consistently placed. It often combines OCR and manual checks by an operator to ensure accuracy, leveraging the strengths of both methods. This approach is particularly useful when dealing with large-scale projects involving documents with uniform layouts, allowing for rapid and efficient data processing.
How Do You Know Which Method is Best?
To determining the best data extraction method for your business, consider the following factors:
- Document Type and Condition: Assess whether your documents are printed, handwritten, or a mix, and evaluate their physical condition.
- Volume of Documents: Consider the scale of your project. Large volumes may benefit from automated methods, while smaller, complex sets might require manual entry.
- Required Accuracy: High-stakes documents, such as legal or medical records, may necessitate manual review to ensure accuracy.
- Budget and Time Constraints: Balance the cost and time efficiency of each method against your project’s budget and deadlines.
Many scanning projects use a combination of methods to achieve the best results. For example, predictable forms may use automated extraction, while varied documents might rely on manual data entry. Combining methods allows for a tailored approach, leveraging the strengths of each technique to handle different types of documents effectively.
Wrapping Up
Choosing the right data extraction methods will help you build a digital archive that is easy to use and efficient to search through, without adding unnecessary overhead to your scanning project. While each extraction method offers its own benefits, the best approach often involves a combination of all three. Using the right tool at the right time balances efficiency and accuracy, putting the most effort where it’s needed.
At SecureScan, we prepare for every scanning project by taking a detailed inventory of all materials, looking holistically at the entire body of documents you have to create a customized approach based on your specific needs. We combine the latest in OCR technology with our trained data entry specialists to achieve incredibly accurate results. Our goal is to not only meet your expectations but to exceed them, providing reliable, accurate, and efficient data extraction solutions.
To start your digitization project, contact us to get more information from one of our scanning technicians or get a free quote for your scanning project.
