(Eugene Lee is senior director, new initiatives and the head of Guidewire Live at Guidewire Software.)
When is too much data a problem? Need a hint? Just ask today's property & casualty insurers, who are drowning in seas of structured and unstructured information from both internal and external sources—a/k/a "big data." It's the data deluge conundrum: big data can bring with it a treasure trove of information, but the valuable nuggets are often buried beneath gigabytes of irrelevance. Trying to sift through it all can feel like an exercise in futility. What's needed isn’t more data. What’s needed is better context.
Data Deluge Challenges
The current p&c insurance market is demanding and challenging, requiring agility, efficiency, and precision in assessing risk and adjusting claims, in order to achieve profitable growth and improve customer service. Data plays an important role in this environment but more data doesn’t necessarily equate to improved competitiveness. Instead of making it easier to compete, indiscriminate data can compound the market's challenging nature: While insurers have lots of data, very little of it is presented effectively to support more informed decisions because:
- Data is siloed and fragmented across disparate systems and departments.
- Information is not timely.
- Granularity is not fine enough.
- Internal projects to obtain and analyze the right information take too long.
- Third-party data services are difficult and costly to evaluate, integrate and use.
- Solutions are not integrated or built for the task at hand.
As a result, insurance professionals are forced to rely on only the data and tools they can readily access: data from internal sources, rules of thumb derived from past experiences, and a patchwork of external data from vendors, industry groups or even consumer websites.
If the insurer has a modern core system, they are much more likely to be capturing a higher quality and volume of data than those with older legacy systems. This data is much more easily accessed now as well—opening a door of possibility.
Progress is being made. Insurers now have more data than ever before, but that data is often scattered across multiple sites and systems. Historically, insurers have had few good options at their disposal to help tackle the data challenge.
The problem is that most big data solutions focus solely on manipulating and creating more data. At the end of the day, the best big data solutions are those that are transparent to the user. They’re the ones that quickly and effectively deliver the information being sought – they are the solutions that put data into context.
Let’s look at big data in more of a consumer manner. When you check your smartphone app to gauge the traffic delays in store for your evening commute you are in fact using a big data solution. That traffic app is tapping into the driving times of other smartphone users who have taken the route ahead of you. It aggregates that information and based on their experiences moments earlier, provides you with an indication of what’s in store for you—right now.
You, the consumer, don’t need or want to understand the tools the app provider is using to make this happen or the vast quantity of data that is crunched in split seconds to provide you with real-time estimates. No, you’re just thinking about how long it’s going to take to get home.
The app is delivering information, but it is delivering information in the context of your drive home and it is providing the information right now, when you need it. The app is making the volumes of data it captures, relevant to you and actionable by you in a visual and easy to use way. It’s solving a specific problem. It’s not more data, its better context.
This is exactly the same concept that when applied to insurance will help insurers scale their data mountains and get their hands on the right data to answer their questions and help them make better decisions. But how does the industry get from here to there?
What does better context look like? In an ideal solution, the right person would have instant access to all the relevant information they need based on who they are, what they're doing and when they need it. Context-driven insurance leverages a three-pronged approach: connect, curate for context, and appify.
First, all data must be structured and electronically linked so insurance professionals can connect to it across departments or even across organizations. Modern core systems are a key first step, but we need to look beyond. Use of a common core system data model by a group or community of peer insurers for instance, ensures that information is defined and treated consistently across organizations so that data sharing is possible. The sharing of structured, non-confidential data with one another magnifies the power of the data for everyone and provides the foundation for context.
Connecting alone is where data mining tools fall short. There is an infinite amount of data out there, and without a "card catalog," it's useless. The data therefore must be filtered, validated, prioritized and searchable—curated.
What information will be relevant for a particular business situation? Where is the best source of that data? How is the data incorporated into the systems I use every day to help me make the decisions that drive my business? These are the questions that need to be asked. Your technology solution partner should have good answers for all of them.
But even connecting and curating are not enough. As consumer technology has shown, users expect much more from technology. IT complexity must be hidden, and re-emerge as an app that presents the technology's capabilities simply and intuitively.
The app must deliver instantaneous results because we need the information right now. It must be intuitive and easily digestible so the user can be in the app getting their information quickly. It must be delivered in an anytime, anywhere, on-demand way so that it is ready when information is needed.
In order to get and stay competitive in the p&c insurance industry, insurers must embrace unique technologies that address one of their most critical challenges: taming the data deluge. By applying these context-driven principles, insurers can begin to use data to their advantage, rather than succumb to it.