Sex sells. And, although it may seem absurdly out of context, it
definitely sells Business Intelligence (BI) software.

Though somewhat ironic, many BI purchase decisions are made on
abstract (or outright flimsy), rather than tangible benefits-based
grounds. – A stunning interface, fancy shapes or colors, can push one
Philly over the line in a close two-horse race.

Yellowfin’s position on data visualization and infographics

At Yellowfin, we’re about to release the latest version of our BI
solution – Yellowfin 5.2. Amongst other enhancements and additions,
the update will include a number of new charting options. And whilst
their aesthetic appeal is undeniable, we think it’s important to
understand their purpose and place.

Confabulation in Business Intelligence and data visualization

Jim Harris, in a recent Information Management blog post – Data
Confabulation in Business Intelligence – stated that in an environment
of forever avalanching data assets, he feared a new trend. His fear
was that: “data-driven decision-making may simply become intuition-
driven decisions validated after the fact by selectively choosing the
data that supports the decision already made. The human mind is
already exceptionally good at doing this – the term for it in
psychology is confabulation.”

He explained that: “Data confabulation in Business Intelligence occurs
when intuition-driven business decisions are claimed to be data-driven
and justified after the fact using the results of selective post-
decision data analysis.”

I concur with Harris, and hold a similar fear for data visualization –
that this component of BI is also being applied improperly. My fear is
two-fold:

•Amidst a growing, cluttered, swirling sea of BI products,
organizations looking to select a BI solution will move through a
mountainous number of POCs (Proof of Concept) and emerge utterly
confused by a combination of expansive choice, and myriad of sweet-
smelling vendor promises. Spoilt (and understandably perplexed) for
choice – a choice that business users now have a larger say in (as
they should) – many organizations’ ultimate purchase decision will be
based on which vendor generates the prettiest 3D pie chart, rather
than which BI solution (and visualizations) can provide the best-fit
(clearest insight).

•Decision-making will suffer. Decision-makers, report users and
writers alike, will be caught up in the euphoria of spiffy-looking
infographics that carry meagre meaning, but project the impression of
authority and decisiveness. This infatuation with the superficial will
lead to the utilization of inappropriate, less incisive data
visualizations, misunderstandings/misinterpretation (or at the very
least, lesser understandings) of the underlying data, and poorer
decisions.

A lively blog post – Business intelligence vs. infotainment – on data
visualization and infographics forum, FlowingData, speaks of this
trend. The post posits that, at its core, despite the “bright and
shiny tools”, “Business Intelligence, which is really just statistics
for business, is analysis. It’s not entertainment.”

Many organizations seem to confuse the two terms and their respective
purposes.

These thoughts are echoed by BI expert, Stephen Few, who in his latest
blog post – Teradata, David McCandless, and yet another detour for
analytics – critiques the work of infographic designer, David
McCandless.

Few exhibits the same frustration regarding the fundamental purpose of
data visualization, stating that: “McCandless rarely chooses forms of
display that our eyes and brains can perceive with ease and precision.
He selects what will appeal superficially to the viewer (lots of
circles, swirls, and vibrant colors), not what will most effectively
express what’s essential and meaningful.”

Few continues, saying that “too many of his [McCandless’]
visualizations display information in ways that hide much that’s
relevant and essential, leaving little of value for the viewer to
see.”

The problem with data visualization: We’ve been here before

It seems that, despite the talk, the world of data visualization has
been failing to walk-the-walk for some time, according to the 2002
publication, Information Visualization in Data Mining and Knowledge
Discovery.

In a forward from the series editor, Jim Gray, the research novel
laments that: “Data visualization has lagged its sister disciplines of
data capture, data storage, data analysis, and knowledge discovery…
there is still a huge gap between our ability to extract answers and
out ability to present the information in meaningful ways.” Although
the book was published in 2002, with a suggestion that the problem was
on the cusp of being resolved, essentially, the sentiment remains
true.

The book defines the principle function of data visualization in
stark, uncompromising terms:

“Visualization, well done, harnesses the perceptual capabilities of
humans to provide visual insight into data… (it is) fundamentally
about data reduction… Finding a view or projection of the data that
reduces complexity while capturing important information.

“A successful visualization is one that emphasizes the information of
interest and presents it as a resolution sufficient to perform the
task.”

Did the last visual re-presentation of your corporate data match this
lofty, rigid definition?

Conclusion: Don’t let data visualization take your eyes off the prize

So sex does sell BI. And that’s fine – it should be fun and engaging.
Just make sure that your corporate data remains the star of the show
and point of focus, rather than the data visualizations themselves.

But is it poor data visualization, or its poor application, that is
hampering this much-maligned element of business analytics?

Whatever the case, just remember this: If it takes five people and an
hour-long meeting to explain what that chart means, and its
implications and impact on your organization’s financial outlook, then
it’s time to send it back to the nunnery. - Overtly eye-catching
visualizations have their place, but they’re not always the best
answer. Sometimes a humble line or bar chart conveys meaning most
clearly.