As your business transitions from paper to digital recordkeeping, you’ll need to consider how you will effectively tag, categorize, and retrieve your digitized documents. Organization is one of the most critical aspects of the scanning process, and the effectiveness of your digital recordkeeping system hinges on how well its executed.
Properly tagging and categorizing your documents transforms what would be a scattered mess of digital files into a well-organized, text-searchable archive of information, allowing you and your team to quickly and efficiently retrieve the documents you need at a moment’s notice.
In this article, we will explain what document indexing is, the benefits of proper indexing, and its pivotal role in the document scanning process.
What is Document Indexing?
Document indexing is a tagging and categorization process that makes it easy to locate and retrieve specific pieces of information within a given set of documents. By extracting key identifiers from each document and attaching them as metadata, indexing allows you to retrieve any file based on the most relevant information it contains using intuitive text-based searches.
Typically, indexed fields include details like names, invoice numbers, or other unique identifiers, information you’d naturally think to search for when locating a document. This makes finding the right file faster and more efficient, ensuring your team can access important information with minimal effort.
Indexing is especially beneficial for those managing large volumes of records, where manual searches are often impractical, inefficient, and time-consuming.
How Does Document Indexing Work?
Document indexing is a multi-step process that turns an unorganized collection of files into a streamlined, efficient recordkeeping system. Below is a breakdown of the 7 main steps involved in the indexing process:
Step 1. Identify The Index Fields
The first part of the indexing process is identifying which “fields” or identifiers within each document are useful for tagging and retrieval. This could be the document’s title, date, author, invoice number, or any other data you’d like to make text searchable. At least one of these fields should be unique within a given set of documents, giving each its own “address” which can be used to retrieve it.
Step 2. Digitizing the Documents
Once the index fields have been identified, the next step is to scan the physical documents and convert them into digital files. High-quality document scanners are used to create digital copies, typically in formats like PDF or TIFF. During this step, if a single unique index field is chosen, such as an invoice number, that data can be extracted and used to name the file, ensuring easy identification.
Documents of the same type are often scanned and stored together, streamlining the data extraction process and helping to organize them from the start. This grouping allows for more efficient indexing and makes it easier to manage related files as a cohesive set.
Step 3. Manual or Automated Indexing
Depending on the number of indexes and the complexity of the documents being scanned, the indexing process can be completed either manually, automatically via specialized software, or a combination of the two.
Manual Indexing
Manual indexing allows for greater accuracy and context-aware tagging, especially for complex or nuanced documents that automated systems may not fully understand.
Human operators can also make judgment calls about ambiguous or unclear data, ensuring that the index is as informative and useful as possible.
In industries where precision and legal compliance are critical, manual indexing is a common choice, adding an extra layer of reliability and quality control to the process.
Automated Indexing
Automated indexing, often performed using optical character recognition (OCR), offers greater speed and efficiency, particularly for large-scale projects involving thousands of documents. This method is highly effective for standardized forms or documents with a consistent layout.
While automated indexing can be more cost-effective, human operators still play a crucial role in reviewing and verifying automatically generated indexes to ensure the highest accuracy. This combination of technology and human oversight helps maintain quality, especially when dealing with documents that require precision.
Step 4. Adding Metadata
Metadata, often described as “data about data,” is additional searchable information that is attached to your digital files. It typically includes details about who scanned the document, when it was scanned, which department it belongs to, and any other useful information you deem relevant.
This extra layer of information enables more advanced searches, allowing users to filter documents by specific attributes, improving retrieval speed, and ensuring accuracy when locating files.
Step 5. Index Validation
To ensure that the indexing is accurate, it undergoes a manual validation process. Typically, multiple operators will manually tag each document based on the index fields identified, and the results will be compared for differences, also known as double blind data entry. When differences between two data entry operators are found, a third operator will conduct a manual review to resolve these differences.
Step 6. Storage and Retrieval
Finally, the indexed documents are stored and managed using either electronic records management software or another type of digital repository. These systems boast advanced search functionalities, enabling users to quickly locate and retrieve documents by utilizing the indexes and metadata generated in the previous steps.
Step 7. Ongoing Maintenance
The work doesn’t end once the documents are indexed and stored. Periodic reviews are essential to update indexed fields, add new documents, and remove or archive documents that fall outside your organization’s retention policy.
Why is Document Indexing Important?
Indexing transforms a chaotic collection of digital documents into an organized, easily navigable digital archive. This makes it far simpler to locate, access, and manage crucial information, thereby saving time and reducing operational costs.
From a business perspective, efficient indexing enhances productivity. Employees no longer have to wade through heaps of paperwork or click through numerous folders and filesystems to find what they’re looking for. A well-indexed system enables quick and precise document retrieval, which can be crucial in time-sensitive situations such as legal disputes or compliance audits.
Quality indexing also has a direct impact on decision-making. Accurate and quick access to relevant information enables better, faster decisions, reducing delays that could otherwise hamper business operations.
In highly regulated industries such as healthcare, finance, and law, the quality of indexing can even affect compliance with document retention and access laws, making it a risk management tool.
As the volume of data you need to manage continues to grow, the importance of effective indexing is magnified. Without it, you’re essentially gathering heaps of potentially useful information, but with no efficient way to utilize it.
The indexing process itself is central to the efficacy of any document management system. Poorly indexed documents are as good as lost, rendering the entire effort of scanning and storing them virtually useless. Therefore, the quality of indexing is not just an added feature but a fundamental component of a successful, usable digital recordkeeping system.
Which Parts of a Document Should Be Indexed?
Determining which data should be a part of your indexing process is a critical decision that hinges on various factors, including the nature of your business, the types of documents you handle, and how you expect to use those documents in your day-to-day operations. Here are some guidelines to help you make an informed choice:
Understand Your Business Needs
Start by identifying the key performance indicators (KPIs) or business objectives, and choose a document management system that supports them. Are you primarily concerned with quick retrieval, compliance, data analysis, or a combination of these?
Understanding your primary goals can help you identify which data fields are most important.
Analyze Document Types
Look at the types of documents you are dealing with. Are they invoices, employee records, legal contracts, or something else? Different documents will naturally contain different types of information that could be valuable for indexing.
For example, when indexing employee records, the primary index is typically an Employee ID number. This unique identifier ensures that each employee’s records are distinct and easily searchable, reducing the risk of mixing up records for different individuals who may have similar names or other common attributes. Since Employee IDs are unique and consistent, they serve as an effective primary index, allowing for quick and unambiguous retrieval of each employee’s information from the document management system.
For invoices, the Invoice Number is commonly used as the primary index. Invoice numbers are unique identifiers that are generated for each transaction, making them ideal for quick and precise retrieval. Using the Invoice Number as the primary index ensures that each invoice can be distinctly identified and separated from all other invoices in your document management system.
Consult Stakeholders
Speak to the end-users or stakeholders who will be interacting with the documents. They can offer valuable insights into which fields they commonly refer to when searching for documents. This can help you avoid over-indexing or under-indexing your documents.
Common Fields for Indexing
For most businesses, common fields to consider for indexing include:
- Document title or name
- Date of creation or modification
- Author or creator
- Document type (e.g., invoice, contract, email)
- Associated project or department
- Keywords or subject matter
Regulatory Requirements
In some industries, there are specific compliance requirements that dictate which fields must be indexed. Make sure to consult any relevant guidelines or legislation to ensure you’re in compliance.
More Isn’t Always Better
While it might be tempting to index as many fields as possible, this can backfire. Over-indexing can make the system complicated and slow, making it difficult to find documents efficiently. It’s better to start with the most critical fields and expand as necessary.
Conduct a Pilot Test
Before fully committing, conduct a small-scale pilot test of your proposed indexing system. Gather feedback from users to understand if your choices meet the practical needs of those who will be using the system.
By thoroughly considering these factors, you can develop an effective indexing strategy that aligns with your business objectives, ensuring that you not only store documents but make them readily accessible when needed.
What Are The Types of Indexing Available
When it comes to document indexing, there isn’t a one-size-fits-all approach. Different types of indexing cater to varying requirements and document management needs. Below are some commonly used types of indexing methods:
Full-Text Indexing
This is one of the most comprehensive forms of indexing. In full-text indexing, every word within a document becomes a searchable index. This allows for very detailed searching but can sometimes yield too many irrelevant results if not used carefully.
Keyword Indexing
Keyword indexing involves tagging documents with a set of predefined terms or phrases that are important for retrieval. For instance, a legal contract might be tagged with keywords like “non-disclosure,” “liability,” or the names of the parties involved.
Field-Based Indexing
Also known as attribute-based indexing, this method focuses on specific fields within the document. For example, in an invoice, the fields could include the invoice number, the vendor name, date, and total amount. Field-based indexing is useful for structured documents where specific pieces of information are consistently located in the same place.
Conceptual Indexing
In this more advanced form of indexing, documents are tagged based on the underlying concepts or ideas they contain, rather than specific words or phrases. This is typically achieved through natural language processing algorithms and is especially useful for unstructured data.
Geo Spatial Indexing
This is a specialized form of indexing used for documents containing geographical information. It allows users to search and retrieve documents based on geographical locations, like GPS coordinates or place names.
Document Indexing Simplifies Retrieval
Effective document indexing acts as the navigational compass for your document management system, guiding you directly to the information you need without unnecessary detours. A well-indexed archive allows for quick and precise retrieval, making it easy to locate documents based on specific criteria such as keywords, dates, or custom attributes.
This eliminates the need for tedious manual searches through stacks of papers or unorganized digital folders. Instead of sifting through irrelevant or unrelated files, good indexing allows you to zero in on your target, saving you valuable time and enhancing productivity.
SecureScan: Your Partner in Flawless Document Indexing
At SecureScan, we understand the importance of accurate indexing. Our specialized processes, including double-blind data verification and automated data extraction, ensures that each document in your archive is accessible to you and your team with just a few keystrokes.
With over 21 years of experience, SecureScan has developed a reputation for delivering reliable document scanning and indexing services backed by a team of highly trained professionals. Our focus on security and accuracy ensures your records are indexed efficiently and remain protected throughout the process.
Whether you’re dealing with a few documents or an extensive archive, we have the expertise to keep your data organized and accessible. Contact us today for a free quote and find out how we can make your digital transformation smooth and worry-free.