The Journey to Data Fluency - Data Fluency: Empowering Your Organization with Effective Data Communication - page 187

information technology investments a decade ago can be done quickly and
economically today. The challenges are in the skills and collaboration of the
people that use those technologies. Poor communication, misalignment of
values, limited data communication skills, unfocused messages . . . these are
the challenges that most organizations we work with face today. The good
news is that these are all solvable by focusing on the skills of your people.
This topic is about creating organizations that value and use data, and the
individuals that can make this happen. The topic started with a focus on
individual skills by explaining the specific knowledge that can make people
effective at working with data. We drew a distinction between authors of
data products and consumers of data products. (Although, many readers may
find themselves in both camps.) From this granular view, you looked at how
organizations can encourage data fluency. An environment was described in
which the data fluent individuals can flourish and high-quality data products
reach their intended audiences.
The Data Fluency Framework comes in four parts, subdivided by the producer-
consumer and individual-organization dichotomies. Each quadrant can be
understood as a necessary and interdependent building block to a fully data
fluent organization.
DATA CONSUMERS: CREATING A
SOPHISTICATED AUDIENCE
Soon the digital divide will not be between the haves and the have-nots.
It will be between the know-hows and the non-know-hows.
—Howard Rheingold
The same could be said of data fluency. Rather than the haves and have-nots,
there are those who engage with data and those who choose to avoid it. It
is a path chosen based on comfort level, education, and experience. As data
becomes more common as part of everyday communication—in the media,
in entertainment, and in the workplace—this data-divide becomes a more
substantial problem.
Chapter 4, “A Consumer's Guide to Understanding Data,” described the skills
and mindset required to become a sophisticated data consumer. It covered