Insurance companies of all types and sizes generate data eachminute, hour and day. Everyone—including executives, departmentaldecision makers, underwriters, claims adjusters and call centerworkers—hopes to learn things from collected data that can helpthem make better decisions, take smarter actions and operate moreefficiently.

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

Data visualization, where information is presented in apictorial or graphical format, is helping insurance professionalssee things that were not obvious to them before. Insurancecompanies analyze historical data—which includes information frompolicy administration solutions, underwriting applications andbilling systems—to forecast and predict future losses.

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

A recent survey by Strategy Meets Action foundthat getting value from the growing diversity or variety of datawas highlighted as the biggest challenge facing insurers. To gaininsights from semi-structured and unstructured data requires newvisualization techniques. A word cloud visual (where the size ofthe word represents its frequency within a body of text) can beused on unstructured data as a way to display high- orlow-frequency words.

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

For many, big data is all about the size or volume ofinformation. When working with large amounts of data, being able toquickly and easily filter your data is important. But what if thefilter isn't meaningful or it skews the data in undesirable ways?One way to better understand the composition of your data isthrough the use of histograms. Histograms provide a visualdistribution of the data along with cues for how the data willchange if you filter on a particular measure. Histograms save timeby giving you an idea of the effect the filter will have on thedata before you apply it. Rather than relying on trial and error orinstinct, you can use the histogram to help you decide what tofocus on.

Pie charts, scatter & bubble plots and decision tress arejust a few other data visualization techniques. Hence anotherchallenge when working with data is how to display results of theexploration and analysis in a way that is meaningful and notoverwhelming. Auto-charting takes a look at the data you wish toexamine and then, based on the amount of data and the type of data,it presents the most appropriate visualization. This intelligentauto-charting helps business analysts and nontechnical users easilyvisualize their data. They can build hierarchies on the fly,interactively explore data and display the data in different waysto answer specific questions or solve new problems without havingto rely on constant assistance from IT to provide changing views ofinformation.

Visualizing your data can be both fun and challenging. It ismuch easier to understand information in a visual compared to alarge table with lots of rows and columns. To maximize the valuefrom data visualization you need to consider the following basicconcepts:

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

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