From SourceIn New York, Jim Stroud explains why big data is a critical tool for recruiters. Learn more about LinkedIn Talent Solutions for recruitment firms: http://linkd.in/1iTsTH5 Subscribe to the LinkedIn Talent Blog: http://linkd.in/18yp4Cg Follow the LinkedIn Talent Solutions page: http://linkd.in/1cNvIFT Tweet with us: http://bit.ly/HireOnLinkedIn

1. @jimstroud
#SourceIn

2. I was for
big data
before I
was
against
it.

3. RECRUITING
AIN’T EASY

4. RECRUITERS
BE LIKE…

5. And let them have
the right amount of
experience and be
willing to accept the
salary we offer and…
<-­‐-­‐-­‐-­‐-­‐-­‐
Post
and
pray
method.*
*This
method
is
gathering
steam
these
days.
Are
you
hearing
me
recrui8ng
gods?

6. WHY IS
THAT?

7. Umm…
IDK!

8. Just kidding.
;-)

9. 2 Reasons why there is
a lot more posting and
praying these days…

10. #1 TALENT
SHORTAGE
#irony

11. WHY
EMPLOYERS
ARE
HAVING
DIFFICULTY
FILLING
JOBS?
At
a
global
level
hiring
managers
report
that
talent
shortages
are
most
likely
to
reflect
a
lack
of
technical
competencies
or
a
more
general
lack
of
applicants
for
a
par8cular
post,
as
was
the
case
in
2012

12. “…the
United
States
ranks
near
the
middle
in
literacy
and
near
the
boGom
in
skills
with
numbers
and
technology.”
Yikes

13. "The
Northern
hemisphere
faces
talent
shortages
in
a
wide
range
of
occupa8onal
clusters
largely
because
popula8ons
are
ageing
rapidly
and
educa8onal
standards
are
insufficient.
"The
United
States,
for
example,
will
need
to
add
more
than
25
million
workers
to
its
talent
base
by
2030
to
sustain
economic
growth,
while
Western
Europe
will
need
more
than
45
million.
In
Germany,
according
to
a
recent
assessment,
70%
of
employers
are
hard-­‐pressed
to
find
the
right
people."
The
skills
deficit
is
exacerbated
by
the
fact
that
baby
boomers
will
be
reTring
and
young
people
are
not
pursuing
the
professional
skills
the
world
will
need.
People
skilled
in
professional
posi8ons
such
as
doctors,
scien8sts,
technicians,
health
care
professionals,
IT
professionals,
computer
scien8sts,
global
managers,
and
skilled
trades
such
as
plumbing
will
be
high
in
demand
but
severe
shortages
are
an8cipated.
Yikes!
(Again)

14. #2 Retention
issues
#headache

15. August
2012

16. Are
you
showing
your
people
love?
January
2014

17. May
2014

18. Are you feeling the pain of
this staffing storm?
Survey says…
Yes.

19. Job
saTsfacTon
among
recruiters
and
leaders
is
not
especially
high.
Most
respondents,
including
hiring
managers
and
company
execuTves,
believe
jobs
are
at
least
as
hard
to
fill
this
year
as
in
2013,
and,
by
large
percentages,
believe
filling
jobs
will
be
even
harder
next
year.

20. So what are
companies
doing about it?

21. Umm…
IDK!

22. Just kidding.
;-)

23. BIG
Boo-­‐yah!
This is how the war for talent will be won.
DATA
BABY!Boo-­‐yah!

24. Data is the future. Data is now.

25. So, what is big
data?

26. Paul
F.
and
Warren
S.
Miller
Professor
of
Economics;
Professor
of
Finance
and
Sta8s8cs;
and
Co-­‐Director,
Financial
Ins8tu8ons
Center,
University
of
Pennsylvania
“Big
Data
refers
to
the
explosion
in
the
quanTty
(and
someTmes,
quality)
of
available
and
potenTally
relevant
data,
largely
the
result
of
recent
and
unprecedented
advancements
in
data
recording
and
storage
technology.”
–
July,
2000
OFFICIAL DEFINITION

27. My definition…
“Big Data is a
whole bunch of
information.“

28. Of
course,
all
the
data
in
the
world
means
nothing
if
you
can’t
make
sense
of
it
all.

29. Some
companies are
masters of big
data!

30. Did
you
know
this?!
(A
clever
use
of
big
data.)
Based
on
big
data,
Target
can
assign
a
“pregnancy
predic8on”
score.

32. Early Weather Warnings
Understanding traffic patterns with GPS data
Predicting 2nd Heart Attacks with EKG data
Detecting credit card fraud
Decoding human genome

33. Do
you
see
it
now?
We
are
meant
to
be
together.
Shut
up
and
kiss
me.
Big Data
HR

35. G o o g l e ’ s
W o r k f o r c e
Predic8on
Algorithm
was
ambi8ous
and
controversial.
2009

36. Now
Google
has
a
“People
AnalyTcs”
department
made
up
of
data
miners,
psychologists
and
MBAs.
-­‐Kathryn
Dekas,
Manager,
People
Analy8cs
Team
at
Google

37. PROJECT
OXYGEN
Google
figured
out
the
traits
of
good
and
bad
bosses.
They
used
that
data
to
improve
the
work
performance
of
struggling
managers
by
75%.

38. The
People
Analy8cs
team
was
also
helpful
in
dispelling
myths.
Namely,
employees
believed
that
when
you
worked
at
Google’s
headquarters
you
were
promoted
more
quickly
than
those
in
other
Google
offices,
or
the
Googlers
who
worked
on
“shiny
projects”
were
more
likely
to
be
promoted
than
those
who
were
just
regularly
working
on
the
day
to
day
opera8ons.
The
data
showed
that
neither
of
these
hypotheses
was
actually
true,
but
the
analysis
did
reveal
that
geing
feedback
from
senior
peers
was
the
most
important
factor
if
you
wanted
to
be
promoted
within
Google.

39. Think
is the only one
doing this?

40. Luxoica
Group
used
data
analy8cs
to
disprove
assump8ons
about
the
company's
recrui8ng
strategy.
Data
showed
that
it
took
on
average
96
days
to
fill
a
posi8on
with
an
external
candidate.
The
management
team
believed
that
the
company's
recruiters
acted
too
slow,
but
a
sta8s8cal
analysis
found
that
the
hiring
managers
dragged
their
feet
about
making
decisions
about
who
to
hire.
Aner
making
a
few
tweaks
they
went
from
96
days
to
fill
a
posiTon
to
46
days.

41. Capital
One
creates
automated
data
reports
on
employee
aGri8on,
headcount
and
promo8ons.
Its
also
beginning
to
analyze
the
characterisTcs
of
its
most
successful
employees,
like
what
schools
they
went
to
and
what
their
majors
were.

42. By
keeping
track
of
the
saTsfacTon
levels
of
delivery
associates,
a
company
called
Sysco
improved
their
retenTon
rate
from
65%
to
85%,
saving
nearly
$50
million
in
hiring
and
training
costs.
Very
impressive.

43. BIG DATA
IS COOL!

44. Umm…
Wait a sec’…
But,
I
kept
reading.

45. Tracking
collar

47. Cubist
PharmaceuTcals
• Sensor
data
tracked
movement
and
voice
tones.
• Merged
sensor
data
with
email
traffic-­‐data
and
weekly
surveys
on
how
produc8ve
employees
felt.
End
result?
• More
face
to
face
interac8on
equals
higher
produc8vity.
• Company
revamped
cafeteria
to
improve
group
interac8on.
Produc8vity
improved.

48. Just
in
case
you
want
to
check
your
office
chair
when
you
get
back.
This
is
a
mo8on
sensor
designed
by
a
company
called
–
Herman
Miller.
(www.hermanmiller.com)
Just
FYI…

49. BIG DATA
IS scary? Maybe
I
should
stop
reading?

55. All very interesting,
but what has that
have to do with HR
today?

57. Two things to worry
about when it comes
to recruiting and big
data!
Just
in
case
you
needed
more
to
think
about.

58. #1 Unintended
Consequences
#irony

60. #2 More
Government
Regulation

61. • Advance
a
consumer
privacy
bill
of
rights
to
provide
be<er
informa=on
and
standards
for
protec=ng
privacy
• Pass
legisla=on
for
protec=ng
data
from
breaches
• Prevent
discrimina=on
based
on
automated
profiling
of
race
or
other
sensi=ve
characteris=cs
RecommendaTons
that
caught
my
eye

62. So how do I get the benefits of big data while
avoiding the negative consequences?

63. I don’t know.

64. Nobody knows (for
sure) because it’s a
new territory.

65. But I have some suggestions…
• Big data is not good or evil. Its just a tool. Use it.
• Be transparent about the data you are collecting.
• Set clear rules around what it will be used for
• Keep a constant vigil for unintended consequences.

66. Subscribe
to
stay
current
on
this
stuff!

67.
Contact
me:
Jim
Stroud
SR
Director,
RPO
Recrui8ng
Strategies
and
Support
Randstad
Sourceright
Linkedin:
www.linkedin.com/in/jimstroud

68. LINKS
All
the
links
cited
herein
can
be
found
here:
hGp://bitly.com/bigdatababy