I'm
Biljana
Besker,
and
I'm
a
JMP
Account
Executive
for
Global
Premier
Accounts.
My
colleague
Sarah
Springer
and
I
will
introduce
you
today
on
how
to
become
an
analytic
advocate
in
your
company
and
what
resources
we
have
available
at
JMP
to
help
you
get
there.
So
let's
start.
What
defines
an
analytics
advocate?
The
analytics
advocate
must
be
an
advocate
and
a
change
agent
who
spreads
the
analytic
strategy
and
fosters
an
analytic
culture
that
everyone
is
comfortable
using
data
-based
insights
to
improve
the
quality
and
effectiveness
of
their
decisions.
Five
characteristics
to
look
for
in
an
analytical
advocate
are,
first,
credibility.
They
are
trusted
and
well
respected
because
of
a
proven
track
record
of
managing
difficult
projects
to
successful
completion.
And
they
have
empathy
because
they
listen
to
and
addresses
fears
and
resistance
to
change
as
new
steps
are
taken
on
this
unfamiliar
path.
And
of
course,
they
are
problem
solvers.
They
are
willing
to
roll
up
their
sleeves
and
work
to
overcome
technical
and
cultural
challenges
that
arise
through
each
stage
of
implementation.
They
always
show
commitment.
They
support
the
analytics
strategy
and
promote
consistent
interpretation
of
the
goals
for
analytics.
And
they
are
flexible.
Data-driven
decisions
require
ongoing
evaluation
of
their
effectiveness.
An
analytics
advocate
must
recognize
when
the
part
of
the
analytic
strategy
is
not
working,
and
work
with
all
parties
to
redefine
the
solution.
What
is
considered
to
be
the
analytics
advocate's
role?
As
an
analytical
advocate,
you
must
promote
data
as
a
strategic
asset
and
you
have
to
address
resistance
and
promote
collaboration.
And
there
is
a
big
need
to
promote
a
culture
of
evaluation
and
improvement
and
to
educate
and
empower
the
workforce.
So
assets
do
not
necessarily
have
essential
value,
and
assets
are
associated
with
liabilities.
So
how
to
promote
data
as
a
strategic
asset?
Analytic
is
about
having
the
right
information
and
insight
to
create
better
business
outcomes.
Business
analytics
means
leaders
know
where
to
find
new
revenue
opportunities
and
which
product
or
service
offerings
are
most
likely
to
address
the
market
requirement.
It
means
the
ability
to
quickly
access
the
right
data
points
to
find
key
performance
and
revenue
indicators
in
building
successful
growth
strategies,
and
it
means
recognizing
risks
before
they
become
realities.
So
how
can
you
address
resistance?
There
are
three
levels
of
resistance
you
must
overcome.
The
first
and
most
important
level
is
the
C-Level
resistance.
Preparing
the
technical
infrastructure
for
an
effective
analytic
program
may
require
significant
resource
investment
for
an
unknown
return.
This
should
be
addressed
where
possible
with
a
small
project
recurring
minimal
infrastructure
to
secure
a
quick
win
with
positive
expected
ROI.
If
this
is
not
possible,
then
show
examples
where
others
in
the
same
industry
have
benefited.
Second
is
the
Department-
level
resistance.
Process
owners
may
resist
the
perceived
effort
associated
with
data
governance
processes
needed
to
make
data
cleaning
sufficient
to
support
analytics.
The
analytic
s advocate
must
find
ways
to
show
how
such
efforts
will
result
in
recurring
long
-term
benefits
to
the
organization
that
will
turn
in
regards
and
recognition
for
the
Department.
Again,
quick-win
projects
can
help.
However,
the
analytics
advocate
should
not
stop
there.
Important
tasks
are
best
accomplished
with
a
dependable
ally,
with
shared
interests.
And
last
but
not
least,
we
have
the
Front-line worker
resistance.
As
with
business
process
owners,
front-line
workers
are
not
interested
in
extra
work
as
we
know
if
it's
not
reflected
in
the
metrics
used
to
assess
their
performance.
A
smart
analytics
advocate
address
that
question,
what
is
in
for
me?
Integrating
analytics
solution
into
existing
workflows
reduces
incremental
effort
and
empowers
front-line
workers
to
make
more
informed
decisions
and
improve
job
performance.
So
how
to
become
an
effective
advocate
of
analytics?
As
an
analyst,
you
are
obviously
aware
of
the
power
of
data
analysis.
You
know
that
the
application
of
appropriate
analysis
techniques
to
a
well
constructed,
meaningful
data
set
can
reveal
a
great
deal
of
useful
information,
information
that
can
lead
to
new
opportunities,
improvements
and
efficiency,
reduction
in
costs
and
other
advantages.
While
many
organizations
have
adopted
analytics
on
a
wide
scale,
several
others
still
employ
it
only
in
certain
areas,
and
some,
believe
it
or
not,
rarely
use
it
at
all.
If
you
often
get
excited
thinking
about
new
ways
of
applying
analytics
in
your
organization
and
are
eager
to
share
your
excitement
with
people
you
think
would
benefit
of
analytics,
you
are
in
a
good
position
to
become
an
analytics
advocate
in
your
company.
So
first,
focus
on
the
person's
greatest
challenges
and
most
burdensome
tasks.
Everyone
has
something
about
their
job
that
is
source
of
frustration,
no
matter
how
much
they
love
what
they
do.
For
the
person
you are
working
with,
a
meaningful
application
of
analytics
is
one
that
relieves
his
or
her
frustration
or
minimizes
it
as
much
as
possible.
As
long
as
the
application
is
also
important
to
the
overall
business,
this
is
a
great
way
to
begin
to
show
someone
the
true
value
of
analytics.
It's
also
a
good
idea
to
start
small
and
then
work
your
way
up
to
bigger
projects
later
so
that
you
are
not
overwhelmed
and
thus
don't
run
the
risk
of
not
being
able
to
deliver.
Second
is
incorporate
their
knowledge
and
expertise.
You
may
be
an
expert
on
the
application
of
analytics,
but
you
are
most
likely
not
an
expert
on
every
functional
area
of
your
organization.
Not
even
the
CEO
can
make
that
claim.
Therefore,
you
must
rely
on
the
insight
of
others
to
help
you
understand
all
of
the
complexity
that
cannot
be
contained
within
the
data
set,
including
any
legal,
ethical,
or
other
considerations
that
must
be
taken
into
account.
What's
more,
you
are
demonstrating
respect
for
their
specific
knowledge,
which
will
help
build
trust
and
make
them
more
eager
to
work
with
you.
Third,
learn
to
speak
their
language.
Being
able
to
understand
and
communicate
in
the
terminology
used
by
the
people
you are
working
with
will
demonstrate
that
you
are
willing
to
meet
them
on
their
terms.
It's
not
a
two
-way
street.
However,
avoid
using
analytical
and
statistical
terminology
as
much
as
possible
.
If
necessary,
practice
finding
ways
to
explain
difficult
or
complex
concepts
in
an
easy
to
understand
manner.
Metaphors
often
work
well
for
this.
Fourth,
publicize
your
victories
and
show
the
credit.
Sorry...
and
share
the
credit.
Once
you
have
successfully
completed
the
project,
be
sure
to
tell
your
boss
.
Ask
him
or
her
to
spread
the
word
throughout
the
organization
and
externally
if
possible.
But
make
absolutely
sure
that
the
credit
is
shared
with
those
assisted
you
in
the
project.
This
will
help
build
attention
to
the
power
of
analytics
within
the
organization.
As
well
as
make
those
people
you've
just
worked
with
feel
rightfully
appreciated
and
respected.
If
you
look
closely
at
these
four
recommendations,
you'll
notice
they
all
have
one
thing
in
common.
They
put
the
focus
on
what
you
can
do
to
help
others.
Whatever
you
follow
these
specific
tips
or
not,
as
long
as
you
promote
the
use
of
analytics
as
a
service
that
can
help
a
person
solve
a
problem
that
is
important
to
them,
you
will
go
a
long
way
towards
fostering
a
positive
attitude
toward
analytics
throughout
your
organization.
But
how
to
become
a
successful
advocate
of analytics?
Put
user
experience
first
.
For
companies,
it
can
be
tempting
to
overlook
the
role
of
the
end-
user
and
focus
solely
on
business
outcomes,
which
is
why
the
analytic
advocate
must
ensure
that
the
focus
remains
on
the
value
and
overall
experience
for
end-
users
in
addition
to
the
positive
business
outcomes
the
company
wants
to
achieve.
To
bring
us
back
to
our
earlier
discussion
of
low
adoption
and
analytics
strategy
that
does
not
consider
the
user's
position
and
needs
is
at
risk
to
become
a
strategy
that
is
technically
capable
but
not
valuable
enough
to
keep
users
engaged.
To
mitigate
this
risk,
the
analytics
advocate
must
be
able
to
explain
both:
the
benefit
of
the
analytics
strategy
to
the
business,
but
also
ensure
that
the
strategy
is
beneficial
for
the
end-
users
who
need
to
make
business
decisions.
And
push
the
analytic
strategy
to
evolve.
Of
course,
user
and
business
requirements
change
over
time.
So
once
the
strategy
is
launched,
the
analytic
advocate
must
ensure
that
the
strategy
evolves
to
meet
those
demands
.
Without
repetition
,
the
strategy
runs
the
risk
of
outliving,
its
usefulness
and
driving
adoption
rates
down
as
a
result.
Instead,
the
analytic
advocate
must
monitor,
manage,
and
drive
the
strategy
forward
to
ensure
ongoing
utility
at
maximum
business
value.
Companies
who
want
to
introduce
an
analytics
strategy
can
make
themselves
much
more
likely
to
achieve
success
by
putting
that
strategy
in
the
hands
of
someone
who
can
understand end-users
and
push
the
project
to
improve
experiences
and
business
outcomes.
Who
understands
the
analytic
represents
a
journey
and
not
a
destination.
Successfully
appointing
an
analytic
advocate
is
the
first
step
in
this
process.
Let
me
summarize
what
we
just
learned.
At
the
most
strategic
level,
analytic
allows
organization
unlock
latent
value
from
their
data
to
gain
insights,
accomplish
business
objectives,
and
improved
profits.
While
these
insights
should
empower
everyone
in
the
organization,
many
organizations
resist
the
cultural
changes
needed
to
benefit
from
an
analytic
program.
As
first
step,
executive
leadership
must
establish
and
support
the
analytics
strategy.
Then
, designate
an
analytic
advocate
to
engage
stakeholders
to
unify
that
vision,
understand
and
address
pain
points,
overcome
resistance
to
adoption,
and
demonstrate
the
value
from
analytics
through
quick
win
projects.
All
organizations
can
better
accomplish
their
mission
of
leverage
and
analytic
with
a
data
-driven
decision
process.
Using
analytics
to
achieve
a
sustainable
competitive
advantage
and
generate
significant
return
on
investment
begins
with
a
well
-convinced
analytics
strategy
and
roadmap
for
success
that
is
aligned
with
and
supports
the
overall
business
strategy.
And
with
that
said,
I
would
like
to
hand
over
to
my
colleague
Sarah
Springer,
who
will
show
you
how
JMP
can
help
you
to
become
an
analytical
advocate
in
your
organization.
Thank
you.
Hi,
I'm
Sarah
Springer.
Biljana,
thank
you
so
much
for
providing
that
great
overview
of
what
makes
a
good
analytic
advocate
within
an
organization.
I'm
going
to
look
a
little
more
closely
at
a
couple
of
those
areas
that
Biljana
touched
on,
and
we're
going
to
talk
about
a
process
and
some
tangible
resources
that
will
assist
you
and
your
organization
in building
a
culture
of
analytics.
So
how
can
JMP
support
your
organization
in
becoming
more
analytical
and
how
can
we
support
an
analytics
advocate?
So
we've
outlined
a
process
here
to
help
you
accelerate
your
organization's
analytics
growth
curve.
So
that
process
is
going
to
go
through
a
couple
of
steps.
So
first,
we're
going
to
talk
about
how
to
build
a
team
of
data
ambassadors.
We're
going
to
talk
about
the
best
way
and
some
resources
to
identify
key
use
cases
and
define
success.
We're
going
to
talk
about
how
to
establish
an
efficient
data
workflow,
how
to
educate
and
what
resources
we
have
available
to
educate
and
upskill
yourself
and
your
colleagues,
how
to
socialize
your
analytics
successes,
and
then
how
to
democratize
data
and
the
process.
So
Biljana
touched
on
this
in
her
presentation.
But
what
is
in
it
for
you?
If
you're
an
analytics
advocate
within
your
organization,
what
can
this do
for
you
as
an
individual?
You
can
be
a
vision
setter
and
a
change-
agent
throughout
your
organization.
This
is
an
opportunity
for
you
to
make
a
real
impact
on
the
lives
and
the
well
being
of
the
people
in
your
organization.
You
can
be
a
subject
matter
expert.
If
you
identify
a
specific
problem
or
a
specific
area
of
deed
and
upskill
yourself
in
that
area.
You
can
really
be
looked
at
as
an
SME
within
your
organization
,
and
gain
some
recognition
for
yourself
within
your
organization
and
within
the
JMP
community.
You'll
be
gaining
credibility.
You'll
become
a
leader
in
teaching
others
the
skills
that
you've
learned
and
upskilled
on.
And
then
ultimately,
we've
seen
a
lot
of
our
analytic
champions
throughout
all
of
our
organizations
really
have
a
strong
resume
and
advance
in
their
careers
because
of
the
great
work
they've
been
doing
at
their
organizations
in building
a
culture
of
analytics
.
Data
is
everywhere.
Analytics
is
an
important
competitive
tool.
And
it's
really
past
the
point
of
being
able
to
not
have
analytics
embedded
in
your
organization.
And
so
what
we've
seen
is
individuals
that
have
been
in
analytics
advocate
within
their
organization
have
been
quite
successful
,
and
so
this
is
a
real
opportunity
for
you.
But
what
Biljana
mentioned
is
it's
really
also
about
helping
others
and
making
an
impact
on
your
organization
and
the
world
around
you.
And
so
what's
in
it
for
your
organization?
Advocates
play
a
key
role
in
demonstrating
value
and
ROI
.
You're
able
to
pick
a
project,
a
real
challenge
that
you
or
your
organization
is
having
and
show
the
true
value
of
the
impact
that
analytics
can
play
to
your
organization.
Adoption
of
JMP
or
an
analytical
tool
or
an
analytical
culture
can
really
help
,
again,
bring
the
organization
into
the
digital
transformation
age.
It is
at
the
point
right
where
we
can
no
longer
not
take
advantage
of
all
of
this
data
that
we
have
.
And
so
in
this
role
you
have
a
real
chance
to
make
an
impact
at
your
organization,
and
again
impact
your
organization's
bottom
line,
save
your
organization
money
by
improving
processes
or
producing
less
waste.
Other
use
cases
we've
seen
are
securing
time
-to
-market
and
you're
really
helping
your
company
to
stay
competitive.
So
the
first
part
of
the
process,
as
you're
thinking,
how
do
I
make
an
impact
at
my
organization
is
to
think
about,
as
Biljana
mentioned,
who
can
come
along
with
me
in
this
journey?
Who
else
is
feeling
the
same
pains?
Who
else
can
benefit
from
a
strong
analytic
culture?
So
looking
beside
you
into
other
departments,
but
then
also
up.
Who
at
the
executive
level?
What
executive
sponsor
might
be
interested
in
some
of
these
pain
points
I'm
having?
How
can
I
get
stakeholders
to
support
this
movement?
How
can
we
get
buy
-in
early?
And
so
the
goal
is
to
find
reliable,
passionate,
accountable
people
that
are
maybe
having
some
similar
challenges
as
you
to
walk
through
this
journey
with
you
and
to
help,
as
Biljana
mentioned,
show
the
value
and
prove
to
leadership
and
prove
to
stakeholders
that
this
work
is
valuable
and
deserves
attention
and
investment.
Once
you
have
your
colleagues
and
you
have
buy
-in
and
you
have
your
team,
what
we
want
to
do
is
the
next
step
of
the
process
is
really
looking
at
identifying
key
use
cases
and
defining
success.
So
what
success
looks
like
is
an
important
part
of
defining
an
analytics
strategy
.
Thinking
about
some
common
use
cases
within
your
organization,
maybe
you
have
too
much
data,
maybe
there's
data
not
being
used,
too
many
systems
to
get
the
job
done,
not
a
good
way
to
share
decisions,
maybe
there's
a
lot
of
wasted
time
being
able
to
sift
through
of
all
of
that.
So
figuring
out
what
is
my
organization's
challenge?
What
would
success
look
like?
How
can
I
move
the
needle?
And
as
Biljana
mentioned,
starting
small
is
important.
We
want
to
think
maybe
of
something
that's
not
a
huge
undertaking,
but
maybe
has
a
broad
impact.
So
as
you're
thinking
of
the
right
place
to
start,
these
are
some
things
to
consider
.
Some
great
resources
that
I
would
recommend
as
you're
thinking
through
this,
if
you
want
to
look
at
your
organization's
annual
report
or
10-K,
if
you're
a
public
organization,
or
maybe
there
are
some
internal
documents
that
are
outlining
for
the
year,
what
your
risk
factors
are
as
an
organization?
You
can
get
a
strong
overview
of
some
of
the
concerns
that
executive
leadership
has
about
maybe
some
of
the
risks
that
they
could
approach
this
year.
Often,
we
see
some
risks
across
R&D
and
manufacturing
that
might
be
very
relevant
to
being
able
to
solve
that
problem
with
analytics.
Maybe
it's
time-
to-
market.
Maybe
it's
improving
any
sort
of
defects
in
the
manufacturing
process
, right?
Those
are
things
outlined
in
your
organization's
10-K
or
your
annual
report.
And
that
could
be
a
really
great
win
for
you,
right?
If
you
can
pull
some
folks
together
to
want
to
solve
one
of
those
problems
or
improve
one
of
those
processes.
The
other
resource
I
would
recommend
taking
a
look
at
is
going
to
the
JMP
website
and
looking
at
our
customer
success
stories.
There's
a
whole
library
across
industry
and
challenge
that
could
really
get
your
wheels
turning
and
give
you
some
great
ideas
about
some
possible
use
cases
and
what
success
might
look
like.
So
once
you
have
your
team
and
once
you
have
the
goal,
next
you
want
to
think
about
how
to
create
and
establish
an
efficient
data
workflow.
So
it's
important
that
you're
able,
in
order
to
do
great
analysis,
you
want
to
have
good
data
access.
You
want
to
be
able
to
streamline
that
process.
How
are
you
pulling,
analyzing,
and
sharing
that
data?
How
are
you
getting
the
right
information
to
the
right
groups?
Where
is
your
data?
Is
it
accessible?
Is
there
anything
you
can
automate?
Can
you
make
anything
easier?
Can
you
use
JMP
Live
to
share
information?
So
there's
a
lot
of
things
to
take
a
look
at.
Tangible
resources
for
this
include
conversations
with
IT.
Maybe
you
can
look
at
possible
scripting
or
automation
within
JMP
or
within
your
analytical
tools
to
really
make
an
impact,
to
make
this
as
easy
as
possible
so
that
it's
in
the
hands
of
the
right
people
who
can
solve
these
real
problems
and
contribute
to
your
success
and
the
success
of
your
organization.
So
next,
we're
going
to
talk
about
a
step
that
is
very
close
to
my
heart,
training
and
upskilling
colleagues.
I
spent
some
years
at
SAS
within
SAS
education,
helping
JMP
users
do
just this.
And
so
I
wanted
to
touch
on,
once
you
have
your
team,
you
define
your
goals,
you've
got
your
data
access
in
a
good
spot.
We
want
to
talk
about
how
do
we
give
our
team
and
employees
and
users
the
tools
and
the
knowledge
to
execute
this
plan.
What
we're
finding...
There
was
a
survey
done
by
HR
Dive
studio
ID
and
SAS
that
was
conducted
in
October
of
2020
.
And
they
found
that
this
is
a
huge
need.
88 percent
of
managers
said
they
believe
their
employees'
development
plans
needed
the
change
for
2021.
A
lot
of
this
was
coming
out
of
us
shifting
into
a
pandemic
world
and
people
working
remotely
.
And
folks
are
really
asking
for
training
and
for
development
and
for
help.
Out
of
the
survey,
50 percent
of
managers
said,
employees
needed
more
upskilling,
more
reskilling,
and
more
cross-killing
.
And
41 percent
of
the
employees
themselves
said
the
same
thing.
And
that
when
considering
the
types
of
skills
employees
should
focus
on,
employees
needed
more
technical
skills.
They
really
, really want
to
build
their
skill
set.
And
so
as
you're
thinking
about
how
to
build
an
analytics
culture,
training
and
upskilling
is
really
important.
And
people
are
wanting
those
more
technical
skills
so
that
they
can
make
a
contribution
in
this
age
of
digital
transformation.
So
the
survey
also
brought
to
light
five
major
learning
and
development
trends.
So
I
just
wanted
to
highlight
this
as
something
to
be
thinking
about
as
you
think
about
your
strategy.
The
trends
were
that
companies
are
now
expected
to
take
on
more
responsibility
for
employees
and
society,
and
making
sure
that
they're
getting
what
they
need,
that
people
are
being
taken
care
of
.
And
companies
need
to
match...
Another
theme
was
that
companies
need
to
match
their
technological
investment
with
the
learning
and
development
of
their
people.
Learning
and
development
are
much
more
universal,
and
it's
really
a
strong
recruiting
and
retention
skills.
And
again,
these
hard
skills
are
really
in
demand.
And
so
as
you're
thinking
about
your
strategy,
it's
so
important
to
think
about
how
can
I
help
my
colleagues,
my
organization,
get
the
right
knowledge
and
training
in
their
hands
so
that
they
can
really
be
impactful
with
all
this
data
that
we
have.
So
here
at
JMP,
we
have
a
couple
of
resources
I
want
to
point
out
that
can
be
really
powerful
to
help
upscale
your
organization.
The
first
that
we're
going
to
touch
on
is
the
Statistical
Knowledge
Portal.
Then
, we're
going
to
take
a
deeper
dive
into
STIPS,
which
is
our
Statistics
Course.
It's
a
free
online
course
called
Statistical
Thinking
for
Industrial
Problem
Solving.
It
is
award-
winning,
and
it
is
self-
paced,
and
a
wonderful
resource
that
many
of
our
customers
are
using
to
provide
analytical
development
to
their
employees.
And
then
finally,
we
do
have
some
formal
SAS training
and
some
resources
that
I
do
want
to
point
out
as
we
go
through
this
process.
So
the
Statistical
Knowledge
Portal
is
a
great
site.
I've
put
the
link
there
for
you
that
has
information
in
all
of
these
different
areas
that
I've
listed.
So
it's
a
great
way
if
you
have
somebody
that
needs
to
know
a
very
specific
skill,
they
can
go
on
here.
They
can
pull
some
resources
and
skill
up
fairly
quickly.
It's
a
great
way
to
get
them
started,
to
get
their
feet
wet,
to
develop
some
knowledge,
to
get
some
tips
and
tricks.
I
would
highly
recommend
spending
some
time
on
this
website.
And
then
you,
as
the
analytics
advocate,
can
really
help
drive
the
person
to
what
skill
they
might
need
based
on
your
project.
So
I
think
there's
a
lot
of
collaboration
that
can
happen
here.
But
I
do
want
to
point
out
that
this
is
a
phenomenal
free
resource
on
the
JMP
website
and
has
a
lot
of
great
statistical
information
for
you.
The
next
one
I
want
to
point
out
is
STIPS.
So
all
of
these
modules
that
are
on
the
right
are
self-
paced.
They're
deep-
dive
d into
the
topic
area.
They are
hands-
on
exercises
.
And
it's
really
going
to
help
you
get
up
to
speed
and
understand
that
statistical
concept.
So
as
you're
working
on
your
project,
as
you're
working
towards
your
goal,
think
about
different
areas
of
this
course
that
might
be
helpful.
There
is
a
great
overview
module
at
the
beginning
as
well
that
I
would
recommend
that
talks
about
what
different
processes
you
can
use
to
begin
to
be
thinking
statistically
throughout
your
organization.
So
it
starts
at
the
beginning,
and
then
it
goes
all
the
way
down
to
advanced
modeling,
so
it
can
really
meet
you
where
you
are.
And
we'll
talk
a
little
bit
more
about
this
course.
So
what
I
love
about
this
course
is
this
is
really
something
that
JMP
has
put
out
because
they
want
folks
to
be
strong
in
analytics
and they
want
folks
to
understand
statistics
and
to
understand
the
why
behind
what
we're
doing.
And
so
we've
put
out
some
additional
resources
to
help
companies
upskill
their
teams.
So
you
can
take
this
course
in
a
self-
paced
format.
But
we've
had
many,
many
customers
want
to
use
these
materials
in
a
different
way.
We
have
customers
doing
lunch
and
worn
throughout
their
organization,
having
sessions
where
they'll
take
a
specific
concept
from
the
course
and
have
discussion
groups.
We
have
professors
and
universities
using
steps
or
some
of
this
material
as
prerequisites
or
even
within
their
statistics
courses.
And
so
what
we've
done
is
we've
made
teaching
materials
that
has
put
some
of
this
material
into
PowerPoint
slides
for
you
to
use
at
your
organization
for
some
internal
training.
And
we
wanted
to
make
that
easy
and
accessible
for
you.
So
going
to
jump.com/
statistical
thinking,
there's
an
online
form
on
the
right
hand
side
of
the
page
where
you
can
fill
that
form
out
and
get
these
materials
to
use
to
help
upskill
your
team.
And
then
finally,
the
third
training
resource
I
wanted
to
touch
on
is
Formal
SAS
Training.
SAS
has
incredibly
strong,
relevant
trainings,
hands-
on
trainings
that
provide
a
real
great
depth
and
understanding
of
different
concepts.
So
there's
lots
of
different
formats
for
individuals,
large
groups,
small
groups.
And
I've
put
the
link
up
here
so
you
can
go
check
out
those
courses
as
well.
It's
a
really
great
way
to
upskill
your
team
and
then
make
sure
they
have
the
right
tools.
And
if
you
don't
know
where
to
start,
I
definitely
wanted
to
highlight
a
tool
that
Fast
Education
offers
called
the
Learning
Needs
Assessment.
It's
a
data
driven
survey
that
can
be
distributed
to
your
team
according
to
learning
area
of
what
major
areas
that
we
often
see
our
customers
needing.
Maybe
the
major
courses
that
SAS
Education
offers
around
design
of
experiments
or
scripting
or
a
Novel
regression.
These
are
great
resources.
And
if
you
don't
know
where
to
start,
we
want
to
be
able
to
survey
your
team,
identify
what
their
preferred
learning
style
is,
identify
their
competency
in
these
areas,
and
then
put
it
in
a
report
that's
easy
for
you
and
managers
and
executive
leadership
to
understand.
And
then
we
would
work
together
with
you
to
make
great
recommendations.
And
those
recommendations
could
be
use
of
steps,
it
could
be
use
of
formal
training,
it
could
be
complimentary
resources
from
the
Statistical
Knowledge
Portal,
but
it
helps
give
you
an
idea
of
where
to
start
if
you're
not
quite
sure
according
to
your
project
and
your
goals,
what
your
skill
gaps
are,
sometimes
you
need
a
little
help
identifying
those.
So
that's
what
this
is
for.
So
once
you've
got
your
team
upskilled,
once
your
team
is
trained
in
the
areas
and
you're
working
on
your
project,
it's
time
to
document
those
successes,
right?
Biljanna
touches
on
this
as
well.
You
want
to
be
able
to
document
that
as
a
proof
of
concept,
show
the
value
to
your
organization,
continue
to
get
that
commitment
and
investment
in
your
work,
your
team's
work,
in
the
power
of
analytics,
continue
to
help
your
organization
move
towards
digital
transformation.
And
so
being
able
to
document
these
successes
are
important.
A
couple
of
resources
that
I've
found
helpful
to
do
this,
I
think
the
main
one
is
our
customer
success
program.
We
do
have
a
great
program,
I
mentioned
earlier,
where
you
can
get
these
stories
published
on
the
website,
but
we've
also
helped
some
organizations
with
internal
stories.
Ask
your
account
team
for
help.
We
want
to
help
you
document
these
successes,
and
so
we
can
certainly
help
you
do
that.
And
then
often
we
can
help
you
do
that
if
you
want
to
tell
a
story
in
JMP,
we
would
love
to
help
you
show
the
impact
that
you've
made
for
your
organization.
And
then
finally
being
able
to
democratize
data
in
the
analytic
process.
So
this
is
one
of
those
steps.
How
can
we
take
what
you've
done
as
a
group
and
then
spread
this
further
throughout
your
organization?
Once
you've
done
this
and
you've
documented
your
successes,
I'm
sure
you're
seen
as
effective
as
a
leader,
you're
probably
well
respected.
So
now
you
get
the
opportunity
to
make
even
broader
of
an
impact
on
your
colleagues
and
bring
them
along
with
you
in
that
success
and
make
an
impact
on
your
organization.
So
what
you
can
do
from
here
is
really
empower
more
people
to
be
more
data-
driven.
And
I
think
using
things
like
I
mentioned
with
some
of
the
steps
tools,
maybe
you're
leading
lunch
and
worms,
maybe
you're
creating
a
user
group,
maybe
you're
doing
an
internal
newsletter
about
the
power
of
analytics,
maybe
you're
working
with
the
JMP
team
to
do
doctor's
day
in
sessions
or
different
sessions
around
features
that
have
been
very
helpful
to
you
with
your
project.
So
this
is
your
opportunity
to
help
others,
and help
others
at
your
organization
make
an
impact,
and
help
your
organization
shift
to
be
more
data-
driven
in
today's
digitally
transformed
world.
So
I
want
to
leave
you
with
some
tangible
next
steps.
We've
gone
through
a
process
of
how
to
build
a
culture
of
analytics.
And
as
the
next
step,
JMP
has
a
great
resource,
jmp.com/advocate,
where
you
can
go
and
learn
more
about
each
of
the
steps
that
we've
outlined
today
and
what
resources
are
available
to
you
that
corresponds
each
step.
So
today
has
been
a
great
overview,
but
if
you
do
want
to
take
a
tangible
step
to
move
towards
an
analytical
culture
within
your
organization,
I
would
highly
recommend
that
you
go
here
and
check
it
out
and
then
don't
hesitate
to
reach
out
to
your
account
team.
We're
all
here
to
help
and
we
want
to
support
you
in
making
an
impact
at
your
organization
and
around
the
world.
Here
are
sources
for
your
viewing
pleasure.
And
I
just
want
to
thank
you
very
much
for
your
time
and
attention
today.
Be
well.
