Contents Coverage: The Flaw of Averages

When you think about how often we use averages in important business decisions in our industry it’s a bit scary. Imagine building a home in Florida, assuming it needs to withstand only average weather conditions? Accounting for variability is usually critical to accurate decision making, but, it requires more data and more work to extrapolate the key insights. That’s what “big data” is all about.

My colleague Frank Cregg and I recently wrote an article on this very topic published in Carrier Management. We used data and analytics to debunk a pretty crazy rule of thumb a top insurance carrier is using on the recommendation of their top claims technology vendor. Their rule says that the Top 250 most expensive items in a home represent 80% of the value. Unfortunately, they use this approach to settle contents loss claims to the detriment of their business as well as to the well-being of their policyholders. In our analysis, we show the obvious flaws of depending on statistical averages and how this translates to over- and underpayment of claims.

Luckily, we have a growing box of tools to handle this so that old-fashioned rules of thumb can be tested and discarded when proved inaccurate. For Enservio, we see our customers increasingly coming to us for help with understanding their operating data and how our analytics products can transform their businesses with more informed decision-making. What do you think? Do you have the visibility you need to make predictive decisions about a key segment of your customer base?