By 2026, the market for Document Analytics is projected to reach $8.15 billion, expanding at a CAGR of 49.58%. Additionally, the increasing demand to improve customer experience and the usage of cutting-edge technologies present the document analytics market with high growth opportunities.
Document Analytics suits business deals of any size and can be applied to any domain. Many verticals have benefited by adopting it.
Many firms have overcome issues that consume the majority of human time and effort with them. Below are a few use cases and benefits incurred on deploying Document Analytics.
Use Cases for Document Analytics
Analytics on MultiLingual Documents
An International law company had a large volume of data (more than 500 GB approx.) with documents in both English and Korean. The company sought a solution that could identify duplicate files in both languages without erasing important data.
The solution involved concept searching and near-duplicate recognition of documents written in foreign languages which provide information about data with filtering. Technology Assisted Review (TAR) was used in a multilingual review along with an analytics engine that supports foreign languages.
Voluminous document management
A firm involved with the lawsuit had data that was gathered and only partially processed before it went idle for more than three years. The team preferred to use the partially processed data when the case became active again. Nearly 18,000 documents had to be examined in one week.
Data such as the document’s title, author, creation and modified dates, etc., were absent from the documents that had not yet been analyzed. The team was unable to filter them as they had not been processed earlier.
The analytics tools assisted the law firm by finding topics on which reviewers may focus. The solution analyzes document content based on specific phrases and compares document content based on the degree of similarity. They identified and grouped related messages and suppressed those containing duplicate content.
Document classification using Analytics
In response to a summons regarding one of its clients’ fraudulent behavior, the bank had to submit details on everybody connected to the bank. Nearly 2.2 million documents of client data, mostly emails, were with the bank. The bank was required to categorize the data accordingly.
Entity analytics were used as part of the solution to identify and group individuals, organizations, email domains, and email threads. The bank could quickly visualize the data and group information on each outlying client using this analytical technique.
Benefits of Document Analytics
Since the volume of document data is very high in the modern era, manually looking upon and analyzing documents consumes a lot of time and firms can benefit by using analytics over them. For example, in the above-discussed use case, with document analytics, the firm was able to review over 18,000 documents within a week.
Cases might occur like the same document getting saved in multiple locations. These duplicates take up extra storage space. Also, humans are bound to make errors which may lead to repetitive documents. With duplicates, firms can’t get useful insights out of it.
By avoiding duplicates and bringing out the necessary documents for review, document analytics improves the accuracy of content and documentation.
Documentation which involves a lot of team effort and monitoring can be simplified and enhanced with Analytics. Thus it reduces human effort and decision-making can be made efficiently with Analytics done over documents.
Manual inspection of documents consumes a lot of time. This causes a delay in work. Firms can largely reduce this delay by using Document analytics. Thus firms can increase their productivity.
Uncover hidden opportunities
As documents are high with content, it is tough for humans to incur from them. With analytics, Firms can adopt trending technologies in their tasks for maintaining documents. On efficient documentation, they can opt for getting their firms to experience new business strategies.
Document Analytics is not restricted to a firm size or a domain as any firm can benefit from it if they have a high volume. Rather than viewing documents as a mere storage thing, firms should deploy analytics on them and reach higher levels. If you need suggestions or know more, reach out to [email protected] for guidance.