What is Records Classification? Why is it Important?

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Written By Haissam Abdul Malak

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Ever wish you could find your records faster, and then share them with people easier? It’s hard to find that a record in your cluttered, messy office. You know it exists somewhere — but where? Records classification is often used in a company to help you find the record you need more quickly.

Records classification is the process of organizing records into categories based on their type, content, or other characteristics. This helps to improve the efficiency and effectiveness of managing, storing, and accessing the records, as well as ensuring that they are properly protected and preserved.

Typically, records are classified according to a predetermined set of rules or criteria, such as their business value, legal requirements, or retention periods. This allows organizations to easily and accurately identify, retrieve, and manage the records they need in a timely manner.

Classifying records can be manual or automatic and can be done using a variety of techniques.

Manual classification is the basic way of working and it’s usually done by experts who have knowledge about the subject and know how to classify records correctly. Automated classification, on the other hand, is performed by machines and it can be done in many ways – through optical character recognition or natural language processing for example.

According to a McKinsey report, employees spend 1.8 hours every day — 9.3 hours per week, on average — searching and gathering information

McKinsey

In any records management implementation plan and following the latest document management trends that organizations use, classification of records is a crucial step. Without it, your company will suffer significant financial loss, and your staff will stop working efficiently.

Manual Document Classification

What is the importance of records classification?

The importance of records classification is to make sure that records are handled, kept, and classified in accordance with their types, compliance requirements, and retention schedules. On the short- and long-term, this will aid organizations in saving time and money.

The benefits of classifying records in organizations are:

1- Protecting sensitive or confidential data

2- Managing large volumes of data in a structured way

3- Ensuring that records are properly classified according to the organization’s policies and procedures

4- Improving efficiency by reducing the time spent on searching for records, sorting them, and filing them away

What is the difference between manual and automatic records classification?

Records classification is a process that determines the category of records. The most common types of classification are manual and automatic. Each one has its own advantages and disadvantages.

Manual records classification is done by humans, with no real automation involved. In the past, this procedure was the only means to classify records. When working with a large number of records, it is highly difficult and error prone.

Automatically classifying records include the usage of a computer to automate the process, which can be done with or without human oversight. With the advancement of technologies, Machine Learning and AI capabilities gave us the possibilities to automatically identify the content of the record and tag them accordingly.

This process is much faster, more scalable, accurate, and cost-effective when compared with manual classification

How Automatic Records Classification Work?

In order to make an automatic records classification system work, you first need to have a list of keywords. These keywords are the ones that the system will use to classify the records. The next step is to create a list of rules that will tell the system what criteria it should use when classifying records. This can be done by writing a set of rules for each keyword and assigning them weights.

The next step is to train the system on a set of records by feeding them into it and having it classify them according to how well its rules matched up with those in its training data. This will help you figure out where your weaknesses are and what kind of adjustments you need to make in order for your automatic records classification system work as efficiently as possible.

Here is an interesting article discussing the future of classification in records management.

How RM Systems Ease the Records Classification Process?

The best DM/RM software available in the market are usually equipped with advanced intelligent document processing engines to analyze and identify the record category as soon as it is available in the system.

Here is how they work

1- Identification of content

A categorization engine will thoroughly examine the records as soon as users begin importing them into their system and will provide recommendations for the best category.

In addition to identifying the content types, it is also capable of understanding different structures; Structured, Semi structured, and Unstructured.

Based on the structure, records come in 3 categories:

1- Structured: They are a type of records that is designed to be easily understood by computers. They are designed in a way that all the content is arranged and organized in an easy-to-read format.

2- Semi structured: These are a form of record that has some structure and some flexibility. They have enough structure to be useful, but not too much so that they are overly rigid and difficult to use.

3- Unstructured: These are a new form of communication. It is a type of data that is not in any formal format, such as a spreadsheet or word file. Unstructured data is growing exponentially, and it is essential to understand the role it plays in the modern organizational context.

It is significant to highlight that this engine will continue to automatically learn about the various sorts of records used in your company and improve itself.

2- Suggest categorization

Users will be able to view the outcomes and the automatic classification carried out by the engine once the procedure has been completed. They have the ability to alter it if they are dissatisfied.

The engine will make use of manual tagging changes as a technique to improve going forward.

3- Continuous improvements

The auto classification engine is equipped with cognitive technologies to keep on improving because of its self-learning capabilities. With time, it will continue learning from previous transactions and understand more about your types.

What is the different kind of records classification?

The two broad categories of classification are:

1. Semantic classification

This type of records classification has been around for over 30 years and has been used to categorize records as spam or not spam, as well as to identify topics and themes in collections of records. The most popular algorithms for semantic classification are Latent Dirichlet Allocation (LDA) and Support Vector Machines (SVM).

Semantic classifiers use machine learning to analyze word frequencies from a collection of records and categorize them into categories.

2. Statistical classification

It is based on the statistics of how different words are used in a record or a set of records.

The process of statistical classification is based on the assumption that words in a record are related to each other, and therefore, words in a particular category will be more likely to occur together than they would be if they were randomly distributed.

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