The Data and Measurement Issue - 6

4
Build a data-literate workforce
For employees to fulfill the expectations of their role in data, they need data
literacy to " speak the language " of data. This includes understanding and
communicating basic data concepts, such as correlation vs. causation,
probabilities, levels of confidence, or sources of error and uncertainty. It also
involves thinking critically about data, including how it's collected, represented,
visualized, interpreted, and used. (For insights into how data can be visualized,
go to page 28.)
Organizations can build a data-literate workforce through a combination of
hiring data-literate employees and upskilling existing employees through
data literacy development programs and experiences. (For an example of
upskilling employees through the work, go to page 8.)
5
Establish guiding principles
Leaders play an important role in setting the tone for data-driven
practices. One way they can shape mindsets and behaviors is through
establishing a set of guiding principles related to data and data usage.
Consider these examples:
* Recognize that data won't provide a definitive answer. Data will open
the door for additional (and hopefully more informed) inquiry. Treat the
data as such.
* Keep humans at the center. In every decision around data, be intentional
in considering the human element. How will the data impact employees,
consumers, or other stakeholders? Who will use the data and for what
purpose? How do consumers of the data need to receive the data (and in
what form) so that it's most useful to their goal? What are some potential
unintended consequences of collecting or attending to certain data?
(For more insights on meaningful measurement for stakeholders, go to
page 16.)
* Embrace that data isn't limited to numbers. Observations and qualitative
information are data too and should be considered along with quantitative
data as part of a richer and more holistic interpretation when
seeking insights. (To learn more about the power of qualitative data,
go to page 26.)
The Data and Measurement Issue

Table of Contents for the Digital Edition of The Data and Measurement Issue
