If your business is in the process of adopting document digitization, you are likely faced with the task of converting paper documents into digital formats. Yet, managing and arranging these digital files can prove to be unexpectedly intricate and time-consuming, requiring a significant investment of your time and resources.
So, how can you simplify this process? Document indexing is the key solution. By automating document indexing using intelligent document processing software, your business can enhance its digital archive and existing database.
In this blog, you will learn about the concept of document indexing, the types of file indexing, and what the overall process looks like. Lastly, you will discover how to index documents using Klippa’s IDP platform. Let’s start!
What is Document Indexing?
Document indexing is the process of organizing documents with proper tags or labels to improve visibility when searching or retrieving documents from large databases or indexes. This approach enables swift and effective searching of documents at all times.
Think of file indexing as the search-engine equivalent of adding color-coded post-it notes to book chapters, to make them stand out and easily find exactly what you are looking for.
An organization may, for example, index documents according to employee name, date, customer number, client name, or other important attributes that are used in everyday business. Before indexing, however, it is important to first determine which indexing type is best suited for your business.
Types of Document Indexing
When it comes to indexing documents, there are several approaches you can choose from. The method you select depends on your unique use case and the volume of documents you intend to index.
Full-text Indexing
Full-text indexing involves scanning the entire contents of the file, giving you the ability to search anywhere within the document for keywords or phrases that help you find what you’re looking for.
This method is synonymous with the ever-so-popular command “find” (Ctrl+F or Command+F), found in the majority of processors and web browsers. It is also the easiest type of indexing you can use, as it is intuitive for users and frankly, quite straightforward.
Metadata Indexing
As its name suggests, for this type of file indexing, you add metadata when scanning or digitizing the respective file. Metadata is represented by tags or other information that is relevant when searching for documents at a later time.
When it’s time to retrieve a document, the software scans only the metadata, instead of the entire document. Metadata can also be considered as alt text, which instead of being used for describing or labeling visuals, is used to label documents.
Automated Indexing Using Field Data
Similar to metadata indexing, field-based indexing focuses on various information sources within a database, otherwise known as data fields. It automatically targets key data fields, such as customer names or document numbers, which are then matched up against an existing database.
For example, if you work mainly with financial documents, you might use field-based indexing to search your database for entries that have a certain name in the “vendor” field or a certain number in the “total amount” field.
How does Document Indexing Work?
Determining the best-suited document indexing type involves first understanding the intention behind indexing documents. It’s important to determine the specific information employees are likely to seek and the terms they typically employ in their searches, to facilitate this process.
Once you’ve grasped your employees’ preferences and identified the optimal document indexing type, the actual process of indexing documents remains relatively uncomplicated. It is mainly concerned with systematically sorting through both scanned and digital documents to locate designated key terms.
Identify the Specific Purpose for Indexing the Documents
The choice of indexing method hinges on the nature of the documents you’re dealing with, whether they are invoices, employee records, or any other type. It’s crucial to also consider who has access to retrieve these documents and for what purpose. For instance, understanding if employees need access for reference or if specific teams require it for analytical purposes will guide your indexing strategy.
Determine the Best Indexing Method for your Use Case
Certain document categories may require less detailed indexing for convenient retrieval. Take invoices, for instance, where basic information such as the vendor’s name or account number could be sufficient for effective file indexing and quick retrieval.
Index the Relevant Data
Once the optimal document indexing type has been identified, you have the option to either manually index the data or, preferably, delegate the task to a software solution:
- Manual indexing: Manual indexing relies on establishing connections between words in a document and a specific term, which is used to retrieve the file later in time. that are manually assigned as indexing terms. However, the rate of encountering duplicate metadata descriptions is also enhanced, making it a challenge to track all manually indexed documents accurately.
- Automated indexing: Employing software for automatic document indexing simplifies the process greatly. It only requires establishing rules that specify what document types should be prioritized, allowing for automated classification and sorting to happen, all based on a certain keyword.
Now that we’ve peeled back the layers of how document indexing works, let’s see the practical advantages that make automated document indexing a game-changer.
Benefits of Indexing Documents
- Improved information flow: The challenge of locating documents is a common hassle for many organizations. Some files are digitized, others are buried in email attachments, and some still exist in a traditional paper format. With automated document indexing, finding and retrieving documents is easier, improving the whole flow of information.
- Facilitates better collaboration and streamlined workflows: Simplified document access promotes more effective teamwork, with shared and indexed documents ensuring that the appropriate employees can access the required information anytime, anywhere.
- Simplified audit compliance: When documents are well-organized and indexed based on factors such as fiscal year and other relevant metrics, retrieval becomes effortless in the event of an unplanned audit.
- Time-saving: Employees invest a significant amount of time filing through documents to locate the necessary information or files. Implementing an effective indexing process allows you and your team to redirect this time toward more strategic endeavors for your business.
- Cost Efficiency: Organizations often incur unnecessary expenses as employees dedicate substantial time to manually search for documents. By adopting an automated document indexing system, you not only save time but also reduce operational costs associated with labor-intensive document retrieval.
For precise automated document indexing and high-quality results, a reliable Intelligent Document Processing solution is essential. The Klippa IDP platform provides your business with the essential tools to swiftly index all your business’s files.
Automate Document Indexing with Klippa IDP Platform
Klippa DocHorizon stands as an Intelligent Document Processing platform designed to automate the process of indexing all types of documents you need. Through seamless integration of various platform modules with your preferred applications, you can establish a smooth and tailored workflow.
- Data extraction – Get data extracted automatically from a variety of documents
- Document conversion – Convert documents into a number of business-ready data formats, such as JSON, XLSX, CSV, TXT, XML, and many more
- Document sorting – have your documents sorted based on their industry or use case, for an enhanced use of document management
- Document verification – Automatically verify documents in numerous ways and detect document fraud
With our unique flow builder, you can create your own document indexing workflow, in just 5 steps:
- Add a new file in your drive: Upload the document you want to index to your Drive.
- Export file from Drive: In the flow builder, choose the Drive input and select the recently uploaded document.
- Capture the document with the relevant model: Make sure to select the document capture mode and establish the certain data fields you want to be extracted. Then, add a tag, depending on your use case.
For example, if you want to index bank statements and want to retrieve them by searching for their customer number, select the respective fields to be extracted. Then, add a corresponding tag, to ensure the search will lead you to these specific fields.
- Create a new folder for the indexed documents: After adding the corresponding tag, create a new folder and rename it with the desired tag. From then on, all documents indexed with the same tag or data field will be forwarded there.
- Copy and export file: When the process is done, copy the file, and the document will be renamed based on the extracted data.
For instance, if you extracted customer numbers, the document will be renamed with the customer number extracted.
And now you’re done! Manual file indexing is a problem of the past, courtesy of our IDP platform. If you want to know more, don’t hesitate to contact our experts or book a demo down below!