How to extract insights from data – 3 industry success stories

We’ve all heard “find more data!” at some point during our week, or our day, depending on your field of work. But what is data, why do we need so much of it and what do we do with all this data we keep seeking?

There are companies like that collect 11,000 terabytes of data from one million people every day to provide them personalized experience according to the Insurance Business report. While one cannot expect the same magnitude from other companies, there is an active hunt for data to bring about data driven actions in businesses today.

Data insights come from processing your data, collecting it, analyzing it, and then acting on the data based on the requirement from your client/ that of your company. Data insights can be achieved through effective analysis strategies that help companies to draw profits, observe patterns, and streamline efforts.

3 core components of data insights

Data – data exists in an unstructured way which may come from a database in the form of text and numbers. It exists so someone can investigate it and draw meaning out of it. Data remains objective information that is available to the readers. Data insights are more focused on the hypothesis one’s going in with. It’s the result of looking at multiple data with a set intent and then drawing conclusions that will aid in some way or another.

Analytics – with the right strategy and tools, one can go into processing data that is laid out for them. The data gets its scope from the potential it holds for analysis. With the help of data insight tools, one can draw significantly meaningful information from dry blocks of data.

Insights – Once you have processed the data, now there is room to send targeted messages, streamline efforts and learn what the data holds. You have access to actionable insights if your approach was done right, and this is the most important objective – gain meaningful insights that give you an actionable outcome.

Some statistics around data and insights

74% of companies want to be “data-driven” but only 31% actually are according to a study by Forbes. For every 100 companies where actions are data driven, 23 are struggling to be data driven in reality. Being data driven takes skill and effort that isn’t popular. Data driven organizations can recognize relevant data, draw meaningful information and use this smartly in their area of expertise. What’s also to be noted is what kind of data to seek. This will take some time but understanding what the most relevant data sources for you are will help you. Knowing where to look, aids in finding solutions faster.

Role of AI in extracting insights from your documents

The reason AI exists to process data is that it helps people focus on the result of the process rather than the enormity of the task itself. Using machine learning helps pull in a large scale of data and process them to get results based on all documents that are relevant to the objective. Bits and pieces of information can be difficult to pick up and pull apart when there is an overwhelming amount of data for people, bringing technology into it helps minimize the room for error while giving more scope for insights and messaging.

AI also goes through data very quickly. What would take a large group of subject experts a couple of days to list out, could be done in a matter of minutes through a smart tool. It could go through large chunks of data daily to provide meaningful information with no zero time and high accuracy.

Why extracting insights from data is important for enterprises

Enterprises that work with a data-driven approach are often carrying multiple advantages. They’re looking at predictable outcomes and seeking patterns that will help increase the longevity of their business. There are large chunks of data that remain available. There is an overwhelming amount of it stored in the cloud and often, it gets too overwhelming to even bother with it at all. This is where AI comes in and sorts through stacks of data to provide answers that are simple and workable.

For enterprises, gaining these insights after processing relevant data increases their chance of profile while also helping them analyze their present numbers. Some businesses must process data for their bread and butter, while some others bank on data to show them what’s missing or where to look. Enterprises and data go hand in hand and the sooner there’s insights being driven from data, the quicker one can benefit from data.

3 enterprise success stories of turning data into insights

Case Study #1

Our client, one of the largest telecommunications companies in the world used XtractEdge to automate their contract review process where in we helped identify, extract, and manage data from over 650,000+ historic commercial tower lease contracts with many amendments, addendums and other relevant documents. Text Analysis and computer vision-based methods were used to extract contract clauses quicker with maximum accuracy.

With our solution, the client’s contract team was able to claim surplus expenditures and impose penalties on defaulting vendors. We made this possible by leveraging insights such as contract terms and clause deviations plus favorable clauses. This helped our client achieve $20 million in savings annually.

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Case Study #2

Our client is a hi-tech manufacturer. Their legal team had to go through the processing of historical customer contracts. This meant manually reading and analyzing a random sample of key contracts to generate a representative assessment of potential risks / opportunities. This is where they brought us in. XtractEdge helped process the historical load of over 30K customer contracts in nearly a week’s time. Post the set up of the product, we extracted 50 intents and 125 entities from 4 different categories of contracts with carrying complexities.

XtractEdge has successfully accelerated the contracts processing for our client, boosted 70% potential workforce improvement, reduced the report generation time from weeks to a matter of days and more.

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Case Study #3

A popular US based bank leveraged the benefits of XtractEdge Platform and its computer vision capability to accelerate loan processing for PPP SBA loans with high accuracy. We took up the challenge and helped them serve many impacted customers by getting them access to PPP SBA loans. We also aided with accelerating loan processing, while adhering to stringent risk and audit requirements while also helping them achieve data accuracy of around 90%.

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Key takeaways

Data will continue to expand every minute but the weight of it? It needn’t weigh you down. With powerful AI tools, like XtractEdge, we can process data documents and provide insights and solutions to our clients. We reduce the average time these tasks take and bring you smarter set ups that will continue to enable your enterprise as you grow.

It’s important to understand how you can benefit from AI. When it comes to managing and processing data, you can lean on AI. Let it draw you observations while you can have your human resource focus on what it means and what can be down with these observations. A careful balance of AI and teamwork can help enterprises achieve what they want quicker and more accurately. AI ensures accuracy and better time saving while human resources can bring about results based on the data. With insights from your data, you can enjoy dynamic decision making which is backed by numbers and facts. Start your data journey with XtractEdge and watch your business take the way the data points at.

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