Since COVID-19 began to change the face of the average workplace, a huge spotlight has shone on converting paper documents to digital files. This seems simple enough – scan a document, save it to a digital format like .JPG or .PDF. There is a step to the process that is often overlooked as organizations prepare to make the big switch – indexing.
Document conversion and indexing are two separate processes, but one is nothing without the other. No digital conversion is complete without an index, and an index isn’t possible unless documents are electronically converted.
Once you begin converting physical copies to digital, indexing is the next step towards a comprehensive document management solution.
What is document indexing?
Document Indexing provides the means to search for and find documents once they have been digitized. In this process, you can tag search terms or phrases to each document to facilitate faster search and retrieval.
Data used to index documents
One of the key decisions for getting the most out of your new digital files is what indexing criteria to use.
Some examples of data used for indexing includes:
- Phone numbers
- Customer numbers
- First and last names
- Account numbers
- Invoice number
- Order number
- Keyword descriptors
One of the most important factors in choosing indexing terms is how documents will be searched for.
For example, in a series of personnel files, first and last names and employment dates would be common means of searching. At the same time, medical records could reference insurance policy numbers or patient birth date.
Referencing commonly used search terms during document indexing will provide better results when your team searches for files.
Methods for document indexing
There are plenty of methods available when it comes to indexing, and this can make it difficult to determine the best way to organize data and information.
Here are a few common options.
Full-text indexes are easily created since the system reads every word of the document and creates an index of each term and its location in the document. While they are easier to process, full-text indexes require a generous amount of storage space, which is critical to keep in mind.
Field-based indexes provide a convenient way of locating information within a database. This type of indexing option allows the user to search for unique details to each document. For example, the field could be a date, time, or any other specified field.
In this example, the index references pre-populated data, also known as metadata, to identify a document when searching. This is data that describes the document contents and is usually in the form of a summary. Metadata is typically used to supplement and enhance the original data.
What’s your best document indexing option?
Document indexing makes search and retrieval of documents seamless when applied correctly. However, the right indexing method is not one-size fits all. Whether documents are indexed by their full text, organized by fields, or supplemented with rich metadata, this choice is what drives the success of the entire system.
An experienced partner can help your team choose the proper indexing methods that fit your team’s unique practices. ILM’s team helps clients pick the best indexing methods and terms to use for the most effective searches possible. To learn more about our document indexing services, contact ILM today.