Data is the fuel of the fourth industrial revolution. Data is the lifeblood of the enterprise. Data powers the information age.

We’ve heard these statements so many times that they’ve almost lost their meaning. But what if I were to tell you that you are only using 10 to 20% of this fuel to power your business? What if there is an untapped power source at your disposal that’s being neglected? What if using this data could help produce actionable insights and allow you to bend the value curve? 

I’m talking about unstructured data – data that’s trapped in billions of enterprise emails, PDFs, images, handwritten notes, forms, audio, and video files. This data forms 80 to 90% of your enterprise data, and today, you are not deriving enough insights from it. That means that you are making decisions based on less than half the information available. What does that say about the accuracy of these decisions? Yes, they are better than those made without any data at all. And they will continue to give you value as data volumes increase and you apply analytics to more aspects of your business. But that is the value of momentum. When added to this mix, unstructured data can bend the value curve for exceptional returns. 

Creating New Opportunities by Transforming Unstructured Data into Insights 

Hundreds of billions of dollars are invested in data and analytics solutions every year. Yet, business growth in the digital world is often hindered and slowed by the complexity of data extraction from various enterprise documents. What enterprises need is a comprehensive strategy towards understanding and leveraging unstructured data that will enable exponential growth. In our experience of working with large enterprises, we have seen insights-driven enterprises make smarter business decisions when compared to other enterprises.

Existing technologies for document digitization face three significant hurdles:

1. Unlocking information becomes difficult as document complexity increases: With documents with numerous elements, complex layouts, and varied templates, we need technology to read all the formats and digitalize them accurately – be it handwritten text, tables, images, or logos.

2. Domain specificity requires customizable solutions: When digitalizing documents, the technology needs to align with domain-specific context. The document types vary with each sector and business, including invoicing, waybill formats, tax forms, and loan applications.

3. Disjointed approaches create inefficiencies: Most solution approaches are disjointed instead of ensemble learning models and unable to solve the enterprise document problems efficiently.

How then do we address these challenges? The key is to take the right approach to extract meaningful and actionable insights.      

Here are four steps organizations can take to extract insights from a large volume of data:

1. Find out what’s essential to your business: Not all data in your business is valuable. Companies often forget this and instead collect and process as much data as possible. That doesn’t deliver on your business goals and may make the initiative more complex than it needs to be. Instead of going after everything out there, the best approach is to find a few business-critical use cases. Where will data make the most impact on your business outcomes? Then identify the various data sources that contribute to this process. And finally, put in place a system to harness these data types.

2. Choose the right solution stack and customize it to your needs: When businesses adopt new technologies, it does not mean that they must completely overhaul the existing systems in place at every turn. Solutions should not be creating more work; instead, they should ease the resource bandwidth constraints. Therefore, there is a need for technologies that can seamlessly plug and play and scale and learn as the business evolves. In addition, to deliver on the promise of extracting insights from a large volume of data, the technology should be advanced enough to identify and classify documents correctly, manage variance in document formats, and increase the accuracy of extracted data while minimizing human interventions. That’s where most out-of-the-box solutions fail to deliver. They may perform exceptionally in a pilot program, but their accuracy declines over time when exposed to real-time data. When choosing a solution, look for document AI products customized to your business needs and evolve.

3. Allow for a learning curve: The promise of 100% accuracy is misleading. No AI solution will deliver 100% from the day of deployment. It’s wise to factor the learning curve into the ROI and make sure you have a human-in-the-loop to help manage exceptions. A solution that learns from these exceptions will be the one that gives you maximum value in the long run.  

4. Focus on extracting relevant insights: Merely extracting data from documents is not enough. How you use that data and get it in the hands of the right people is also extremely important. A comprehensive suite of document AI platforms and products that enables enterprises to extract actionable insights from a wide variety of enterprise documents, contracts, and legal agreements will ultimately change the game for your business.  

Insights-Driven Enterprises Will Reimagine New Business Possibilities

From our experience working with 400+ large-scale enterprises across multiple industries, we have seen clients glean insights from unstructured data to improve business efficiency and gain a competitive edge – especially in unpredictable times. For example, When the COVID-19 wave hit, banks in the U.S. had to assess and approve millions of Paycheck Protection Program (PPP) Small Business Administration (SBA)-related loan applications in a matter of days. It meant banks had to deploy millions of man-hours to execute the loan, and still, the process would remain prone to inaccuracies and errors. However, leveraging tools with computer vision capabilities to process unstructured data, banks were able to accelerate loan processing for PPP SBA loans with higher accuracy. Our company’s client, one of the oldest and largest U.S.-based financial institutions, was able to process a 25K loan application folder with over 100K documents with the speed of 15K digital forms per hour for faster execution by loan officer with around 90% accuracy.

Another instance from one of our clients, the largest telecom company globally, deals with several thousands of commercial lease contracts every day. Their contract enforcement team was inundated with over 650K commercial lease contracts. Manually reviewing the lease contracts and identifying and extracting relevant insights was tedious and time-consuming, affecting the efficiency and accuracy. They were looking for a solution that could automate the contract review process to free up the teams to focus on higher-value work and potentially enable them to save millions. By leveraging intelligent document processing tools paired with automation, this organization was able to identify and extract actionable insights from over 650K historic commercial lease contracts. Their team’s productivity improved by 60%, and they achieved $20 million in savings by leveraging the insights like deviations in contract terms and clauses and the presence of favorable clauses in the contract to impose penalties on defaulting vendors.

The needle on document AI technologies is moving fast. As COVID-19 accelerates digitization, the window to leap ahead of the competition is getting smaller. If you haven’t yet given a thought to unstructured data in your business, the time to do it is now!