Training Industry Magazine - July/August 2020 - 53

STELLA LEE, PH.D.

WHAT'S NEXT
IN TECH

BUILDING DATA FLUENCY
IN L&D: A QUICK GUIDE

Increasingly, organizations are using
artificial intelligence (AI) and machine
learning-enabled business platforms
to streamline processes, reduce costs,
train staff and optimize resources.
These platforms generate a tremendous
amount of data, much of which is
unused or unanalyzed. For learning and
development (L&D) practitioners, there
lies a great opportunity to make use of
data to demonstrate how L&D directly
impacts and supports business, as well
as how learning is crucial to establishing
alignment with business goals. We can
only do that if we have the ability to turn
raw data into insights, and we need to
build data fluency within our L&D teams
to do so.
Data fluency extends beyond data
literacy. To have data fluency means that
we know where the data comes from, and
as a result, we can process, interpret, infer
and apply data effectively. Application
sets data fluency apart from literacy,
empowering you to take informed action.
To build data fluency, start with the
following practices:
START WITH "WHY"
Before we lose sight of the forest for the
trees, we must understand why we want
to make use of data in learning. Define the
challenge or problem you set out to solve
within your organization. For example,
learning practitioners are commonly
questioned about the effectiveness of
their training efforts. You need to define
"effective" for your learning programs
and determine how to measure that

effectiveness. Only then do you know
what data to look for.
KNOW YOUR DATA
With various online platforms deployed
across organizations, you need to identify
where the sources of data are. Don't
just collect the obvious - like data from
your learning management systems
(LMSs). E-libraries, web conferencing
systems, learning experience platforms
(LXPs), online survey tools, internal social
networks, intranets and knowledge
sharing repositories are valuable sources
of data; make sure you have access to
these systems. Then, you need to get
comfortable asking questions about the
data you collect. The most important
questions to ask: Did you find the right
data? In other words, are you able to
measure what you want to measure? Or
are you comparing apples to oranges?

DATA FLUENCY
EXTENDS BEYOND
DATA LITERACY.
ANALYZE THE DATA
While big data seems to be all the rage,
small data is what we typically handle in
L&D. Small data provides information
that can be easily analyzed with your
every-day spreadsheet programs, such
as Excel. Don't get caught up in complex
data analytics software. Many modern
data analytics tools are designed with a
non-technical audience in mind, provide
templates to get you started, and allow
you to quickly compare and visualize data.

If you find the task of analyzing data too
daunting, consider partnering up with your
organization's business intelligence unit or
information technology department who
are familiar with manipulating databases.
FROM INSIGHTS TO ACTION
Finally, you need to put your insights from
data into action. Based on the problem
you defined, your data should help you
make decisions, implement improvements
and solve issues. For example, if you want
to know how effective your cybersecurity
training program is, you need data
that indicates efficacy based on your
definition. Is there an increase in the
number of people changing to stronger
passwords post-training? Can you identify
what caused this increase and whether it
is related to training? Are you able to take
action based on what you know to more
effectively design the material?
Data fluency is more than technical skills.
You need to develop an interdisciplinary
mindset, and be able to look at data
from a wide range of angles including
business, communications, statistics
and psychology. It also requires us to be
curious, continue to ask questions and
collaborate with others to implement
what you learn.
Dr. Stella Lee has over 20 years of
experience in consulting, planning,
designing, implementing, and measuring
learning initiatives. Today, her focus is on
large-scale learning projects including
LMS evaluation and implementation,
learning analytics, and artificial intelligent
applications in learning. Email Stella.

T R A I N I N G I N DUSTR Y MAGAZ INE -DATA FLUENCY IN LEARNI NG 2 02 0 I WWW. T RAI NINGINDU S T RY . C OM/ MAGAZ I NE

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Training Industry Magazine - July/August 2020

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