Maybe it’s the recent birth of my
twin girls that’s got me thinking in 2’s. Whatever it is, I can’t seem to get
my head off the effectiveness of dual-axis charts.
For a long time, I used dual axes
and thought nothing of it. After all, they enable us to show 2 measures on the
same graph and we’re seemingly always looking for more real estate to work
with.
However, I’ve found that there are
fewer situations that truly benefit from leveraging this technique than I might
have originally believed. Now I’m not gonna go to an extreme here and say
“Never Use Dual Axes”, I’ll leave the absolutism to the hard asses in our
field.
While a case can be made for
(although I’m not completely sold) dual axes when you have want to compare 2
measures of different units (i.e. Sales $ and Units Sold), I would suggest that
we savoid using 2 scales for measures of the same unit (i.e. Sales $ and
Shipping Cost $).
I’ll use a simple plot chart to
illustrate the potential shortcoming here. Let’s say we want to show Sales $
and Shipping Cost $ for each of our Customer Segments. It might look something
like this:
The issue with the chart above is
the Sales $ are exponentially larger than the Shipping Costs $ leaving the
latter in a state where the differences can’t be visualized. A common tendency
here would be to create 2 axes, one for Sales and a 2nd for Shipping
Costs as shown below:
So we’ve resolved our problem of not
being able to see the pattern for Shipping Cost $. However, in doing so we’ve
created an illusion as our minds will instinctively attempt to compare the
magnitude of difference.
The best solution here might be to
use a separate chart for each measure…i.e. Small Multiples. Or, if your data is
granular enough, a scatter plot might be more revealing depending on the
question you seek to answer. Just a couple of alternatives, happy to hear yours
Cheers,
Kevin Taylor
