For beginning and advanced report developers alike, the
biggest challenge I have witnessed is the challenge of Report
Conceptualization. This is the process of translating often incomplete business
requirements into a structured plan that will produce the result that the
business needs. For operational reports based on known data structures and
calculations this process can be simple, often operational reports are
structured very simply and the job of the report developer is to simply put the
right fields in the right place. The process becomes much more difficult for
strategic reports which attempt to help the business define what they should be doing. Strategic reports are
often poorly understood by the business, their needs are uncertain and
difficult to communicate, and vision for the end product is amorphous. Taking
vague, conceptual requirements into a concrete view of business data is a
challenge for developers and analysts alike.
The first step is understanding which are the best
visualization options to meet the business requirements. Often a table of
numbers is what a business unit understands and asks for because they are used
to dealing with operational reports where they need numbers. But sometimes a
well-designed visualization of the data makes it easier to understand and gives
the business the interpretation that they need in order to make a decision
without having to spend time crunching numbers.
Visualization of a data set needs to be chosen carefully to
properly communicate the information that needs to be understood. A poorly
chosen visualization, especially if it is poorly documented, can provide
confusing, useless, and sometimes misleading information.
A couple of my favourite visualizations that do an excellent
job of communicating information are:
1) Florence
Nightingale’s Diagram of the causes of mortality in the army in the East
The purpose of Nightingale’s chart
was to illustrate that the primary causes of death amongst soldiers in the
Crimean war were due to preventable diseases. The polar area diagram does a
fantastic job of showing this, and by how much. As an aside, Nightingale could
have exaggerated her diagram by choosing to use a polar radius diagram where the radial measurement is linear with the
value instead of the area of the wedge. Since the eye naturally compares areas
it would imply that the scale of deaths due to preventable causes was that much
larger, but to her credit Nightingale strove for precise accuracy in her
representations.
2) Charles
Minard’s Flow map of Napoleon’s March
Minard’s graph combines a variety
of pieces of information in a novel way, representing the course of Napolean’s
march geographically, as well as including the number of soldiers on both the
initial march and the retreat from Moscow and the successive losses incurred,
but also the temperature on the return march showing the impact of the weather
on casualties.
That being said, visualization is something that needs to be
developed with cooperation from the business people who are going to be using
it. Even if a 100% Stacked Bar Chart is a perfect representation of the
information that needs to be communicated, it is worthless if the business
users do not understand what it represents and how to use it, or are trying to
interpret more information from the visualization than exists because of their
preconceptions about what a bar chart is.
One example is the use of two types of bar charts: Stacked
Bar Chart, and 100 Percent Stacked Bar Chart. The Stacked Bar Chart can often
be confused with an Area Chart as the stacked bars are misinterpreted as
“overlapping” by assuming the view is a projection of the normal Standard Bar
Chart from the end. Likewise the 100 Percent Stacked Bar Chart is confused with
the Stacked Bar Chart assuming that the height is representative of magnitude
not share, this confusion arises because the business user does not see the 100
Percent Stacked Bar Chart as analogous to a series of Pie Charts.
Remember when designing charts for business use that
creative interpretation can hinder clarity. A grid of Pie charts may feel
clumsy, but may do a better job of communicating effectively with your business
user.
Deciding
How do you decide when to use what kind of chart?
The first step in choosing an appropriate visualization is
to understand what you are trying to communicate. The purpose of a chart is to
convey information about some kind of relationship between pieces of data.
There is always at least two pieces of information in a chart (otherwise it is
a very boring chart) and the type of relationship between those pieces of
information helps determine the most effective way to display it.
What kind of relationship do you want to illustrate?
- Do you want to draw a
comparative relationship?
Ex. How do the values of A compare to B, compare to C, over time?
- Do you want to illustrate
the existence of a relationship?
Ex. As the values of A increase, what happens to B or C?
- Do you want to understand
a composition, how pieces make up a whole?
Ex. How are the values of A broken down into groups B and C?
- Do you want to show how
values in a relationship are distributed?
Ex. How often does A occur by value?
One of the better examples I have seen on how to start
understanding this process is by Extreme Presentation Method and their Chart
Chooser (http://www.extremepresentation.com/design/charts/).
This chooser presents a nice compact decision tree to understand how certain
charts are best used to explain specific relationships. It is neither perfect,
nor complete, but it is an excellent starting point.
Another
good resource is the Periodic Table of Visualization Methods by Visual Literacy
(http://www.visual-literacy.org/periodic_table/periodic_table.html#).
This resource gives a wide spectrum of visualization options and groups them by
What is being visualized (Data, Information, Concept, Strategy, Metaphor,
Compound), whether the visualization is Process or Structure, whether the
visualization is on the Overview or Detail level or both, and whether a visualization
is geared towards Convergent or Divergent thinking. It does not do a good job
of explaining when or how to use any particular visualization, but it is a nice
complement to the Extreme Presentation decision tree by providing a bit of
context around the purpose of certain visualizations.
