Bar charts have been around for many years.
William Playfair who was a Scottish political
economist is considered by many sources to
have created the first bar chart.
In the last book he published, he also included
a column chart that looks like this.
Since then, the visualization of these charts
have been improved on by the likes of Edward
Tufte, who's known for his concepts of maximizing
the data to ink ratio and phrases like chart
junk and let the data speak.
You can read all about this in his book, the
visual display of quantitative information.
In this video I'm going to dig deeper into
column chart design and I'm going to share
with you five tips when it comes to creating
the optimal column chart for any of your reports.
Now what I'm going to be showing you here
is based on a study conducted at the university
where I'm teaching.
Link to the full report is below.
The point of this study is to test if certain
design decisions that you make can influence
the effectiveness of your graphs and here's
the best part.
They do this by applying eye tracking to make
an accurate assessment of what the observer
is looking at.
Here's what it looks like.
The tests are done in special settings.
The way it works is you're presented with
a question and you need to answer that question
by looking at the visualization on the screen
while the camera is tracking your eye movements.
Two parameters are measured.
One is effectiveness, which means did you
get the answer right and the second one is
efficiency, which means how fast were you
able to respond?
Eye-tracking is supposed to provide more insight
into visual behavior.
This is done with the use of scan paths, so
how you're moving your eyes, your attention,
on the screen and fixations what you're concentrating
on.
Here's an example of an actual to budget comparison.
Participants were shown this chart and they
were asked: what was the variance between
actual and budget for the business segment
retail?
This is an example of the resulting scan path.
It shows a complex search pattern and lots
of eye movements back and forth.
Another group was shown an improved chart
and was asked the same question, what was
the variance between actual and budget for
the business segment retail?
And here's an example of the resulting scan
path.
The eye has much less work to do, which not
only is more efficient, which means people
were faster responding, but it also improved
the overall effectiveness, which means more
people got the right answer.
Now let's get into the five tips.
Number one, don't use 3D.
This is probably a no brainer, but I found
the results interesting.
There were 84 participants divided into groups.
They were asked two questions, does the actual
sales volume exceed the budget in June, and
how high is the actual sales volume in June?
Here's the 3D version they were shown.
For 2D, they were shown different versions
like these.
For the first question, the study found, the
3 D graph had an 11% error rate while the
2D versions had zero.
For the second question where they had to
guess the exact number, with the 3D version
people estimated either way too high or way
too low, and if you're still not convinced,
I give you another reason to skip 3D graphs
and that's the response times were 47% longer
for 3d than 2d.
Number two.
Show the values directly above the columns.
The study found that when they showed a graph,
with only labeled values, the results were
better than using only a label axis.
People were faster responding to questions
like how high is the actual sales volume in
June?
Number three, align label values vertically.
If you don't have enough space with large
numbers, we sometimes have the tendency to
make them smaller to fit.
Instead of putting them horizontally and making
them super small, we can put them vertically.
Number four, don't break the axis.
This can result in lower effectiveness, which
means people misunderstand the message of
the graph.
Take a look at this and now this, do you spot
the difference?
Number five, this wasn't directly covered
in this study, but it's super important.
Don't just give your charts a title, but make
them big and meaningful.
This is the first place people look at before
they move their attention to your chart.
They need to know what they're looking for.
I hope you find these tips helpful.
Let me know in the comments below which ones
you're currently using in your reports.
If you liked this video, give it a like to
support my channel, and if you like to receive
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Thank you for watching.
See you in the next video.
[inaudible].
