From the vast quantities of actuarial data to the minute details of client data, there's no escaping the truth that we're surrounded by data and only creating more of it every day.
Data is everywhere. And even more so in the insurance industry. From the vast quantities of actuarial data a carrier houses to the minute details of client data an independent insurance agent collects, there's no escaping the truth that we're surrounded by data and only creating more of it every second of every day.
But often, especially in the insurance industry, it can feel like, “Water, water, everywhere. But not a drop to drink." Data, data, everywhere. But none of it is accessible or usable. The problem isn't that we're lacking data. It's more to do with how data is collected that determines whether or not it's usable. This brings us to the important distinction between structured and unstructured data.
What Is Unstructured Data?
Before we can talk about structured data, let's talk about its predecessor: unstructured data. Unstructured data can encompass anything from paper forms to disorganized and siloed digital formats. Just like it sounds, unstructured data is data that is collected and housed in an unorganized, unstandardized way.
Examples of unstructured data include emails, spreadsheets, images, video files, audio files, and, of course, paper files. When information is collected and stored in an unstructured way, it blocks the ability to view the data as a whole, analyze it, identify trends, and many other uses that we actually want from our data.
Unstructured data tends to be more siloed, it's less efficient to sort through and requires more manual labor. Insurance industry employees would rather not spend their time tediously digging through different spreadsheets, files, and folders to then cross-reference information between multiple sources. But the truth is that many still do!
What Is Structured Data?
Structured data doesn't consist of inherently different pieces of information compared to unstructured data: It's just that it has been collected, organized and stored in a way that enables both people and technology to access it and leverage it more easily.
As long as they are housed within a shared database, structured data can include formulaic data points that are easily labeled, like customer names, addresses, important dates, car makes and models, and insurance claims history.
When an insurance agency uses an agency management system (AMS) or customer relationship management system (CRM), the system forces data to be entered in a way that adheres to a set structure. Once collected, the software can filter, sort, report and analyze the data in a way it never could if—for example—each employee kept a Word document with the same information on their own computer.
A huge benefit of structured data is the ability to proactively manage your business. With the transparency and visibility structured data provides, business leaders can access trends, leverage predictive models, and make data-informed decisions because they have a clear view of what's happening across each part of the business.
On top of just being more accessible to employees and more easily analyzed by technology, structured data formats are more secure. This is because, rather than data being all over the place—your desktop, a shared network drive, a USB thumb drive, a sticky note in your pocket, so on—all data is kept within a secure platform that has safeguards in place to prevent unauthorized access. Insurance industry software is increasingly moving toward zero-trust security protocols, which limits access to authorized users and never assumes a user is authorized just because they logged in previously.
Is There a Downside to Structured Data?
With any technology shift, there are always concerns regarding implementation, hassle, data security, costs and ongoing maintenance. Structured data kept in a secure location, whether cloud-based or on-premises storage, is typically not as much of a security concern as unstructured data, although it can become one if files are shared outside the secure environment. Once data leaves a closed, secure system, your organization loses control of how it may be used and who may access it.
Also, structured data is more rigid. One con of structured data is that it is structured. The same parameters that make the data easily searchable and analyzable can limit the creative use-cases for the data outside of its original purpose. Luckily, this is becoming less of a roadblock as new technology like application programming interfaces (APIs) help connect one set of structured data with another.
Another side effect of structured data is that the agency owners must adhere to storage requirements. Most structured data is stored in data warehouses, which may come with their own requirements about exactly how the data needs to be formatted. If the warehouse changes anything about its setup, this can mean customers of the warehouse must spend time and money adjusting large quantities of data to meet the new criteria.
Grow your Distribution Channel
Despite any downsides, the truth is, the insurance industry will largely benefit from moving away from its historic unstructured methods and toward systems of structured data in the future. One particular use case for structured data within the insurance industry is the ability to use data to power growth.
In the world of unstructured data, any insurance business looking for insights that will help grow its distribution channel has to obtain multiple, overlapping, messy data sources, which likely have incomplete or inaccurate data. They then must cross-reference all sources to check for inaccuracies and redundancies. They have to manually analyze data, or at the very least, spend time entering data from different sources into one central system to try to find insights.
Structured insurance industry data, on the other hand, allows the user to instantly access and sort industry-wide data from multiple, reliable sources.
Ellen Lichtenstein is senior content specialist at AgentSync.