Coachable Business Results

Published date01 November 2015
Date01 November 2015
© 2015 Wiley Periodicals, Inc.
Published online in Wiley Online Library (
DOI 10.1002/jcaf.22104
Coachable Business Results
Tim Chartier
The office is stuffy after
hours of discussion
and analysis. How can
outcomes be improved? Can
shortcomings be foreseen and
minimized? What preparations
should be changed to meet
overall goals? Scraps of paper
contain scribbles of ideas.
Asmudged whiteboard has
an eclectic outline of the day’s
Is this scene a familiar
one? Can you think of a time
when you or others in your
office enacted such moments?
Are you a basketball coach?
Why do I ask? The office
I’m describing belongs to a
coach of the men’s basketball
team at Davidson College as
they analyze team and player
I speak nationally and
internationally about my work
in data analytics. A popular
topic is my work in sports. A
number of points resonate with
chief executive officers, chief
information officers, and finan-
cial analysts in the audience.
This article will discuss a point
that comes up after most every
talk: produce coachable results.
What is a coachable result?
To answer this question, let’s
discuss how this work began.
In the fall of 2013, a group
of four undergraduate math
majors and I met with coaches
of the Davidson College
men’s basketball team called
the Wildcats. We decided to
explore the potential of our
group supplying analytics for
the team. Forthe next two
months, we met weekly to hone
our work to their needs.
This was an exciting step
for our group, which now calls
itself Cats Stats. We quickly
produced results that interested
us and presented them to the
coaches. Some of the work
led to analytics we supply for
the team. Other presentations
were met with a very simple
remark, “This isn’t coachable.”
Said another way, we found
an interesting insight but not
something actionable.
Hearing that an analytic
isn’t coachable began a con-
versation. In order for us to
supply helpful results, we had
to understand the coaches’
needs and goals. They wouldn’t
mine through the data. They’d
use the results as part of their
larger work. So we asked
whya result wasn’t coachable.
Through their answers, we
learned more about basketball
in the context of their coach-
ing, which made us better data
analysts for the team.
In time, we grew to better
recognize and produce coach-
able results. Even now, we do
not assume we fully under-
stand the coaches’ needs. When
we produce results, we take
them to the coaches for their
input. Sometimes we present
failed results or less interesting
statistics for their feedback.
Let’s consider a recent
example. After producing
two new analytics, we set a
meeting with the coaches.
Wethought one of the analyt-
ics was helpful and the other
was not. In the meeting, the
coaches were excited about
both, especially the insight
that we thought wouldn’t help.
Again, this was an opportu-
nity for our group to grow
in our understanding. So I
immediately asked, “How is
this coachable?” The coaches
explained how looking at our
work could influence where
they might direct the ball in
a game or how they might
instruct players to move with
the ball. We had a coachable
result that we almost discarded.
This connects to an impor-
tant part of our work. How do
we know we have a coachable
result? Simply put, the coaches
tell us. Keep in mind that they
don’t always know. Sometimes,

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