There are dozens of ways to refer back to a baseline to compare your data to. But, none are as efficient as using a benchmark to compare an average (or even a group of something), to measure against your own data. For example, if a man or woman were to mention that they were able to do 60 push-ups, you may realize that’s a lot, but you aren’t sure how this person may measure up to others. When adding the additional information that the global average is between 26-35, it drastically changes your perspective and makes you realize where that person fares up against most. This applies to any form of data visualization by adding depth to the topic you cover and also helping to give the reader a better understanding of the strength or severity of something.
Recently, Florida has been hit with an onslaught of catastrophic-level hurricanes, taking the lives of many and wrecking millions of dollars worth of damage. But, when measuring out the strength and magnitude of these hurricanes, how can we understand their true strength?
This visualization uses historical data and inserts previously recorded hurricanes as the benchmark to measure up against the new Category 5 hurricane, Hurricane Milton, that will soon make landfall in Florida. As shown in the visualization, and made abundantly apparent to the reader, Hurricane Milton is one of the strongest hurricanes to ever be recorded in modern times. We know this by using the line graph to measure up Hurricane Milton against all the other recorded hurricanes in history.
By using benchmarks, readers are able to quickly determine the scale of a given event and compare it against previously established benchmarks. In the example of Hurricane Milton, we are able to see the horrifying strength of the winds compared to hundreds of other hurricanes, and quickly understand just how severe the force of the hurricane will be in Florida.