The Data Product Ecosystem - Data Fluency: Empowering Your Organization with Effective Data Communication - page 170

DESIGN
Less than 30 percent of the potential users of organizations' standard
business intelligence (BI) tools use the technology today. This low
take-up is due to the fact that longstanding tools and approaches to
BI are often too difficult to use, slow to respond or deliver content of
limited relevance.
—Gartner 5
The three reasons cited by Gartner for this problem are:
1. Ease of use (“is hard to work with”)
2. Performance (“users are frustrated by delays”)
3. Relevance (“does not express content in line with their frame of reference”)
The first and last reasons link directly to issues of poor data product design.
In our role as dashboard and analytical application designers, this is an area
that is close to home. We see it all the time: reports and dashboards that lack
focus and a message that targets their audience, which is often undefined.
We see poor choices in data visualization that distract from the important
elements in the data and put the burden of deciphering meaning on the
readers. We see data products that lack an obvious starting point and logical
flow to conclusions.
Poor design is wasteful. It results in solutions that users don't want to use,
as noted by Gartner. It wastes the audience's valuable time as it struggles to
comprehend the data. And it wastes the development and distribution efforts
necessary to deliver the data product.
Overcoming these design shortcomings requires systematic processes and
capabilities within your organization. Chapter 5, “Data Authors,” discusses
the skills involved with designing effective data products. But how do you
incorporate these skills into your processes and create repeatable ways to
ensure quality design?
OBJECTIVE
Better information design in your organization will come from a combination
of skilled people and processes that ensure design is a priority.