Part 1: Ice Blocks and Hot Coals
Let’s talk about averages. We are often asked “What are the average costs per square foot in [fill in the blank]?”
Our answer is to use this illustration of average: If you stand with one foot on an ice block and one foot on a bed of hot coals, your average temperature may be normal. Your feet probably hurt, but the rest of you is just fine! Of course, the painful feet will get your attention. Frankly, it is doubtful you care about the rest of you at that moment when your feet are blistering from heat or freezing from cold.
The real point is that the average does not describe either foot correctly. When it comes to houses, each one needs to be treated like an individual with the replacement cost based on the description of the actual home.
Now let’s look at the average housing market. Based on the cold and hot foot example, should we care about averages? We think the answer is “No.” Developing an average cost per square foot in an area doesn’t accurately describe individual homes and it cannot accurately be used for homes that may be in different strata.
If there is a high-value home builder, that builder’s averages are very different than homes built by production builders, for example. The homes can be two miles from one another with the same description of a 2,500 square foot, one-story home with stucco walls and architectural shingles, yet wildly different in value.
If one is $1,000,000 and one $350,000, they have a Mean (average) value of $675,000. The average value is wrong for both houses. Why not add 1,000 more examples and the average will move to the right number, right? Nope. It won’t and it can’t. If production builders create homes that cost 5% more, does that help? It doesn’t unless the production builder starts building homes one at a time. You need data from builders that can build one house or one retail shopping center at a time to get an insurance level replacement cost value.
Mode = Most Frequent Number
Median = The Value In The Middle Of A Data Set
In reality, structure costs are not a typical bell curve. With anything, and especially structures, there are more low-cost items than high-cost items. Especially in home rebuilding costs, the bell curve is skewed left. The mean and median lean to the larger sets of structures. Those just happen to be lower cost structures. The problem arises on the right and left side of the bell curve. The “tails,” if you will.
The tails of the structure bell curve can wreck a company. It only takes a few of the homes on the right side of the bell curve to wipe out a company with a left-skewed bell curve.
Further, on the left side are small houses, manufactured mobile homes—those structures that are relatively simple to build or rebuild. Those low-cost items can really drag the Mode, Median, and Mean away from that right side of the tail. That not only increases the impact of the few ticks on the right, but it pulls the “average” below average.
All of the sudden the book of 2,500 sq. ft. homes is a touch light.
Analyze your portfolio. Find the bell curve in your book of business. Do a portfolio valuation. From there resources will dictate how to fix that portfolio. Resources, time, and market constraints will help you decide if you look at the “worst” 10%, 25%, etc.? The key is to do something. It is not done in a vacuum and one way that is not recommended, is to non-renew the locations with the largest delta from current state to actual state.
Beware the cost averages!
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