Choose automation over monotony: intelligize your document indexing
Documentation has been vital for many centuries in preserving historical facts and has proved to be an important medium for communication and storage of information. It can be used as reference information or evidence in the form of written proof, covering a vast number of domains and industries. From text books, claims forms, legal agreements, to business partnerships, every one of these processes must be accurately documented and preserved. Some of the downsides of manual documentation are the sheer number of required human hours and related inefficiencies that can occur due to such monotonous work.
The advent of digitization has drastically reduced the manual effort required to create, store, retrieve and archive information in an easily searchable form. In fact, anything that is relevant and useful to a document can be digitized and stored for future reference. For example, an image or video recording. Also, the amount of information being generated globally is huge; 2.5 quintillion bytes of data a day to be exact, which makes it essential for organizations to have real-time access to data for additional business analysis and research.
However, in spite of the latest digital technologies available today, a number of organizations have yet to digitize their documentation processes. According to a Xerox study, 46% of small to medium-sized businesses still waste their time every day on inefficient, paper-related workflows.
Other important factors are cost and time; companies spend more than $120 billion a year on paper forms and employees spend 30-40% of their time, just looking for information kept in filing cabinets. A fraction of that money invested in the right document management system or document indexing solution could save a huge amount of money and improve resource utilization in the long run. Organizations also need to focus on data security and data utilization to drive business decision-making.
Document indexing done intelligently
You must learn to crawl, before you can walk. Data, before it can be exploited to the fullest, needs to be identified and classified under specific categories. Only then does data become searchable, retrievable, and actionable. At a basic level, data can be extracted from paper documents through scanners and converted into digital formats, such as DF, TIFF, and JPEG files. These digital formats make it easier for organizations to store and retrieve large volumes of data. Also, employees can quickly search and access the information that they need.
Traditional document indexing systems stick to the same logic to index information, time after time, day in and day out. Relentless? Yes; a lot of data can be indexed and made accessible. But what happens after that? How can an organization add more value at a larger scale? That’s when AI comes into play.
Enterprise documents largely consist of unstructured business data that remain invisible or inaccessible. Before AI, organizations would scan their documents, index them with a date, number the documents, and store them in a repository. By leveraging OCR, ML, NLP, and RPA, AI can derive an abundance of previously untapped value from enterprise documents and data.
With AI, organizations can automate document classification and processing. For example, OCR technology can read the contents of a document and automatically classify and process it, without even the slightest of human interference. The more documents that AI gets to read, the more it can detect how employees engage with the documents, and the better it gets at recognizing and processing information.
Another good example is AI-driven document clustering. AI is capable of accurately labeling vast document repositories to different topics or hierarchies, establishing relationships between documents at a higher level, and identifying similarities between documents. As a result, company documents can be effortlessly categorized and organized for easy retrieval, when in-depth analysis is required.
Successful customer engagement
One of our customers, a UK-based company specializing in retail and commercial insurance brokerage services, required an automated solution for their document indexing process. We implemented a holistic solution that would run the document indexing processing automatically through bots, with minimal downtime and completely nullifying the need of human intervention.
While ML algorithms assisted in categorizing documents, OCR tools and NLP detected patterns and extracted data with 85% accuracy. The extracted information was pivotal in improving the efficiency of claims processing by 70%.
The following diagram provides an outline of the document indexing solution:
Insurance is not the only industry that is still dependent on physical documents for their business operations. Healthcare, legal, and education are just a few of the sectors that have huge document repositories. These documents contain millions of hidden, unexploited bytes of data. Let’s take a look at how document indexing can benefit some of these sectors:
Healthcare: Healthcare providers use and generate a lot of patient-related documents, including patient demographics, patient statistics, test reports, clinical reports, surgery reports, and so on. Data from these documents can be extracted, organized, and categorized as EMRs (Electronic Health Records). An electronic health record contains diverse patient data in a digital format. Such digitally available data can help healthcare providers to access information quickly, improve the quality of care, standardize data across different sources, and aid in analytics and reporting.
Legal: Law firms, government law departments, and courts are often inundated with mandatory documents that are frequently accessed and referred. These documents contain vital information, such as case number, docket code, party names, citations, and so on. The right document indexing solution can automatically extract and organize such minute details for further review and revision. Quicker access to such data enables law firms or courts to process more cases and substantially eliminates case backlogs.
Education: Educational institutions, such as colleges, public school, and private institutions, are always looking at ways to improve their operational efficiencies by reducing their dependency on paper-based information. Educational institutions still rely on physical documentation for student and teacher records, attendance sheets, transport schedules, invoices, accounting documents, intellectual property, and so on. The conversion of such information into digital formats can help educational institutions save a lot of money and provide access to information in a centralized and organized manner.
The paper trail ends now
It is just not efficient or secure, either from a business or environment perspective, to use physical documents for storing your vital enterprise information. Business data needs to be made available within minutes, instead of hours or days, to make crucial decisions. That’s how competitive it is in the world today. Our document indexing solution is not defined by one industry and can be customized to fit the needs of your organization. The ‘one-size-fits-all’ approach is not how we engage with our clients. Get in touch with us and find out how we can make your paper trail a thing of the past, where it rightly belongs.