Data’s usefulness to the insurance business is unquestioned. But it wasn’t until the 21st century that its full potential was discovered and realized. With the right tools, savvy insurers can use data and analytics to guide their strategies in order to amplify the customer experience and identify growth opportunities.
While data’s value is obvious to nearly all insurers, what’s less obvious is how to actually leverage the insights from their data. As Harvard economics professor Sendhil Mullainathan has said,
“The problem with data is that it says a lot, but it also says nothing. To understand why something is happening, we have to engage in both forensics and guesswork.”
The presence of a data set doesn’t instantly provide insurers with a course of action to take.
Data Barriers Insurers Must Overcome
Today’s sophisticated analytics can at times feel like a code that constantly needs to be cracked. To realize data’s true potential, insurers need to find ways to bypass those blockages. These are three common obstacles many insurers will encounter in their mission to pull actionable insights from data:
1. Lack of qualified analysts
Analytics isn’t a “set it and forget it” proposition. It requires skilled humans to contextualize information in order to properly apply it, which presents a problem because the talent needed for this sort of job is in short supply.
In fact, a recent Valen Analytics survey concluded that 75 percent of insurers struggle to attract the talent needed to manage predictive models.
The issue is that analytics and insurance experts don’t see where their specialties merge. Without qualified data analysts there to translate, it’s easy for insurers to become overwhelmed by a sea of data and incapable of comprehending it.
2. Trouble with legacy data
A swarm of incoming external data can be overwhelming enough, but an even bigger hurdle comes when insurers try to integrate legacy information. This data on past experience is an essential part of creating a predictive model, but when it comes from an array of sources, it tends to bring a variety of complications.
Some figures may be incomplete, while others may be redundant or actively contradict one another. For smaller insurance companies, sifting through this clutter of data and turning it into something useful can seem like an insurmountable task.
3. Making data actionable
Even the most sophisticated and accurate models can be difficult to translate into decision support in the real world. The connections between raw information and practical application are rarely obvious to the untrained eye. Data has the potential to be both a preemptive tool and a resource after the fact, so it’s important to know what you want from data and how to get it.
These are some of the more common challenges that prevent insurers from fully embracing analytics. But even in their absences, an effective implementation requires a measured approach and a clear strategy.
As the insurance industry matures, its data use must also mature in order to bring more value to the customer. However, antiquated systems supporting new technology leave these insurers floundering and wondering how to act next.
Valen Analytics can help insurers take the next step into this brave new world without crumbling under the weight. Download our latest whitepaper to learn how your company can best conquer these data challenges head-on and build a healthy and vibrant analytics ecosystem.