Training Industry Magazine - July/August 2019 - 44

Innovation over the past eight years in
technologies like natural language
processing, vocal recognition and
facial analysis means that machines can
assess, as accurately as a human coach,
a professionals' predicted impact on their
audience, their team and/or their clients,
and then respond with specific feedback,
insights and actionable recommendations
for improvement tailored to each user's
unique strengths and development
areas. This is one example of innovation
driving the capability for improved
communication skills.

AUTOMATING THE
LEARNING PROCESS
THROUGH DATASCIENCE AND AIDRIVEN PROGRAMS
LEADS TO A MORE
PERSONALIZED
LEARNING
EXPERIENCE.

Imagine if you could take your new
salesperson and use behavioral analytics
to assess their five-minute pitch against
the top 10% of salespeople in your
organization, then deliver them a
personalized development plan. If you
do this for all your salespeople and
continue to measure and tweak the
feedback, then the system only gets
smarter and faster.
Of course, given the reputation of outdated
computer-based learning programs,
the idea of taking the human experts
out of the equation does tend to raise
eyebrows. However, we know from
research and our own experience
with coaching both the "old" way and
through analytics, that automating
the learning process through these
data-science and AI-driven programs
leads to a more personalized
learning experience - and more
measurable results - than traditional,

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subjective coaching methods
content-only approaches.

or

3 WAYS MACHINE-DRIVEN
LEARNING OUTPERFORMS
TRADITIONAL COACHING
IT'S OBJECTIVE.
Professionals who rely on data and
research to make every major business
decision are more apt to accept data than
opinion, no matter how experienced the
coach.
After all, for somebody with a mind for
facts and statistics, "You didn't seem very
confident" sounds less compelling than,
"Your latest presentation scored 30%
less confident than average, because
you used more tentative language than
usual, including these five words..." The
former feedback is subjective - maybe
the audience felt differently - but the
latter is concrete, data-driven and paired
with an insight that can help drive
improvement in the future.
Additionally, with data, learners can track
their progress meticulously, watching
their scores increase rather than relying
on subjective comparisons from peers
and leaders. It's one thing to hear a
coach tell you you're getting better, but
it's another altogether to look at a chart
showing measurable progress in distinct
areas and highlighting areas that
need improvement.
Finally, objective scores can be modeled
against performance outcomes, so you
can demonstrate efforts' true ROI - in
areas like performance, engagement,
retention, selection and more.

IT'S IMPERSONAL.
Traditionally, giving feedback - in any
area, from leadership to job performance
to public speaking - has been a
highly personal and subjective activity.
No matter how skilled the coach or
constructive the feedback, learners tend
to take evaluations personally, dwelling
on the negatives and defending their
performance rather than focusing on
the recommended solutions.

When it's data rather than a human
delivering the tough love, however, it
creates a safer space in which learners
can accept feedback. No longer is the
learner hearing the coach's perspective
(which too often sounds like a judgment)
but, instead, is an seeing objective
analysis free of emotional impact. This
means that, when trainers and coaches
do get involved, they aren't the "enemy."
Instead, they're allies using the data to
build a healthy coaching relationship
on the foundation of improvement
and progress.

IT'S SCALABLE.
Elite training has historically been
too expensive (easily adding up to

WHAT HAPPENS TO LEARNING
WHEN WE TAKE HUMANS OUT
OF THE PICTURE?

Given the reputation of old-school,
computer-based L&D programs, the idea
of world-class coaching without human
involvement raises eyebrows. However,
there are three distinct advantages to
letting the data do the work:
1. It's objective. Savvy leaders make
their biggest decisions based on data,
research, and statistics - not opinions.
When the feedback is based in that
concrete data and evidence they
value for decision-making, it's easier to
accept than subjective opinions.
2. It's impersonal. While feedback
from a coach can feel like personal
judgment no matter how positive the
relationship, no emotions are involved
when the data does the talking. With
data-driven feedback, learners can
let down their defenses and focus on
improvement.
3. It's scalable. It would take too much
time and money to send a coach to
every team member, but automated,
data-driven programs can reach every
employee - on schedule and under
budget.
Training Industry Magazine - July/August 2019

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