Insurance companies of all types and sizes generate data each minute, hour and day. Everyone—including executives, departmental decision makers, underwriters, claims adjusters and call center workers—hopes to learn things from collected data that can help them make better decisions, take smarter actions and operate more efficiently.

But the real challenge begins when companies begin extracting meaningful insights from this explosion of data. Determining how to take advantage of all this data to price better, expand markets and improve underwriting risk and handing claims. Fortunately, the science of extracting insight from data is constantly evolving. Regardless of how much data you have, one of the best ways to discern important relationships is through data visualization.

Data visualization, where information is presented in a pictorial or graphical format, is helping insurance professionals see things that were not obvious to them before. Insurance companies analyze historical data—which includes information from policy administration solutions, underwriting applications and billing systems—to forecast and predict future losses.

The digital age has brought with it a quantum increase in the amount of data available, but it is not just the quantity of data that sets this time in history apart. The speed with which data reach organizations, the variety of their form and the insights they contain are completely changing everything we have known about the collection, analysis and management of data.

A recent survey by Strategy Meets Action found that getting value from the growing diversity or variety of data was highlighted as the biggest challenge facing insurers. To gain insights from semi-structured and unstructured data requires new visualization techniques. A word cloud visual (where the size of the word represents its frequency within a body of text) can be used on unstructured data as a way to display high- or low-frequency words.

Velocity is all about the speed at which data is coming into the organization. The ability to access and process varying velocities of data quickly is critical. Using data visualization techniques, such as correlation matrices, combines big data and fast response times to quickly identify which variables are related.

For many, big data is all about the size or volume of information. When working with large amounts of data, being able to quickly and easily filter your data is important. But what if the filter isn't meaningful or it skews the data in undesirable ways? One way to better understand the composition of your data is through the use of histograms. Histograms provide a visual distribution of the data along with cues for how the data will change if you filter on a particular measure. Histograms save time by giving you an idea of the effect the filter will have on the data before you apply it. Rather than relying on trial and error or instinct, you can use the histogram to help you decide what to focus on.

Pie charts, scatter & bubble plots and decision tress are just a few other data visualization techniques. Hence another challenge when working with data is how to display results of the exploration and analysis in a way that is meaningful and not overwhelming. Auto-charting takes a look at the data you wish to examine and then, based on the amount of data and the type of data, it presents the most appropriate visualization. This intelligent auto-charting helps business analysts and nontechnical users easily visualize their data. They can build hierarchies on the fly, interactively explore data and display the data in different ways to answer specific questions or solve new problems without having to rely on constant assistance from IT to provide changing views of information.

Visualizing your data can be both fun and challenging. It is much easier to understand information in a visual compared to a large table with lots of rows and columns. To maximize the value from data visualization you need to consider the following basic concepts:

Understand the data you are trying to visualize.
Determine what you are trying to visualize and what kind of information you want to communicate.
Know your audience and understand how it processes visual information.
Use a visual that conveys the information in the best and simplest form for your audience.

Every organization is continuously looking for that "X factor", something that will differentiate them from their competitors. For insurance companies that "X factor" is often hidden in mountains of data. Insurers have long seen data as a source of competitive advantage. But data alone is worthless—it is insights derived from the data that matter and with the emergence of big data the possibility for deriving insights is increasing dramatically. Insurance companies taking advantage of data visualization will uncover the "X factor" much faster than their competitors.

Special Reports /

How to extract data to price better, expand markets and improve underwriting

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