Infographic: Louisiana Flood Insurance Claim Statistics

Sep 30, 2011 by     No Comments    Posted under: Finance, Political
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This infographic comes to us from Bachus & Schanker personal injury law firm.

The crawfish dancing up the side of this IG are pretty visually enticing. I definitely craned my neck to one side to find out what it was representing, and was happy to see it’s a good example of data visualization. Four rows of smaller crawfish might’ve been better, but design-wise it could’ve definitely gotten cluttered. The Louisiana-shaped statistic about flood insurance is also an effective example of visualizing data, except that the National Flood Insurance Payments section is also state-shaped. For variety’s sake, maybe the 71% statistic should be in some other shape.

The blue color scheme makes plenty of sense for this infographic, and it looks pretty interesting in all of its varying shades. However, it makes the beige seashell section stand out in an awkward, off-balance way. This is the weakest section of the infographic because it is so text-heavy. Infographics are really about visuals, and the “Did You Know” and “If Flooding Occurs” sections have great potential. “12 inches of water floats many vehicles” could be interesting, as could “Flash floods often bring walls of water 10 to 20 feet high.” “Listen to the radio or television”: picture of a radio/television. “Stay away from downed power lines”: a little stick figure backing away from a downed power line? Infographics are intended to tell a story, and should still show all relevant data when text is removed. This IG stands that test pretty well until the seashell section. The data that is visualized there is almost too small to stand out; it looks a little squished.

On the grammar and spelling side of things, this infographic is pretty good. The crawfish sentence could use some punctuation, though, and Hurricane Ike is spelled Hurrican Ike. Still, it fares better in this department than others we’ve seen.

Overall, I’d give this infographic a C. More and different data visualization is needed, and a less severe division of data would help the overall appearance.



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