Business Intelligence: 7 Tips for Effective Data Visualisation

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Business Intelligence 7 Tips for Effective Data
Visualisation
Inside Info
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Sophisticated data models wont do us much good
unless decision-makers are able to interpret,
understand and act on the results appropriately.
Here are seven principles for designing
analytic apps that lead to high user acceptance
and results, from our team of consultants. 
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Understand What Users Will Do with the
Results Analytic interfaces should be driven by
an understanding of what users will do with the
results. Frame the discussion on uses around
role-based design, with sensory cues directing
action on only the most critical pieces of
information.  Role-based design of interfaces is
important to match analytic needs to support the
different type of decisions people may need to
make throughout the organisaton. While scores of
workers from management to the contact centre
might benefit from access to analytics, different
interfaces may be required to serve different job
roles.  Remember less is always more. Good
business analytics interfaces show the
information most critical to the user not every
piece of information that might be available for
analysis. Sensory cues direct attention.  Good
interfaces exploit peoples abilities to perceive
patterns based on position, size, shape, color
and movement. These properties highlight
important features that might otherwise be lost
in a table of numbers.
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Let Users Lead Start from user needs and work
backward to design the interface that supports
those needs, ultimately to the analytics that
will drive that interface. Even when users cant
specify in advance what they really want, its
critical to involve them early and often as
analytic interfaces are designed. Sometimes users
may not be able to define it, but theyll know it
when they see it. Users are even better gauges
for bad interfaces if enough users believe an
interface is unsatisfactory, youre well-advised
to accept their judgment. If you are
contemplating giving users the ability to set
analytics modeling parameters, determine if they
want to set those parameters and that they know
how to do so or at least give them default
values. Users can help identify early wins the
designer may not have thought of and might
provide useful introductions to other potential
users and their communities. A user who feels a
sense of ownership in interface design can become
an advocate for the technology respected by other
users. Users of different abilities may point out
accessibility considerations, such as how and
when color is used so colour-blind users get the
same information from the intensity of the
display.
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A Picture is Worth a Thousand Numbers Because of
our human ability to understand relationships
quickly based on size, position and other spatial
attributes, the eye can summarise what might
otherwise require thousands of numbers to
convey. From Analytics to Action An analytics
interface may be visually appealing, but if it
doesnt stimulate action, its not going to be
very effective. Good interfaces provide the
context to let the user know when action might be
required. Host Analytic dashboards alert users to
potential performance issues and provide
actionable information. Good interfaces provide
context to interpret results that suggest what
the user might do next and provide mechanisms
such as clickthrough to facilitate an explanation
and further analysis.
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Apply Design Principles Apply principles for
good visual design. Displays of related
information are horizontally and vertically
aligned so the eye can see patterns across
related variables (they do not have unintended
alignments that suggest misleading or irrelevant
comparisons). Colour serves to highlight
exceptions, not to brighten up a dull dashboard.
Analytic results are not presented to 10 decimal
places when the user does not need such precision
to make a decision. Good interfaces avoid 3-D
effects or ornate gauge designs when simple
numbers, charts and graphs will do.
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Thank You
Inside Info
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