Structured Data

Improving Litigated Claims Outcomes: Structured Data vs Unstructured Data

Claims organizations have traditionally been plagued by slow and cumbersome procedures, relying on email communications to move the vast amount of data between their defense counsel and claims handlers. The data about the case, although critical to the litigation management process, ends up residing in email attachments and other locations, separate from the organization’s claims system and useless to claims leadership for analyzing and reporting. Organizing and capturing that data in a structured format has been elusive for most but is generally agreed upon as the answer to improving case outcomes and ultimately saving the organization money, time, and effort.

With data science and collection all the rage, the decision of how to organize all the customer, competitor, and organizational data is more important than ever. Most would agree that having access to data and being able to report on that data are vastly different topics.

In this article, we’ll get to the root of the differences between structured data and unstructured data. We will highlight why organizations need to structure their data, provide real-life examples of how insurance carriers are gaining data insights, and offer some tips on how insurance professionals can do the same.

What is Structured Data?

Structured data is quantitative in nature and is easily searchable because it comprises clearly defined information that fits within specific fields. Since structured data is sortable, it can be analyzed, interpreted, and acted upon.

The best way to think about structured data is in terms of what you might find in a spreadsheet. This includes data fields like name, location, unique customer or invoice numbers, reservations, inventory information, and policy numbers. It exists in what are called relational databases and lives in massive data warehouses.

You may have heard the words “Structured Query Language,” or SQL, floating around. SQL is a type of programing language that has been around since the 1970s and is what developers use when building databases that house structured data.

If your business uses a CRM software, a policy system, a claims system, or more likely, a combination of those and more – you’re already collecting structured data. The real question is, are you using that data to the fullest extent? Or better yet, what data are you missing?

What is Unstructured Data?

Unstructured data is qualitative in nature, meaning it comes in an endless variety of formats with no predefined fields. As opposed to structured data, unstructured data is not sortable for that very reason.

If structured data consists of uniform fields like names and email addresses, unstructured data is just about everything else. To provide some context, examples of unstructured data include emails, pdf attachments, photographs, audio or video files, text messages, word processor files, sensor data, and satellite imagery.

“The fact that unstructured data is not searchable makes it challenging for businesses to glean relevant insights once the data has scaled beyond what an employee can manually review.”

While those examples are all helpful elements for any business—including claims departments—the fact that unstructured data is not searchable makes it challenging for businesses to glean relevant insights once the data has scaled beyond what an employee can manually review.

How Claims Leaders Can Benefit from Structured Data

While some claims departments have yet to adopt the method of structuring data, especially in regard to litigation management, those that have are seeing their cases close faster and with better outcomes.

Claims leaders can comb through archived, structured data to make sound, informed decisions on case strategy. In doing so, claims departments can save money on legal fees since cases don’t unnecessarily drag on. The power of structured data would allow claims leaders to answer questions like these:

  • How accurate were counsel’s predictions of resolution amount?
  • What was the attorney’s success with dispositive motions?
  • How long did it take to get to settlement discussions?
  • How timely was the attorney in terms of executing key milestones in the litigation strategy?
  • How well did the attorney do against a specific plaintiff attorney? In a specific venue? With this type of case?

Another advantage of having access to litigated claim data is that claims departments can now build data-rich profiles on both defense and plaintiff attorneys that tell a meaningful story on performance. This ultimately assists in attorney selection and preparation.

Providing structured data to litigation professionals also fosters an environment of collaboration and communication between claims reps and attorneys. With all the data in one location and both sides working in the same platform, litigation management-related tasks are completed more efficiently.

Lastly, because it improves communication and provides claims leaders with historical relevance, utilizing structured data may even be able to help an insurer mitigate the risk of a nuclear verdict.

Additional Benefits of Collecting and Harnessing Structured Data

Structured data has made a big difference in organizations’ customer service, including insurance carriers. Lead generation strategies utilize CRMs with structured data to identify, track and nurture potential policyholders throughout the process. Descriptors like “prospect,” “qualified lead,” and “customer” help to delineate where a buyer is in their journey and drive the next steps in the process.

When it comes to customer retention, the benefits of using structured data are just as powerful. For example, let’s say your policyholder just purchased a new home. That customer then can be added to a campaign to receive recurring messaging about home maintenance based on the age of their home. Without a way to capture that data and report on it, there would be no way to tailor that outreach. Customers are happy because they receive communications that are relevant to them, and the insurer is happy because the customer remains engaged with the brand. The more an insurer knows about the customer, the better the message.

Outside of litigated claims, these are just a few examples of how structured data can help organizations reach their goals. The possibilities of harnessing captured data are extensive and fruitful.

Final Thoughts Litigated Claims and Structured Data vs. Unstructured Data

The best way to organize litigated claim data is to use a system that structures the data for you. Litigation management software is built to integrate with your current systems in place and provide highly customized reporting to help you make better, more informed decisions.

If your only metrics on litigated claims come from invoice data, you are missing a huge piece of the puzzle. The data critical to the litigation management process needs to be liberated from email attachments and other locations and made available to claims leadership to report and analyze.

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