Misleading Graphs!

A poor graphical design simply results in miscommunication. Data can be handled faster using high end programming tools but they don’t tell us how to communicate the graphs or summaries you generate to decision makers.

I recently came across this graph. It’s purpose is to show the change in prescription refills and revenue by consumer group.

At first glance, this looks meaningful and more importantly attractive. Let’s evaluate the graph to make sure that it conveys the correct message and does not mislead the viewers.

Per the refill per customer by Group graph above, customers in Group B refill the prescriptions several times more than the customers in Group A. For instance, the orange bar for year 2015 conveys the message that refills by Group B is 5 times more than Group A. Similarly, for year 2019, orange bar appears to be twice as big as the blue bar indicating that refills by Group B is extremely high. Is that true?

A few items to notice in this graph are -

• Chart type — Simplicity is the ultimate sophistication. The author has unnecessarily used a 3-D column chart simply to make it attractive, which does not add any value.
• Baseline in y-axis — The y-axis has a minimum bound of 4. This results in the orange bar appearing to be larger than it actually is. Let’s go back to the…