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From YouTube: C* Summit 2013: Accenture - What Were They Thinking?
Description
Thomas J. Glazier, Senior Big Data Architect at Accenture
Nothing is more frustrating than knowing you may have the right solution to a problem, only to have the rug pulled out from under you and your project gets derailed for unknown reasons or for unclear understanding of your solution. While you may not see your job as being a business champion, the fact is that you can be a powerful force to stop your company from making the wrong choice.
A
A
How
can
advanced,
analytics
platforms,
open
source
technologies
and
strong
alliance
networks
open
up
the
insights
of
so
much
data
and
who
will
do
that
heavy
lifting
the
data?
Scientists
must
also
be
or
work
with
an
analytics
artist,
combining
technique,
talent
and
new
technologies
to
gain
insights
into
business
challenges
and
help.
B
Wow
all
right,
I'm
gonna,
be
talking
about
none
of
that.
Okay
and
I'm
very
pleased
to
hear
that
my
job
is
one
of
the
sexiest
in
the
21st
century.
So
what
I
would
like
to
thank
billy
bosworth
from
datastax
for
inviting
me
to
speak
here
this
morning.
What
he
asked
me
to
speak
about
was
what
happens
when
you
guys
leave
here
and
try
and
go
and
get
these
projects
actually
started
up
in
your
own
companies.
B
Okay,
I've
worked
in
emerging
technologies
in
one
form
or
another,
either
within
enterprises
or
technical
startups
for
the
past
13
years
or
so,
and
it's
always
amazing
to
me,
because
I
always
find
myself
asking
the
question
of
my
executives
at
some
point.
What
were
you
thinking?
Okay,
when
you
made
this
decision?
B
Okay,
so
I'm
gonna
walk
you
through
kind
of
what
they
are
thinking?
Okay,
what
is
happening
on
the
other
side
of
that
door?
Okay,
so
imagine
for
a
second.
You
have
spent
all
of
your
time
effort,
typically
extra
beyond
your
regular
job
duties
and
you
leave
here
and
you
want
to
start
putting
some
emerging
technology
into
place
in
your
company.
It's
solving
a
practical
problem
for
you,
so
you
put
together
an
architecture
diagram.
Okay,
you
have
conversations
with
experts.
You
read
the
blogs,
you
talk
to
the
other
people
within
your
company
and
what
happens?
B
B
Most
of
us,
don't
work
for
charities.
We
understand
that
the
function
of
a
business
is
to
make
money,
so
it
doesn't
make
sense
to
put
projects
online
unless
they
can
be
financially
justified.
So
you
run
through
that
exercise.
How
much
money
will
this
save?
What
are
the
soft
projections?
What
are
the
hard
projections
and
things
like
this?
So
you
work
all
that
out
and
you
come
up
with
that
number
fantastic
we're
halfway
there.
B
Then
you
go
through
the
painful
exercise
and
I
admit
I
don't
like
doing
it
either
of
putting
together
the
project
plan,
all
of
the
various
steps
necessary
to
accomplish
the
task
you're
looking
to
put
together.
What
is
the
staffing
going
to
look
like
how
many
people?
Okay,
do
you
need
which
skill
sets?
Do
you
need,
etc?
You
have
thought
of
everything
and
you
didn't
do
this
in
a
vacuum.
Okay,
you
talk
to
project
managers.
B
You
talk
to
your
corporate
executives
to
some
extent,
you've
talked
to
the
chief
architect,
okay,
you've
had
these
conversations
and
they're
really
excited
about
the
project.
Okay,
so
you
send
it
off
for
formal
approval.
Okay,
you
get
some
feedback
that
hey
some
meetings
are
going
on
we're
talking
about
it.
You
know
things
are
looking
good,
okay,
etc,
and
then
things
go
quiet.
B
Okay,
you
don't
hear
anything
back:
okay,
you're,
given
more
work,
you're
just
continuing
on
and
then
all
of
a
sudden
you
come
back
and
say,
okay.
So
what
is
the
status
of
this?
Okay?
And
somebody
comes
back
to
you.
You
know
24
48
hours
later
and
says
we're
sorry
project
rejected.
Okay.
Now
this
has
happened
to
me
on
way
more
than
one
occasion.
Okay,
if
I
had
a
nickel
every
time,
I
wouldn't
be
standing
here,
okay,
so
the
problem
is
trying
to
understand
what
goes
on
in
this
process.
Okay.
B
So
when
I
was
putting
together
this
proposal,
this
deck,
I
was
thinking
okay,
how
do
I
visualize
frustration
with
business
decisions
enter
the
mandatory
dilbert
cartoon
here?
Okay,
now,
while
we're,
while
you
guys,
are
reading
through
this
to
the
executives
in
the
room,
you
can
take
off
your
scuba
gear.
Okay,
for
now,
we're
gonna
go
snorkeling
a
little
bit
okay,
but
there
is
going
to
be
some
stuff
in
here
for
you,
okay,
now
to
the
executives.
B
B
B
Okay,
enter
mandatory
dilbert
cartoons,
two
and
three
all
right
to
the
corporate
executive
to
anybody
who's
ever
had
this
happen
to
them.
These
are
the
conversations
going
on
in
the
technologist's
head,
okay
to
the
executives
most
of
the
time.
These
conversations
are
not
just
going
on
in
our
heads.
Okay,
we're
actually
having
some
of
these
conversations
with
our
colleagues
around
the
water
cooler
and
certainly
at
the
bar
after
work.
B
Okay,
so
there's
peeling
back
the
curtain
on
the
technologist
for
some
of
the
executives.
Okay,
now
I
can
recall
a
one
particular
time
where
I
had
spent
an
enormous
amount
of
time.
I
mean
three
months
of
extra
time
in
addition
to
my
regular
job
duties,
because
I
was
so
passionate
and
so
sure
that
I
had
the
right
answer
to
one
of
the
biggest
problems
the
company
had.
Okay,
I
spent
a
lot
of
time.
I
had
every
conversation
you
can
think
of.
B
B
I
went
home
and
my
wife's
seeing
that
I
was
really
frustrated.
Okay,
obviously
said
so
what's
wrong
and
I
explained
it
all
to
her
etc
and
towards
the
end
of
the
conversation,
okay,
I
basically
said
something
along
the
lines
of
this:
okay,
benjamin
franklin,
okay,
thomas
edison
and
isaac,
newton
masters
of
emerging
technology
in
their
day.
Okay,
why?
I'm
not
trying
to
invent
electricity?
B
Okay,
I'm
not
creating
1500
new
patents
and
I'm
certainly
not
rewriting
the
rules
of
physics
and
creating
a
whole
new
mathematics
at
the
same
time.
Okay,
all
I'm
trying
to
do
is
solve
this
one
narrow
problem
for
this
one,
narrow
company,
okay,
to
try
and
make
them
just
a
little
bit
more
money.
Okay,
and
she
then
my
by
the
way
my
wife
is
way
smarter
than
I
am
okay
asked.
The
question
said:
why
did
you
pick
those
three
okay?
Why
didn't
you
pick?
B
Somebody
like
galileo
and
I
said
well,
these
three
okay
were
not
imprisoned
for
their
work.
They
were
rather
successful
at
it.
Okay!
Well,
she
said
well,
it's
interesting
that
you
picked
those
three.
I
said.
Why
is
that?
And
she
said
you
know,
she's
a
little
bit
of
student
history
and
she
said
because
they're
also
known
for
something
other
than
their
technology.
B
Benjamin
franklin
was
a
diplomat.
He
was
the
us's
first
ambassador
to
france.
Okay,
thomas
edison
was
a
highly
successful
businessman:
okay,
licensing
those
1500
patents
to
all
sorts
of
companies
and
isaac
newton.
He
was
a
statesman.
He
was
the
head
of
the
royal
society
royal
academy
of
sciences
and
the
royal
mint
okay
and
saw
and
debated
and
settled
some
of
the
most
controversial
scientific
issues
of
his
day.
Okay-
and
I
said
you
know
me
still
being
completely
frustrated-
said
what
the
heck
does
that
matter.
Okay,
I
don't
care
what
else
they
did.
B
They
solved
the
technology
problem,
and
so
am
I
that's
all
I'm
doing.
Okay
and
she
said
okay,
so
look
at
it.
This
way.
Are
you
wrong?
Okay,
and
I
you
know,
had
to
think
about
that
quite
a
bit,
nice.
You
know
knowing
all
of
the
work
that
I
put
into
it
all
three
months:
okay,
everything
that
I
know
the
training
etc.
B
B
B
B
Okay,
all
right,
so
technologists
are
trained
to
solve
a
problem.
Okay,
people
with
some
experience
see
the
world
as
black
white
in
a
small
area
of
gray,
okay,
but
in
general,
when
we're
sitting
there
programming
something
or
making
a
technical
decision,
it's
either
approach
a
or
approach
b,
okay,
so
software
engineers
typically
have
that
type
of
decision.
B
Okay,
given
all
the
information
that
I
have,
should
I
go
with
technical
approach,
a
or
b,
it's
quite
frankly,
a
very
simple
question
to
answer
now:
people
when
you
move
up
the
ladder-
and
you
start-
you
know,
managing
other
people
and
have
more
project
responsibilities
and
things
like
this.
The
question
changes
a
little
bit.
Okay,
project
managers
and
dev
leads
okay,
given
all
of
the
information
that
I
have,
okay,
there's
a
50
chance
team
a
will
hit
their
deadline.
Therefore,
I
can
accommodate
this
request
for
more
time
from
team
b.
B
Okay,
the
top
one
for
software
engineers.
It
is
a
pure
decision.
Okay,
a
or
b
the
bottom.
One
is
a
gamble;
let's
call
it
for
what
it
is.
It
is
a
gamble.
Okay,
I
am
betting
that
this
fact
will
come
true,
so
I
can
make
this
other
decision
in
choice.
Okay,
unfortunately,
executives
have
a
much
harder
problem.
Okay,
when
you
move
up
in
the
chain
and
you
move
up
in
the
ladder,
there's
a
much
more
compelling
question-
they
don't
have
a
decision,
they
don't
have
a
gamble.
B
They
have
a
decision
to
gamble
the
previous
two
decisions.
It
is
an
a
or
b
okay.
The
executives
have
a
third
choice:
okay,
go
with
something
new,
okay
or
don't
do
anything
at
all
the
software
engineer.
Writing
the
code
doesn't
have
a
choice.
He
needs
to
get
it
to
work.
He
either
uses
approach
a
or
approach
b
to
get
there.
Project
manager
has
to
deliver
the
project
and
make
a
decision.
A
or
b
project
manager
doesn't
have
the
choice
to
not
make
a
decision.
B
Okay,
the
executive
does
have
that
choice,
believe
it
or
not,
there's
already
something
there
there's
already
something
existing.
Let's
use
it.
Let's
continue
to
use
it,
so
that's
the
choice
that
they
have,
and
it's
typically
framed
something
like
this.
Given
all
the
information
that
I
have
would
I
accept
a
gamble
that
offers
a
specific
chance
to
gain
x
and
a
chance
to
lose
y.
B
B
B
Who
would
not?
Okay,
this
room
is
a
little
bit
different.
Okay,
a
slight
majority
said
that
they
would
not
accept
this
gamble.
Okay,
so
we'll
come
back
to
that
in
just
a
minute,
but
because
of
this
okay
executives
seek
what's
called
the
outside
view.
All
right.
We've
all
heard
those
stories
of
crazy
budget
overruns.
For
example,
in
1997
the
city
of
edinburgh
commissioned
a
company
to
build
them
a
new
government
building.
They
came
in
with
a
cost
projection
of
195
million
pounds.
Okay,
three
years
later,
they
they
capped
the
cost
at
195
million
pounds.
B
Okay,
two
years
after
that,
they
asked
for
a
final
cost
estimate
and
got
it
back
at
341
million
pounds
in
2007
the
project
completed
at
a
total
cost
of
491
million
pounds,
okay
120
to
491
million
pounds.
Okay,
that's
almost
a
five-fold
increase,
there's
not
an
executive
on
this
planet
that
wants
to
be
in
charge
of
that
type
of
project.
B
B
A
study
conducted
in
2005
showed
that
they
analyzed
railroad
projects,
but
they
were
conducted
between
1969
and
1998
and
what
they
found
is
in
over
90
percent
of
those
cases,
people
overestimated
the
number
of
writers
on
the
train
system,
sometimes
as
grossly
as
107
percent.
That's
not
as
interesting
as
over
30
years.
In
other
words,
nobody
learned
the
lesson.
B
Okay
of
doing
this.
Okay,
now
one
other
interesting
thing
to
make
it
a
bit
more
real
2008,
a
survey
was
conducted
and
the
average
homeowner
expected
that
a
kitchen
renovation
would
cost
about
18
thousand
dollars
to
anyone
who's
actually
done
it.
The
next
number
is
not
going
to
be
as
surprising:
it
actually
cost
about
37
000,
okay,
despite
the
millions
of
renovations
that
go
on
each
year,
people
still
grossly
underestimate
that
number.
That's.
B
Why
executives
call
in
what's
called
the
outside
view
to
technologists
in
the
room
understand
what
the
outside
view
is
and
the
materials
that
your
executives
are
reading,
harvard
business
review,
cio
magazine
case
studies
and
reports
coming
from
mckinsey,
ibm,
accenture,
etc?
They
are
seeking
this,
these
facts
and
information.
If
you
don't
understand
what
they're
looking
at,
how
can
you
propose
a
project
to
them
all
right?
So
here's
some
facts,
the
outside
view.
Okay
and
I
intentionally-
did
not
use
any
accenture
reports,
so
you
didn't
think
I
could
be
biased
on
this
or
make
it
up.
B
Okay,
ibm
only
forty
percent
of
projects
meet
schedule,
budget
and
quality
goals.
European
services
agency
reports,
average
cost
overrun-
is
30.5
percent
mckinsey
on
average
large
it
projects
run
45
over
budget
7
over
time,
while
delivering
56
less
value
than
predicted.
Now
these
facts
really
aren't
news
to
anybody
in
this
room.
Who's
worked
in
this
space
for
any
significant
period
of
time.
Okay,
that
we
all
know
it.
The
problem
is,
is
that
we
don't
actually
factor
it
in
to
what
we
are
proposing
back
to
the
executives.
B
So,
let's
take
a
pretty
hard
look
at
the
gamble.
We
are
asking
the
executives
to
make
okay.
Would
you
accept
a
gamble
that
offers
a
forty
percent
chance
to
gain
forty
four
percent
of
whatever
the
expected
gain
is
on
this
project
and
a
sixty
percent
chance
to
lose
the
entire
project
budget
plus
30
to
45
percent?
On
top
of
that,
plus,
all
of
the
expected
gain
in
the
event
that
the
project
is
cancelled,
oh
and
by
the
way,
it'll
be
seven
percent
late.
B
All
right
seriously,
would
you
guys
accept
this
gamble
with
your
money?
Not
a
single
person
in
here
would
I'm
sure
of
it,
but
that
is
exactly
what
you're
asking
the
executives
to
do.
Okay,
when
you
consider
the
outside
view
and
guys,
these
numbers
are
for
established
projects
using
established
technologies.
B
Yeah,
the
gamble
does
not
get
any
better.
Okay,
all
right.
So
one
of
the
other
problems
that
you're
going
to
run
into
is
this
expected
gain
portion
of
it.
Okay,
that
is
a
hotly
debated
issue
within
these
okay.
Exactly
what
gain
am
I
going
to
be
getting
out
of
it?
Well,
I
don't
think
it's
quite
that
much.
I
think
it's
going
to
be
more
here.
Soft
gain,
hard
gain,
etc.
Okay,
so
what
we
come
up
to
is
another
problem
called
the
endowment
effect
and
everybody
here
has
has
done
this.
B
B
Do
you
sell
the
tickets?
Okay
yeah?
So
a
lot
of
people
sitting
here
in
this
room
are
saying:
yeah,
no
problem
that
big
a
gain,
no
issues,
guess
what
most
people
do
not
sell.
This
is
an
established
fact.
Okay,
psychological
studies
have
shown
this
over
the
course
of
the
past
30
years.
Okay,
and
that
is
odd.
Okay,
economists
don't
understand
that
the
fact
the
establishment
of
this
is
a
fact.
B
Okay,
daniel
kahneman
and
amos
traverskey
received
the
nobel
prize
in
economics
for
establishing
this
fact
and
the
reason
why
one
of
the
reasons
is
because
these
are
goods
for
use,
not
exchange.
Okay.
What
does
that
actually
look
like
if
one
of
you
was
come
up
to
me
and
asked
me
to
change
a
five
dollar
bill
for
five
ones?
I
do
it
without
thinking,
okay,
because
that's
an
expected
function
of
that
items.
Okay,
I
don't
expect
that
I
would
sell
these
tickets
because
I
intend
to
use
them
not
exchange
them
for
something
else.
B
So
here's
the
decision
that
again
you're
asking
somebody
to
make
a
little
while
ago
a
system
was
put
online
and
has
been
working
effectively
for
its
original
purposes.
Okay,
granted
there
are
some
problems
with
it.
What
system
doesn't
have
it
for
a
number
of
reasons,
it's
time
to
put
a
new
system
online?
B
No,
it
is
not
enough,
and
this
is
due
to
the
endowment
effect.
Okay,
the
current
functionality
is
the
buy
price
okay,
but
it
must
do
more.
The
sell
price.
Okay,
if
you
were
willing
to
sell
the
tickets
at
3
000
okay,
then
there
is
some
level
in
between
which
and
somewhere
between
500
and
3
000,
in
which
you
switched
from
I'm
not
willing
to
sell
it
to
I'm
willing
to
sell
it,
okay
and
that
price
I'll
guarantee
is
more
than
500.
B
That's
the
same
decision:
okay,
pure
plain
and
simple.
Now
a
note
to
the
executive
so
pop
your
head
up
from
that
snorkeling.
This
effect
percolates
through
the
organization
in
that
it
also
increases
project
risk.
The
technologist
in
the
room
will
tell
you
it
is
hard
enough
to
put
emerging
technologies
online,
especially
when
you
start
throwing
in
well.
It
also
has
to
do
this.
It
also
has
to
do
this
by
the
way.
Can
it
walk
my
dog?
Do
the
dishes,
okay
and
plan
my
hawaiian
vacation
all
at
the
same
time?
B
B
Just
understand
the
more
you
ask
the
larger
the
problem
you're
going
to
have
all
right,
so
the
disposition
effect.
Okay,
here's
another
item-
and
this
happens
when
making
the
decision
of
what
systems
you're
going
to
have
to
replace
and
why?
Okay
now
the
good
thing
about
this
is
to
the
executives
in
the
room.
You
guys
have
heard
of
this
problem
before
under
a
different
name.
Anybody
that
has
formal
training
in
economics,
management
or
an
mba
has
had
this
drilled
into
them.
B
Okay,
but
technologists
haven't
we
went
to
engineering
school,
not
economics,
okay,
so
the
business
guys
in
the
room
know
this
is
the
agency
effect
okay
or
the
agent
problem.
So
among
the
stocks
you
own,
blueberry
tiles
is
a
winner.
If
you
sell
it
now,
there's
a
five
thousand
dollar
game.
Okay,
you
hold
a
total
investment,
an
equal
investment
in
tiffany
motors,
but
if
you
sell
it
right
now,
you
take
a
five
thousand
dollar
loss:
okay,
which
one
are
you
more
likely
to
sell,
you're
likely
to
sell
the
game?
B
B
Okay,
there's
the
problem
with
that.
The
psychological
effect
is
that
is
as
soon
as
you
cash
that
in
and
realize
that
loss.
You
have
a
negative
mark
in
your
mental
bank.
Put
simply
if
you
frame
the
choice
as
one
between
giving
you
pleasure
and
giving
you
pain,
evolution,
says
you're
gonna
pick
the
pleasure.
B
Okay
managers
have
this
drilled
into
them,
because
nothing
loses
more
money
on
wall
street
than
the
agency
effect
guys.
There
are
traders
on
wall
street
who
suffer
from
this,
so
much
okay,
that
they
only
have
winners
about
30
percent
of
the
time.
Okay,
guys
a
dart
throwing
monkey
could
achieve
better
results
than
that.
Just
on
pure
randomness,
okay,
this
is
a
massive
problem
within
organizations.
B
That's
why
it's
drilled
into
executives,
but
technologists,
don't
generally
understand
it
all
right,
so
if
we
make
it
real
into
our
everyday
lives
in
the
technology
organization.
Okay,
this
is
the
scenario
that
you're
asked
with
a
while
ago,
two
different
pieces
of
technology,
where
two
different
pieces
of
technology
were
recommended
and
implemented.
Okay
technology,
a
is
widely
seen
as
a
success.
The
technology
b
has
been
problematic
since
the
beginning
and
is
currently
your
responsibility
to
work
with.
Okay,
you
had
no
direct
impact
on
putting
either
of
these
technologies
online.
Okay,
you're,
an
unbiased
observer.
B
You
do
not
have
a
mental
account
built
up
on
this.
Okay,
so
which
one
are
you
going
to
want
to
replace
technology,
be
easy,
the
guys
who
make
the
decisions
who
made
the
decision
to
put
that
in
line
okay?
Sometimes
the
bosses,
sometimes
somebody
over
another
division.
Somebody
like
this,
they
do
have
a
mental
account
against
that
decision.
B
Who
are
they
going?
Which
one
are
they
going
to
want
to
replace
technology?
A
okay?
It's
actually
believe
it
or
not,
easier
to
replace
the
successful
technology
than
a
problematic
one.
Okay,
that's
kind
of
ironic
all
right
and
then
there's
another
problem
that
we
ask.
Okay,
there's
another
issue,
and
this
is
one
that
I
face
more
often
than
any
of
the
others.
B
B
B
Okay,
now
just
answer
the
question
yourself:
if
you're,
like
most
people,
you
choose
option
two,
the
reason:
why
is
because
option
two
is
a
much
better
story:
it's
not
more
probable!
It's
more
plausible,
okay,
and
if
you
wanna
see
that
these
two
vary
on
one
thing
one
says:
north
america
one
says:
california,
okay,
it's
more
likely
to
have
a
massive
flood
in
a
large
in
a
huge
geographic
area
like
north
america
than
it
is
here
in
just
california,
okay,
guys
this
effect
85
to
90
percent.
B
When
this
test
was
originally
conducted
on
a
similar
question,
85
of
students
at
major
universities,
I'm
talking
harvard
berkeley,
stanford,
etc
failed
to
get
this
right.
Okay,
because
the
story
was
more
plausible:
okay,
but
not
more
probable.
Okay.
So
how
does
this
affect
the
everyday?
Okay,
good
question?
Adding
details
to
scenarios
makes
them
more
plausible
and
persuasive.
B
B
Okay,
just
visually,
the
decision
becomes
pretty
straightforward.
Okay,
I
can
say
the
one
on
the
bottom
right
is
more
likely
to
come
true
because
it
has
far
less
detail
in
it.
Okay,
now
do
you
have
to
fill
in
that
detail
at
some
point?
Absolutely
don't
get
me
wrong.
Okay,
but
when
you're
proposing
a
project,
the
detail
is
not
as
important
as
do
you
have
a
strategy?
B
B
So
how
does
anything
new
happen?
I
mean
we've
got
some
pretty
substantial
hurdles
and
guys
I
have
not
put
in
any
specific
budget
numbers.
I've
not
talked
about
any
specific
technology.
Okay,
I
have
done
nothing
but
give
you
a
general
overview
of
how
people
make
decisions.
Okay,
that's
before
these
are
all
the
problems
you
have
before
you
fill
in
what
you
actually
want
to
do
and
why
okay?
So
how
does
anything
happen?
Okay,
startups
out,
innovate
enterprises
on
a
routine
basis?
Okay,
why?
B
Okay,
their
decision
to
gamble?
They
actually
change
the
question.
Okay,
so
would
you
pay
five
dollars
to
participate
in
a
lottery
that
offers
a
ten
percent
chance
to
win
a
hundred
dollars
and
a
ninety
percent
chance
to
win
nothing?
Okay,
quick
show
of
hands
who
would
participate
in
that
lottery
a
far
sign,
far
better
percentage
of
people
in
the
room.
Guess
what
guys
this
is?
The
previous
gamble,
they're
identical.
B
B
Okay,
now,
the
other
lessons
that
we've
learned
startups
out,
innovate
enterprises
why
there's
no
endowment
effect?
Okay,
there's
nothing
to
compare
against,
so
no
need
to
decide
how
much
functionality
is
enough.
Okay,
no
disposition
effect,
nothing
to
repair
or
replace,
therefore,
no
need
to
acknowledge
failure.
Okay,
there's
no
mental
accounts
on
anybody.
B
Okay,
number:
four:
the
forecasters
trap
is
still
possible.
There
are
plenty
of
startups
okay.
They
come
out
with
these
great
grandiose
visions
and
at
9
00
a.m
and
by
5
p.m.
They
are
completely
thrown
out
the
window.
Okay,
forecasters
trap
is
still
possible,
okay,
but
they
generally
expect
to
be
wrong
and
adapt
quickly.
In
other
words,
they've
developed
that
strategy
on
how
to
do
that.
B
B
So
these
are
the
new
rules
that
we've
kind
of
learned
on
how
to
go
back
after
this
conference,
talk
to
your
executives
and
start
working
through
how
to
create
how
to
get
these
emerging
technologies
into
your
organization
acknowledge
the
decision
to
gamble.
Okay
acknowledge
what
that
is,
but
change
the
question
frame.
It
is
a
cost
to
play.
B
Okay
deciding
how
much
new
functionality
is
enough
is
a
losing
battle.
Okay,
so
don't
try!
Okay,
when
you
include
the
risk.
Okay,
replacing
a
problematic
system
acknowledges
failure,
not
a
winning
approach.
It's
not
a
winning
approach
to
try
and
do
that
trying
to
predict
every
technical
possibility
is
a
fool's
errand.
Okay-
and
god
knows,
I've
been
on
him
more
than
once,
but
a
strategy
and
direction
are
essential
to
success
period.
B
Okay,
so
what
does
an
emerge?
Oh
yes,
this
is
the
one
time
I
put
cassandra
in
here,
because
cassandra
has
another
interesting
challenge
or
problem.
Okay
with
the
enterprise,
I
t
guys.
Okay,
cassandra
and
big
data
technologies
in
general.
Love
bare
metal;
okay,
the
tagline
big
data
loves
bare
metal,
okay,
virtualization
sans
wands.
Things
like
this
are
bad
news:
okay
for
general
big
data
technologies,
the
enterprise
it
guys
have
just
spent
the
past
15
years
virtualizing
and
consolidating
data
centers-
and
here
you
guys,
are
coming
in
and
saying
no.
B
I
want
a
hundred
bear
node
servers.
I
want
them
up
tomorrow
and
by
the
way,
find
it
in
your
budget.
Okay,
they're,
like
not
gonna,
happen.
Okay,
we,
it
is
quite
common
for
people
to
get
so
frustrated
working
with
enterpriseit
that
we
have
had
clients
that
have
said
we
do
not
want
to
go
work
with
them.
We
do
not
want
to
talk
to
them,
don't
even
think
about
it,
but
I
want
all
these
big
data,
tech,
okay,
so
take
these
guys
out
for
a
drink.
B
B
Okay,
something
in
the
cloud
something
small
things
like
this
and
you
build
their
comfort
level
and
confidence
guys.
You
think
the
executives
were
risk
adverse.
You
should
see
enterprise
I.t,
okay,
they're,
the
one
that
get
the
call
at
three
a.m
while
on
vacation
in
a
foreign
country,
because
the
programmer
forgot
to
put
a
period
you
know
forgot
to
put
in
a
semicolon
or
something
like
this,
and
now
their
entire
day
has
gone
to
hell.
Their
wife
is
yelling
at
them.
Their
kids
are
crying.
B
They
are
way
more
risk
adverse
than
the
executives
are
okay,
they
take
a
lot
longer
to
bring
around.
You
have
to
include
them
from
the
beginning
and
you
have
to
let
them
play
around
and
see
what
they're
going
to
be
working
with
telling
them
that
netflix
is
the
largest
implementer
and
google
uses
something
similar.
B
B
B
Those
same
three
guys
understood
that
okay,
bifocal
lenses
didn't
exist
before
benjamin
franklin
existed
them,
but
invented
them
new
capability
and
functionality.
Thomas
edison,
1500,
patents
enough
said
isaac,
newton,
redefined
physics
with
a
brand
new
type
and
invented
a
new
type
of
mathematics
in
the
process.
None
of
these
three
guys
changed
it.
Okay,
they
invented
something
new.
B
If
you're
sitting
in
this
room,
you
are
now
a
member
of
the
fraternity
of
fools.
Welcome
to
the
club,
we
got
do's
and
jackets.
Okay,
a
greater
fool
is
an
economic
term.
Okay,
it
is
somebody
that,
with
the
perfect
blend
of
self-delusion
ego
that
believes
he
can
succeed
where
others
have
failed.
Okay,
most
people
spend
their
lives,
trying
not
to
be
the
greater
fool:
okay,
they're,
a
patsy
okay.
We
run
for
their
chair
when
the
music
stops.