Ease of Use in BI serves only the operator, not the organization. Instead, we introduce a concept of Ease of Usefulness and describe what BI lack. Propagating the results of analytics requires nee skills in storytelling and metaphor

1. Storytelling
Drives
Usefulness
in
Business
Intelligence
Storytelling
Drives
Usefulness
in
Business
Intelligence
By
Neil
Raden
Hired
Brains,
Inc.
December 2013
©
2013
Hired
Brains
Inc.
All
Rights
Reserved
1

2. Storytelling
Drives
Usefulness
in
Business
Intelligence
2
Table
of
Contents
Executive
Summary
................................................................................................................
1
Ease
of
use
..................................................................................................................................
4
Relevance
and
Understanding
......................................................................................................
7
Going
From
One
to
Many:
Storytelling
.............................................................................
9
Metaphor
...........................................................................................................................................
12
Using
Storytelling
with
Visual
Analysis
..................................................................................
13
Conclusion
...............................................................................................................................
16
ABOUT
THE
AUTHOR
..........................................................................................................
18
©
2013
Hired
Brains
Inc.
All
Rights
Reserved

3. Storytelling
Drives
Usefulness
in
Business
Intelligence
1
Executive
Summary
“The
real
voyage
of
discovery
consists
not
in
seeking
new
landscapes,
but
in
having
new
eyes.”
Marcel
Proust
Any
individual
exploration
or
examination
of
the
data
must
be
easily
conducted
and
shared,
communicated
and
subject
to
group
collaboration
and
consensus
that
characterizes
decision-­‐making
in
most
cases.
Ease
of
use
has
to
be
evaluated
in
a
broader
context
of
“ease
of
usefulness”
to
the
audience
of
stakeholders,
not
a
single
set
of
eyes.
A
key
competency
for
moving
analysis
from
the
frontal
lobes
of
an
analyst
to
other
principals
in
the
process
is
the
ability
to
tell
a
story
with
data.
Data
Discovery
is
a
recent
innovation
in
Business
Intelligence
that
can
bypass
the
structure
of
a
data
warehouse
and
allow
people
to
create
their
own
viewpoints
by
assembling
analyses
and
visualizations,
animating
them
and
sharing
them.
While
performance
and
“ease
of
use”
are
necessary
qualities
in
this
field,
they
are
far
from
sufficient.
There
is
no
measure
for
ease
of
use,
except
the
one
that
shows
in
low
adoption
rates.
A
colorful
GUI
does
not
perform
if
the
underlying
actions
are
not
understood
clearly
by
the
user.
Tools
must
be
relevant
to
the
work
that
people
do
(not
additive
or
complementary).
The
underlying
data,
models
and
assumptions
must
be
understood.
In
this
paper,
we
examine
three
concepts
that
are
needed
to
succeed:
•
A
realistic
model
of
“ease
of
use”
•
A
needed
competency
to
weave
a
story
from
data
as
a
means
to
achieve
positive
results
from
analytical
work
©
2013
Hired
Brains
Inc.
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Rights
Reserved

4. Storytelling
Drives
Usefulness
in
Business
Intelligence
2
•
Examining
the
benefit
derived
when
people
are
able
to
ask
questions
as
needed
Background
Numerous
names
have
been
used
to
describe
the
technology
and
methods
that
allow
people
to
draw
insight
from
various
sources
of
data:
decision
support
systems,
business
intelligence,
business
analytics,
predictive
analytics
and
business
discovery.
For
the
sake
of
brevity,
we
refer
to
this
class
of
technology
as
business
intelligence
or
BI.
It
is
clearly
an
industry
segment
with
fuzzy
edges.
In
addition,
the
names
are
somewhat
misleading
as,
in
fact,
these
approaches
are
used
more
widely
than
just
for
business:
in
science,
government,
non-­‐profit
sectors
and
others.
Over
thirty
years
or
so,
much
that
has
been
written
about
these
subjects
focused
on
technology,
features
and
poorly
defined
aspects
such
as
performance
and
ease
of
use.
Useful
to
a
point,
these
writings
often
avoid
the
well-­‐documented
fact
that
uptake
of
BI
in
organizations
is
historically
less
than
20%,
often
much
less.
To
remedy
this,
various
initiatives
take
place
by
BI
vendors
to
achieve
“pervasive
BI”
but
except
in
rare
cases,
it
does
not
achieve
the
objective.
The
blame
is
usually
placed
on
not
enough
executive
support
or
on
IT
control
that
fails
to
meet
the
needs
of
the
expected
audience.
What
is
rarely
addressed
is
that
people
in
organizations
make
a
rational
decision
to
apply
other
techniques.
Spreadsheets
are
the
most
common
course,
but
from
an
organizational
point
of
view,
they
are
not
an
optimal
solution.
The
emergence
of
e-­‐Business
and
web-­‐oriented
applications
surfaced
an
appreciation
for
user
“experience”
and
“engagement,”
very
different
from
the
engineering
and
“human
factors”
approach
of
user
interface
design
of
enterprise
systems.
BI
vendors
“ported”
their
user-­‐facing
applications
to
web-­‐based
interfaces,
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2013
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5. Storytelling
Drives
Usefulness
in
Business
Intelligence
3
but
unfortunately,
the
underlying
models
remained
the
same.
A
new
interface
did
not
bring
more
“experience”
or
“engagement.”
On
the
contrary,
they
were
the
same
old
tools
in
a
new
wrapper
which
failed
to
engage
the
wider
audience
more
accustomed
to
true
web-­‐based
applications
designed
for
the
web.
What
had
been
lacking
in
the
overall
discourse
about
BI
is
how
can
people
make
use
of
the
tools
effectively,
regardless
of
the
technology.
For
example,
what
exactly
is
needed
for
people
to
not
only
be
informed
by
these
systems,
through
their
own
efforts
or
presentation
of
material
from
others,
but
to
use
the
insight
to
make
well-­‐
informed
and
actionable
decisions?
Most
people
who
are
not
technologists
are
unimpressed
with
features;
they
are
interested
in
finding
ways
to
be
more
effective.
It
isn’t
automatic.
In
short,
ease
of
use
on
an
individual
level
pales
in
importance
to
how
well
a
given
application
contributes
to
the
overall
ease
of
use
of
the
group.
While
any
BI
system
must
be
engaging,
performant,
fault
tolerant
and
helpful,
findings
have
to
be
communicated
and
explained
to
others.
Making
copies,
pointing
at
a
screen
and
developing
presentations
are
of
limited
use..
The
most
effective
method
for
communicating
ideas
and
insights
to
others,
and
making
them
stick,
is
the
needed
competence
of
telling
a
story
with
data.
©
2013
Hired
Brains
Inc.
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Rights
Reserved

6. Storytelling
Drives
Usefulness
in
Business
Intelligence
4
Ease
of
use
Even
on
an
individual
basis,
ease
of
use
is
a
pretty
complex
idea.
Some
things
just
aren’t
easy.
Analyzing
data,
navigating
through
it,
looking
for
patterns,
choosing
the
right
visual
display
–
no
matter
how
much
assistance
a
product
can
provide,
analysis
still
requires
some
effort.
For
those
who
find
exerting
this
kind
of
effort
tedious,
ease
of
use
is
not
acknowledged.
But
for
those
so
inclined,
tools
that
handle
the
tedious,
repetitive
and
obvious
work
are
considered
easy
to
use.
For
a
long
time,
it
was
assumed
that
ease
of
use
was
not
an
issue
for
those
involved
in
the
production
of
information
technology:
programmers,
designers,
analysts,
etc.
The
understanding
was
that
they
were
so
conversant
in
their
cryptic
(or
verbose)
languages,
scripts
and
configurations,
that
any
attempt
to
make
it
easier
to
use
was
a
sort
of
affront
to
their
sensibilities.
That
assumption
was
wrong.
With
the
development
of
IDE’s
(Integrated
Development
Environments),
Version
Control,
Higher-­‐Level
Languages
and
a
host
of
other
innovations,
the
process
of
creating
and
maintaining
systems
became
much
easier,
not
necessarily
with
the
uses
of
GUI
and
mouse
and
colors
and
buttons,
but
by
fundamentally
changing
and
streamlining
the
way
developers
work.
Much
of
development
these
days
is
configuration
of
applets,
reliance
on
tools
such
as
relational
databases
and
programming
in
object-­‐oriented
or
even
functional
languages.
Even
more
importantly,
these
tools
it
made
it
considerably
easier
for
large
projects
to
spread
across
groups,
or
even
oceans,
not
only
for
development,
but
for
maintenance
and
enhancement
too.
Unfortunately,
much
of
what
passes
for
ease
of
use
on
the
user
(or
analytical)
side
has
not
addressed
a
fundamental
change
in
the
operation
of
business
intelligence.
It’s
been
focused
on
simplifying
things
that
aren’t
simple,
masking
complexity
and
providing
a
pleasing
interface
(at
best)
to
the
individual
using
the
system.
For
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2013
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Brains
Inc.
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Reserved

7. Storytelling
Drives
Usefulness
in
Business
Intelligence
5
example,
a
major
research
report
summed
up
ease
of
use
for
Business
Intelligence
as
follows:
The
solution
is
easy
to
use
when:
•
It
is
familiar
because
it
works
as
expected
and
is
similar
to
another
tool
with
which
a
user
has
experience.
•
It
takes
less
time
and
fewer
clicks
to
accomplish
the
ultimate
goal.
Routine
tasks
may
be
automated
and
personalized.
•
It
is
intuitive
and
obvious
in
how
a
task
can
best
be
performed.
From
Ease
of
Use
and
Interface
Appeal
in
Business
Intelligence
Tools
By
Cindi
Howson,
BiScorecard
This
one-­‐person-­‐at-­‐a-­‐time
concept
of
ease
of
use
has
not
addressed
the
central
issue
–
how
do
you
change
the
way
analytical
work
is
done
in
an
organization?
How
do
you
get
beyond
one
person
and
a
display
of
information,
to
a
seamless
environment
where
analyses,
ideas
and
conclusions
are
shared?
Masking
complicated
requests
with
pleasing
interfaces
doesn’t
make
them
easier.
In
fact,
it
often
does
just
the
opposite.
Those
who
couldn’t
learn
the
lower
level
interface,
such
as
a
scripting
language,
still
can’t
and
those
who
could
learn
the
lower-­‐level
interface
often
find
the
“helpful”
interface
an
impediment.
The
way
to
make
something
complicated
easy
to
use
is
to
make
it
less
complicated.
For
instance,
in
business
discovery
software
like
Tableau
(among
others),
people
seeking
information
usually
start
with
what
they
easily
grasp
then
incrementally
explore,
like
feeling
for
the
first
step
in
the
dark
with
your
foot,
then
moving
more
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2013
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8. Storytelling
Drives
Usefulness
in
Business
Intelligence
6
surely
with
subsequent
ones1.
But
it
is
too
easy
for
BI
to
complicate
and
hinder
this
process
by
forcing
the
driver
to
make
all
the
decisions
in
detail
with
each
step
instead
of
anticipating
what
they
might
be,
learning
from
the
person’s
habits.
Ten
years
ago
this
may
have
seemed
like
a
dream,
but
it
is
quite
common
in
customer-­‐
focused
applications
today,
but
BI
has
trailed.
To
illustrate
the
gap
between
what
is
perceived
as
ease
of
use,
and
the
reality,
consider
a
vacuum
sweeper:
Presumed
ease
of
use
A
robotic
vacuum
cleaner
than
runs
on
its
own,
vacuuming
the
floor
in
an
unattended
way.
Actual
Experience
The
small
bag
has
to
be
changed
frequently,
doesn’t
thoroughly
vacuum
completely
and
usually
requires
bringing
out
the
conventional
sweeper
to
finish
the
job
Actual
Ease
of
Use
A
sweeper
with
exceptional
suction
that
vacuums
in
one
sweep
and
has
an
easy
to
empty
canister
with
no
bag.
Ease
of
use
has
to
be
couched
in
terms
of
doing
the
whole
job.
Ease
of
use
first
and
foremost
requires
that
BI
be
useful
to
people
and
is
relevant
to
the
work
they
do.
It
must
promote
understanding
through
shared
ideas
and
discussion.
With
respect
to
BI,
a
proper
test
of
ease
of
use
has
to
include:
•
Obviously,
elements
of
individual
ease
of
use,
especially
an
interface
that
exposes
functionality
in
a
way
that
is
understandable
•
Performance
cannot
be
separated
from
ease
of
use;
it’s
a
“right
now”
world
today
•
It
is
not
sufficient
for
BI
to
inform
an
analyst;
being
informed
does
not
necessarily
lead
to
better
decisions,
or
even
making
them
1
This
statement
is
a
metaphor.
Its
use
in
storytelling
is
explained
in
a
further
section
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2013
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Inc.
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9. Storytelling
Drives
Usefulness
in
Business
Intelligence
7
Measures
of
ease
of
use
are
irrelevant.
All
that
matters
are
that
people
use
the
tools
productively.
They
vote
with
their
time
and
participation.is
this
really
a
bullet
point
under
that
heading?
Relevance
and
Understanding
What
does
it
mean
for
a
BI
environment
to
be
relevant?
Do
the
tools
and
information
provide
a
degree
of
utility
great
enough
to
warrant
modifying
your
work
processes
to
incorporate
them?
For
the
most
part,
BI
in
general
has
not.
This
of
course
begs
the
question,
“Why
are
these
efforts
not
relevant?”
The
irritating
refrain
from
past
Presidential
elections,
“Are
you
better
off
now
than
you
were
four
years
ago,”
is
a
good
metaphor2.
Has
the
implementation
of
your
analytical
environment,
typically
a
data
warehouse
and/or
data
marts
plus
a
BI
tool
made
things
better?
Is
your
organization
more
effective?
Are
you
making
better
decisions?
Do
you
have
a
better
grasp
on
the
elements
that
drive
your
success?
One
element
that
is
prominent
in
our
research
is
understandability.
One
shouldn’t
confuse
this
with
Ease
of
Use.
People
don’t
just
float
out
of
their
smokestacks,
they
have
to
be
rescued.
What
is
understandable
to
a
data
modeler
is
not
necessarily
understandable
to
anyone
else.
In
many
cases,
people
are
staring
at
a
schema
that
is
loaded
with
relational
and/or
multidimensional
terms,
like
keys,
joins,
dimensions,
attributes
and
slices.
In
her
landmark
book,
“In
the
Age
of
the
Smart
Machine,”
3
a
volume
that
no
practitioner
in
this
business
should
leave
unread,
Shoshanah
Zuboff
offers
some
2
ibid
3
Shoshana
Zuboff,
In
the
Age
of
the
Smart
Machine:
The
Future
of
Work
and
Power,
(New
York:
Basic
Books,
1988)
391-­‐392
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10. Storytelling
Drives
Usefulness
in
Business
Intelligence
8
insight
into
the
relationship
between
learning
and
control
in
organizations:
“A
commitment
to
intellective
skill
development
is
likely
to
be
hampered
when
an
organization’s
division
of
labor
continuously
replenishes
the
felt
necessity
of
imperative
control.
Managers
who
prove
and
defend
their
own
legitimacy
do
not
easily
share
knowledge
or
engage
in
inquiry.
Workers
who
feel
the
requirements
of
subordinates
are
not
enthusiastic
learners.
New
roles
cannot
emerge
without
the
structures
to
support
them.
If
managers
are
to
alter
their
behavior,
then
the
methods
of
evaluation
and
reward
that
encourage
them
to
do
so
must
be
put
in
place.
If
employees
are
to
learn
to
operate
in
new
ways
and
to
broaden
their
contribution
to
the
life
of
the
business,
then
career
ladders
and
reward
systems
reflecting
that
change
must
be
designed.
In
this
context,
access
to
information
is
critically
important;
the
structure
of
access
to
information
expresses
the
organization’s
underlying
conception
of
authority.”
The
implications
are
clear:
We
cannot
force
success
with
BI
without
a
desire
and
commitment
on
the
part
of
the
organization
to
change
and
improve
the
flow
of
information,
the
optimization
of
work
processes
and
the
breakdown
of
artificial
barriers
that
serve
certain
participants,
but
not
the
organization
as
a
whole.
This
is
a
much
greater
challenge
than
“change
management,”
a
nebulous
term
that
is
applied
with
no
rigor.
Despite
our
best
efforts,
all
too
often,
projects
fail
to
reach
their
goals
for
reasons
that
are
not
at
all
obvious.
It’s
easy
to
pinpoint
the
usual
suspects,
such
as
mid-­‐
project
organization
realignment
and
killer
politics,
our
inability
as
consultants
to
convince
our
clients
that
certain
decisions
are
sub-­‐optimal
and
a
host
of
others,
well
documented
in
the
literature
(“Ten
Mistakes
to
Avoid…”).
But
there
are
also
many
cases
where
everything
goes
well,
yet
the
initiative
never
gets
traction
in
the
organization,
penetration
stays
at
a
very
low
level
and
the
ROI
projections
are
not
met.
In
many
of
those
cases,
this
failure
to
thrive
has
been
something
of
mystery.
Part
of
the
answer
is
that,
despite
good
intentions,
it
may
not
be
possible
in
some
organizations
to
make
BI
relevant
without
a
concerted
effort
to
help
people
change
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11. Storytelling
Drives
Usefulness
in
Business
Intelligence
9
their
habits.
Developing
a
spreadsheet
or
personal
database
is
a
singular
effort
and
in
those
organizations
described
by
Zuboff
above,
the
collaboration
needed
to
make
BI
successful
is
just
not
possible.
A
collection
of
singular
efforts,
inefficient
and
potentially
inaccurate
as
it
is,
simply
has
a
greater
chance
of
being
used
as
it
skirts
the
lines
of
authority
and
control.
Another
less
ominous,
but
still
dysfunctional
problem,
is
that
is
it
simply
too
difficult
to
actually
build
models
in
most
BI
tools,
which
are
primarily
designed
for
ad
hoc
query
and
analysis
using
pre-­‐built
relationships.
So
the
first
step
is
in
our
court,
as
an
industry,
to
learn
how
to
bundle
the
appropriate
organizational
transformations
into
the
technology
implementation.
But
there
is
more.
Our
offerings
must
be
more
aligned
with
the
actual
work
that
people
do.
Going
From
One
to
Many:
Storytelling
Before
humans
knew
how
to
write,
probably
before
they
even
had
language,
the
means
for
passing
wisdom
from
one
person
or
one
generation
to
the
next
was
storytelling.
Most
likely
our
brains
are
wired
to
respond
to
and
retain
stories
(though,
oddly,
not
necessarily
proficient
at
telling
them).
Nevertheless,
it
remains
perhaps
our
most
powerful
tool
of
communication.
To
put
it
bluntly,
people
are
generally
more
interested
in
a
story
than
in
the
storyteller.
If
you
want
to
get
your
point
across,
you
need
to
learn
how
to
condense
the
data
into
a
good
story.
But
how
do
you
tell
a
story
that
can
convince
and
compel?
To
begin
a
discussion
of
telling
a
story
with
data,
it’s
a
good
idea
to
start
with
a
(real)
story.
This
happened
in
the
early
days
of
OLAP
technology:
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12. Storytelling
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Usefulness
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10
Consultant:
So
we’ve
built
this
facility
for
you
so
that
you
can
align
promotional
spend
with
results
using
time
series
analysis.
You
navigate
on
any
of
the
dimensions,
or
pivots,
aggregating,
filtering
or
even
drilling
into
detail
in
this
point-­‐
and-­‐click
interface.
You
have
the
facility,
when
you’re
ready,
to
perform
some
ARIMA
analysis
to
do
some
forecasting.
Client:
You
don’t
get
it,
do
you?
Consultant:
I’m
sorry?
Client:
I
don’t
want
to
navigate
or
drill
or
whatever
you
call
it,
that
doesn’t
help
me
at
all.
This
is
a
$5
billion
company
and
we
spend
$1
billion
a
year
on
promotions.
I
don’t
know
if
one
dollar
of
that
is
spent
wisely.
I
want
you
to
tell
me
where
to
focus
my
promotional
spend
next
year.
Consultant:
Oh.
This
is
like
a
story
in
a
story.
The
inner
story
is
that
what
the
client
was
saying,
which
wasn’t
grasped
right
away
by
the
consultant,
was
that
they
failed
to
tell
a
story
and
no
matter
how
informative
the
facility,
it
didn’t
solve
the
client’s
problem.
The
outer
story
is
what
Steven
Denning4
calls
a
“springboard
story,”
Which
he
defines
as:
1.
Must
be
a
“story”
with
a
beginning,
middle
and
end
that
is
relevant
to
the
4
http://www.amazon.com/exec/obidos/ASIN/0750673559/qid=984605028/103-­‐
7657515-­‐1436633
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13. Storytelling
Drives
Usefulness
in
Business
Intelligence
11
listeners.
2.
Must
be
highly
compressed
3.
Must
have
a
hero
–
the
story
must
be
about
a
person
who
accomplished
something
notable
or
noteworthy.
4.
Must
include
a
surprising
element
–
the
story
should
shock
the
listener
out
of
their
complacency.
It
should
shake
up
their
model
of
reality.
5.
Must
stimulate
an
“of
course!”
reaction
–
once
the
surprise
is
delivered,
the
listener
should
see
the
obvious
path
to
the
future.
6.
Must
embody
the
change
process
desired,
be
relatively
recent
and
“pretty
much”
true.
7.
Must
have
a
happy
ending.
In
Stephen
Denning's
words,
"When
a
springboard
story
does
its
job,
the
listeners'
minds
race
ahead,
to
imagine
the
further
implications
of
elaborating
the
same
idea
in
different
contexts,
more
intimately
known
to
the
listeners.
In
this
way,
through
extrapolation
from
the
narrative,
the
re-­‐creation
of
the
change
idea
can
be
successfully
brought
to
birth,
with
the
concept
of
it
planted
in
listeners'
minds,
not
as
a
vague,
abstract
inert
thing,
but
an
idea
that
is
pulsing,
kicking,
breathing,
exciting
-­‐
and
alive.”
That
may
be
a
little
too
much
excitement
on
a
daily
basis,
something
you
save
for
the
really
important
things,
but
it
matters
nonetheless
that
turning
data
into
a
story
is
a
valid
and
necessary
skill.
But
is
it
for
everyone?
Not
really.
Actual
storytelling
is
a
craft.
Not
everyone
knows
how
to
do
it
or
can
even
learn
it.
But
everyone
can
tell
a
story.
It
just
may
not
be
of
the
caliber
of
storytelling.
But
to
get
a
point
across
and
have
it
stick
(even
if
it’s
just
in
your
own
mind,
not
to
an
audience),
learn
to
apply
metaphor.
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14. Storytelling
Drives
Usefulness
in
Business
Intelligence
12
Metaphor
Metaphor
is
our
most
powerful
tool
for
conveying
information.
While
a
tabular
report
may
be
a
representation
of
data
and
derivations,
visualization
is
a
metaphor.
It
is
so
much
easier
to
see
and
understand.
Comparative
volume,
gradients
of
color
or
depth
represent
a
continuum
of
values.
Lines
going
up
mean
“up,’
and
lines
going
down
mean
“down”
No
need
to
scan
a
range
of
values
to
decipher
the
direction.
Metaphor
and
analogy
are
often
used
interchangeably,
but
an
analogy
is
more
concrete
and
detailed,
with
the
two
things
being
compared
having
obvious
similarities,
while
metaphor
is
more
literary,
with
the
two
things
being
further
apart.
For
example,
comparing
the
way
protons
and
neurons
move
around
the
nucleus
in
an
atom
with
our
solar
system
is
an
analogy,
while
using
the
term
black
hole
for
a
very
dense
mass
in
space
from
which
light
cannot
escape
is
metaphorical.
Data
visualization
is
metaphorical.
The
best
most
effective
metaphors
are
ones
that
are
new
and
creative.
To
say
one
is
“sick
as
a
dog”
conveys
very
little.
To
say,
“this
systems
is
as
slow
as
a
rainy
Sunday,”
is
likely
to
convey
a
more
vivid
image.
The
whole
point
of
using
metaphor
in
storytelling
is
to
illustrate,
educate,
convince
and
compel.
Metaphors
can
be
powerful
and
clever
ways
of
communicating
findings.
A
great
deal
of
meaning
can
be
conveyed
in
a
single
phrase
with
a
powerful
metaphor.
Moreover,
developing
and
using
metaphors
can
be
fun,
both
for
the
analyst
and
for
the
listener.
It
is
important,
however,
to
make
sure
that
the
metaphor
serves
the
data
and
not
vice
versa.
The
creative
analyst
who
finds
a
powerful
metaphor
may
be
tempted
to
manipulate
the
data
to
fit
the
metaphor.
In
addition,
because
metaphors
carry
implicit
connotations,
it
is
important
to
make
sure
that
the
data
fit
the
most
prominent
of
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15. Storytelling
Drives
Usefulness
in
Business
Intelligence
13
those
connotations
so
that
what
is
communicated
is
what
the
analyst
wants
to
communicate.
Finally,
one
must
avoid
concretizing
metaphors
and
acting
as
if
the
world
were
really
the
way
the
metaphor
suggests
it
is.
Using
Storytelling
with
Visual
Analysis
Workers
can
develop
intensely
useful
analyses
using
data
visualization
tools
with
a
snappy
in-­‐memory
database,
agnostic
about
the
data
schema
of
the
source
data,
,
and
can
share
them
with
their
colleagues
with
some
stories.
Here
are
a
few
examples:
Market
basket
analysis:
Explaining
a
complicated
analysis
with
results
that
can
be
visualized
in
an
easy-­‐to-­‐understand
way
often
encounters
resistance
because
the
evaluators
do
not
understand
the
technique
underneath.
Some
storytelling
usually
helps:
“I
was
in
Home
Depot
one
day
and
when
I
was
walking
through
the
aisles,
I
wondered,
how
could
they
ever
understand
what
products
customers
looked
at,
or
even
picked
up
and
put
back,
but
didn’t
purchase?
How
could
they
modify
their
merchandising
in
a
way
to
understand
what
products
are
most
often
purchased
together,
or,
even
at
a
short
time
later?
In
fact,
how
could
we
figure
out
how
to
do
something
like
that
here?
We
have
detailed
information
about
customers’
behavior
on
our
website,
we
know
what
they
pick
up
and
purchase
or
not,
or
in
what
sequence
they
do.
We
have
information
about
the
journey
they
take
through
the
aisles
[notice
use
of
metaphor].”
The
application
looks
at
each
item
purchased
and
determines
a
list
of
complementary
items
to
recommend
to
purchasers.
The
market
basket
application
uncovered
insightful
new
data
about
the
items
that
customers
typically
purchase
together,
enabling
one
organization
to
present
these
items
as
complementary
offerings
to
online
customers.
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16. 14
Storytelling
Drives
Usefulness
in
Business
Intelligence
Figure
1:
Heat
map
to
visualize
market
basket
analysis
“We
did
some
A/B
testing
in
the
way
we
arranged
things,
and,
as
a
result,
the
average
order
size
for
orders
with
the
market
basket
pairings
is
more
than
twice
the
average
order
size
for
orders
without
pairings.
In
addition,
the
information
has
helped
this
company
better
serve
its
customers,
with
a
deeper
understanding
of
purchasing
preferences.”
Data
never
speaks
for
itself.
As
the
visualization
is
shared
in
a
discussion
format,
there
may
be
stories
about
suggesting
bundles
that
did
or
did
not
work,
or
about
anomalies
in
the
data
that
render
it
misleading.
Further
analysis
and
discussion
continues
until
a
consensus
is
reached.
However,
everyone
involved
will
have
a
mental
picture
of
people
picking
up
products
and
how
things
group
together,
mental
images
that
would
be
lacking
without
storytelling
and
metaphor.
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17. Storytelling
Drives
Usefulness
in
Business
Intelligence
15
Visualization
of
detailed
demographic
data
to
spot
trends
and
correlations:
Understanding
and
analyzing
demographic
data
such
as
age,
income,
and
home
ownership
status
of
millions
of
individual
users
cannot
always
be
done
at
an
aggregate
level.
Specifying
groups
of
individuals
on
the
fly,
based
on
the
detailed
records
allows
for
greater
insight.
In
Figure
2,
it’s
easy
to
see
at
a
glance
that
homeowners
in
the
35-­‐54
range
have
the
highest
balances
and
that
those
with
incomes
above
$150K
lead
the
pack.
Some
of
the
individual
details
of
the
customers
in
that
group
are
also
included
in
the
display.
Some
analyses
are
useful
in
the
way
they
slice
and
dice
information
without
revealing
any
sort
of
causality,
simply
a
rendering
of
what
is.
In
this
example,
it
might
have
been
interesting
to
see
how
the
numbers
break
out,
but
the
storytelling
part
of
it
would
be
focused
on
what
to
do
about
it.
“I
was
having
some
problems
with
my
second
car,
a
pick-­‐up
truck,
that
was
randomly
losing
power.
It
seemed
to
only
affect
the
right
side
of
the
engine.
I
assumed
it
had
to
be
either
a
fuel
problem
or
an
ignition
problem.
I
ruled
out
the
“brain”
because
the
V8
engine
has
two
brains,
one
for
each
side.
I
swapped
those
to
no
effect.
I
checked
fuel
lines,
checked
fuel
pressure,
and
checked
injectors
one
at
a
time.
All
normal.
I
did
the
usual
ignition
check
by
removing
wires
one
at
a
time
and
visually
checking
for
a
spark.
Then
it
occurred
to
me
that
I
was
wasting
time
on
obvious
things
and
had
to
think
out
of
the
box.
What
one
thing
was
most
likely
to
account
for
these
symptoms?
In
the
end,
it
turned
out
to
be
the
sparkplug
wires
themselves.
In
our
marketing
campaigns,
we
seem
to
try
too
many
things
and
focus
and
too
many
market
segments.
What
that
data
shows,
clearly,
is
that
only
one
or
two
segments
are
the
most
likely
to
result
in
sales
and
we
need
to
focus
on
them.”
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18. 16
Storytelling
Drives
Usefulness
in
Business
Intelligence
Figure
2:
Dashboard
profiling
the
age,
income,
market
and
homeownership
status
of
a
financial
institution's
30+
million
401k
holders
Conclusion
Training,
and
to
a
larger
extent,
the
culture
of
the
organization
toward
learning,
is
a
key
indicator
of
BI
success.
Equally
important
is
the
need
to
deliver
tools
in
a
bundle
of
learning
and
cooperation
that
have
a
high
degree
of
relevance
to
the
work
people
do,
something
that
is
often
trivialized
by
Information
Technology,
focusing
on
the
work
of
a
collection
of
individuals,
not
a
collaborative
group.
There
is
much
work
to
do,
but
one
thing
we’ve
learned
from
this
research
is
that
stepping
back
a
little
from
the
technology
of
BI
reveals
a
very
complicated
landscape
strewn
with
hazards.
Many
industry
analysts,
vendors,
journalists
and
practitioners
are
not
well
equipped
for
dealing
with
the
challenges
of
making
BI
successful.
We
need
to
strengthen
our
practice
portfolios
and
partner
with
our
clients
to
implement
programs
that
encompass
technology
and
organizational
development.
Ease
of
use
is
only
a
component
of
ease
of
usefulness
to
the
enterprise.
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2013
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Brains
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19. Storytelling
Drives
Usefulness
in
Business
Intelligence
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2013
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Brains
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17

20. Storytelling
Drives
Usefulness
in
Business
Intelligence
18
ABOUT
THE
AUTHOR
Neil
Raden,
based
in
Santa
Fe,
NM,
is
an
active
consultant,
widely
published
author
and
speaker
and
the
founder
of
Hired
Brains,
Inc.,
http://www.hiredbrains.com.
Hired
Brains
provides
advisory
services,
consulting,
systems
integration
and
implementation
services
in
Data
Warehousing,
Business
Intelligence,
Decision
Automation
and
Advanced
Analytics
for
clients
worldwide.
Hired
Brains
Research
provides
consulting,
market
research,
product
marketing
and
advisory
services
to
the
software
industry.
Neil
was
a
contributing
author
to
one
of
the
first
(1995)
books
on
designing
data
warehouses
and
he
is
more
recently
the
co-­‐author
of
Smart
(Enough)
Systems:
How
to
Deliver
Competitive
Advantage
by
Automating
Hidden
Decisions,
Prentice-­‐Hall,
2007.
He
welcomes
your
comments
at
nraden@hiredbrains.com
or
at
his
blog
at
Competing
on
Decisions.
©
2013
Hired
Brains
Inc.
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Rights
Reserved