This is the keynote presentation I delivered at the 2012 ATC in Sydney, Australia on the topic of the Moneyball opportunity that exists for companies when they are sourcing, identifying, assessing, and recruiting talent. Big Data and predictive analytics are just beginning to be leveraged in talent acquisition, and I am convinced it is the future. I think you will find the examples of how companies are leveraging analytics in their recruitment as well as in the analysis of their current workforce to be quite interesting. You may be shocked to find that data supports the fact that taller and more attractive men and women make more money than their shorter and less attractive peers - which gives us a glimpse into how people make hiring and promotion decisions based on unconscious prejudice, similar to how unconscious prejudice, wisdom, and "gut" instincts are used in athletic recruiting. As demonstrated in Moneyball, the best teams can be sometimes built with data-based decision making, throwing conventional wisdom to the wind.

1. The Moneyball Approach to Recruitment:
Big Data = Big Changes
Glen Cathey
VP, Global Sourcing and Talent Strategy

2. Moneyball
Moneyball: The Art of Winning an Unfair
Game, a book by Michael Lewis about
the Oakland Athletics baseball team, its
general manager Billy Beane and his assistant
Paul DePodesta
Image: http://en.wikipedia.org/wiki/File:Moneyballsbn.jpg

3. Moneyball
The central premise of Moneyball is that the collected wisdom of
baseball insiders (including
players, managers, coaches, scouts, and the front office) over the
past century with regard to player selection is subjective and
often flawed.

4. Moneyball
The Oakland A’s didn’t have the money to buy top
players, so they had to find another way to be
competitive. Source
http://www.flickr.com/photos/leadersevents/5964095428/
Billy and Paul took an
analytical, statistical, sabermetric* approach to
assembling their team, picking players based on
qualities that defied conventional wisdom and the
beliefs of many baseball scouts and executives.
Source
*Sabermetrics is the specialized analysis of baseball through objective evidence, especially baseball statistics that http://www.flickr.com/photos/sheridan/6324889354/
measure in-game activity. The term is derived from the acronym SABR, which stands for the Society for American
Baseball Research.

5. Moneyball
In 2002, with approximately $41
million in salary, the Oakland A’s were
competitive with larger market teams
such as the New York Yankees, who
spent over $125 million in payroll that
same season.
They finished 1st in the American
League West and set an AL record of
20 consecutive wins.
Source: http://en.wikipedia.org/wiki/File:Osmar_Schindler_David_und_Goliath.jpg

6. Moneyball
The Boston Red Sox built their
2004 team with Moneyball in
mind.
They won the World Series in
2004, after failing to do so for
86 years.
Coincidence?
Source: http://www.flickr.com/photos/eggplant/22414700/

7. Moneyball
When sabermetrics was introduced into baseball, it was
immediately rejected by many simply because it was
new, different, leveraged statistics over intuition and
experience, and frequently questioned conventional wisdom with
regard to traditional measures of baseball skill evaluation.
However, today, many MLB teams have full time sabermetric
analysts.

8. Moneyball
"You don't put a team together with a computer."
- Grady Fuson, former Oakland A's Scouting Director

9. Moneyball
Much of what is accepted as sourcing, recruiting, interviewing
and hiring best practices today is largely based upon conventional
wisdom - ideas or explanations that are generally accepted as true.
Conventional wisdom can be a significant obstacle to advancement
because it is often made of ideas that are convenient, appealing
and deeply assumed.

10. Moneyball
"It's human nature to stick with traditional
beliefs, even after they outlast any conceivable
utility"
- Jim Pinkerton, What Comes Next

11. Moneyball
At some point assumptions and traditional beliefs can and should
be violently shaken when they no longer match reality at all.
Some people would call this violent shaking of conventional
wisdom disruptive innovation, and I believe it is coming to talent
acquisition in the form of Moneyball recruiting.

12. Moneyball
What Could Moneyball Recruiting Look Like?

13. Moneyball Recruiting
Moving away from using largely subjective means of assessing
talent and making hiring decisions to more objective, fact and
empirical data-based means.
Identifying and acquiring top talent looking for
traits, experience, accomplishments and information overlooked
by traditional recruiting and assessment methods.

14. Moneyball Recruiting
Challenging conventional wisdom as to what top talent looks like
and where it comes from:
• Specific industry, company, or competitor experience
• ANY prior experience
• Specific universities
• High G.P.A.'s
• Certifications
• M.B.A’s

15. CEO Data
Only 3.9% of American men are 6 feet, 2 inches in height or
taller, yet 30% of all Fortune 500 CEO's are 6 foot 2 or taller.
-Malcolm Gladwell, Blink: The Power of Thinking Without Thinking
The Implicit Association Test (IAT) measures your level of
"unconscious prejudice" - the kind of prejudice that you have that
you aren't aware of, that affects the kinds of impressions and
conclusions that you reach automatically, without thinking.
Source: http://www.gladwell.com/blink/blink_excerpt2.html

16. IAT

17. https://implicit.harvard.edu/implicit/

18. Leadership Height
"No one ever says, dismissively, of a potential CEO candidate that
'he's too short.' This is quite clearly the kind of unconscious
prejudice that the IAT picks up."
"Most of us, in ways that we are not entirely aware
of, automatically associate leadership ability with imposing
physical stature. We have a sense, in our minds, of what a leader
is supposed to look like, and that stereotype is so powerful that
when someone fits it, we simply become blind to other
considerations."
-Malcolm Gladwell, Blink: The Power of Thinking Without Thinking

19. CEO's Only?
When corrected for variables like age and gender and weight, an
inch of height is worth $789 a year in salary. That means that a
person who is six feet tall, but who is otherwise identical to
someone who is five foot five, will make on average $5,525 more
per year.
Timothy Judge, one of the authors of the study, points out: "If you
take this over the course of a 30-year career and compound
it, we're talking about a tall person enjoying literally hundreds of
thousands of dollars of earnings advantage."

20. Australia Too
Tall & Stupid – Meet the CEO
"The average height of an Australian Male in 1995 was measured
at 174.8cm (~ 5ft 9in) by the ABS. I am 174cm (5ft 8in & ½) tall. So
imagine my irritation when I met with the CEO of a major
(AUD$1B in revenue) Australian organisation who was around
188cm (6ft 2")."
Source: http://www.onesock.net/2010/09/meet-the-ceo-tall-stupid/

21. Australia Too
"He followed me around the board room as we
chatted and not only stood to close to me, but
was even leaning over a bit. I realised
afterwards that he was used to using his height
to his advantage, which I thought was a bit
stupid, so I decided to do a bit of research to
make myself feel better."
Source: http://www.onesock.net/2010/09/meet-the-ceo-tall-stupid/

22. Australia Too
Andrew Leigh of Australian National University found that in
Australia, taller people get paid more.
For women, the researchers estimated that another 10 cm of
height is associated with a 2 per cent increase in hourly wages.
This is approximately equivalent to the wage returns from an
additional third of a year of education, or another 4 years of
labour market experience!
Source: http://people.anu.edu.au/andrew.leigh/pdf/BodySize.pdf

23. Attractiveness
In America, a person whose looks are in the top third will
earn around 5% more, on average, than a person
who, except for facial beauty, is otherwise exactly the
same, even on seemingly related factors, such as self-
esteem.
Beauty Pays: Why Attractive People are More Successful
Daniel S. Hamermesh
Source: http://hbr.org/2011/10/hot-or-not/ar/1

24. Attractiveness
By Hamermesh’s calculation, the difference in the
earnings of someone good-looking versus someone
bad-looking might be $230,000 over a lifetime.
His conclusion: The role of beauty in labor markets is
pervasive.
Beauty Pays: Why Attractive People are More Successful
Daniel S. Hamermesh
Source: http://hbr.org/2011/10/hot-or-not/ar/1

25. Back to Moneyball
Explore objective measurements that are relevant across any
role, responsibility, company, and industry
Imagine a score that can stick with each person as they move
through their career, similar to a credit score…

26. Identified.com
If you think a score that can stick with each person as they move
through their career is far fetched and an impossibility, Identified.com
(funded in part by Google CEO Eric Schmidt, by the way) has already
tried to come up with a numerical score for individuals based on work
history, education history, and social network.

27. Identified.com

28. Identified.com
It has some serious flaws (how companies and universities are
weighted and ranked, how someone with more than 1 job can be
ranked higher than someone who has only worked at 1
employer, etc.) but it shows that there is already a movement to try
and represent and rank people based on a single numerical score, and
Identified.com won’t be the only foray into that space. I believe that
there is a significant opportunity for companies to develop their own
data-based and statistically driven talent identification and acquisition
models.

29. Intelligence
While conventional, when it comes to hiring, the single factor
that’s the best predictor of performance across all jobs is not
personality, not interview performance, not prior work
experience, but intelligence.
Source: http://www.downtothehire.com/moneyball-or-moneyhire-hire-on-intelligence/

30. Intelligence
If you were just to select candidates based on intelligence, 65% of
the time, you’d be selecting the top performing candidate out of
your pool of applicants.
Source: http://www.downtothehire.com/moneyball-or-moneyhire-hire-on-intelligence/

31. How Good is Intelligence?
"When performance is measured objectively using carefully
constructed work sample tests (samples of actual job tasks), the
correlation (validity) with intelligence measures is about .84 – 84%
as large as the maximum possible value of 1.00, which represents
perfect prediction."
Handbook of Principles of Organizational Behavior:
Indispensable Knowledge for Evidence-Based Management
"Select on Intelligence" by Frank L. Schmidt

32. Intelligence
This isn't just IT people – it's steel
workers and police officers too!
Despite beliefs to the contrary, hiring on
job experience is inferior to hiring on
General Mental Ability (GMA).

33. Procter & Gamble
P&G, a company with 130,000 employees in 80 countries, uses an
online, unsupervised cognitive assessment involving pattern
recognition to determine GMA. Using pattern recognition is
brilliant because it doesn't require any translation cost.
P&G found this to be the strongest prediction of performance
available from a single test, developed and calibrated with
180,000 people and validated with 2000 employees.
Source: Procter & Gamble

34. Data and Analytics
Is anyone using data and
analytics heavily in their
recruiting efforts?

35. Google
"All people decisions at Google are based on data and analytics,"
-Kathryn Dekas, a manager in Google’s "people analytics" team
This includes compensation, talent management, hiring and all
other HR decisions. Some would argue that Google’s data-based
HR may become a key factor in the company’s future success.
Source: http://venturebeat.com/2011/09/20/people-analytics-google-hr/

36. Capital One has automated data reports on employee
attrition, headcount and promotions and is beginning to analyze
the characteristics of its most successful employees, like what
schools they went to and what their majors were.
"Now we’re going back through resumes and creating a lot of that
data."
- Mark Williams
Statistical Analysis Manager for Workforce Analytics at Capital One
Source: http://it-jobs.fins.com/Articles/SBB0001424052702304444604577342260799623438/Moneyball-and-the-HR-Department

37. Their time to fill for external candidates was an average of 96
days, and management assumed the recruiting team was at fault.
Statistical analysis found that the real cause was hiring managers
dragging their feet about making decisions about who to hire.
They have since reduced their time to fill to 46 days.
Source: http://venturebeat.com/2011/09/20/people-analytics-google-hr/

38. Luxottica also uses analytics to determine if they are promoting
their best employees.
"Are we actually moving high potential people?" "Why is this
person [who rates highly] in the way we evaluate talent in the
same job they were four years ago?"
- Sean Dineen
VP of Talent Management and Organizational Development
Source: http://venturebeat.com/2011/09/20/people-analytics-google-hr/

39. CompanMoneyball Recruiting
Companies will break away from the idea
that the only way to hire great people is to
“buy” and poach them from competitors or
specific companies (look at how incestuous
Facebook, Google, LinkedIn, Microsoft, Appl
e and Yahoo are with regard to their talent
pool)
Companies will develop "secret sauces" for
sourcing, analyzing and evaluating potential
hires based on their own data and factual
statistical analysis of the makeup of their
ideal hire and employee
Source: http://www.allfacebook.com/infographic-facebook-winning-war-for-best-talent-2011-06

40. Moneyball Recruiting
Pay top dollar for an already highly paid industry retread?
Develop and use a structured and proven data and fact-based
methodology for identifying the next superstar from a non-
obvious company out or straight out of school?

41. Moneyball Recruiting
What do all of these people have in common?
• Steve Jobs
• Bill Gates
• Mark Zuckerberg
• Michael Dell
• Sean Parker*
*Napster, Plaxo, Facebook, & Spotify ring a bell? He was making $80K/yr in high school & was recruited by the CIA

42. Moneyball
What if you could leverage data to identify the potential in people
before they were 18, regardless if they were on a path to college
or not?
How many brilliant, high-potential people could be given the right
opportunity to fully realize their potential, regardless of whether
or not they were born into the right family, in the right place, at
the right time, and the stars aligned for them to be able to attend
a prestigious university, let alone any college?

43. Moneyball
Does the technology exist?
Companies already spend millions on business intelligence
software for marketing, product development, sentiment
analysis, healthcare, etc.
Why don't companies similarly invest in human capital analytics?

44. “What if you could increase revenue by 66% using your
data to make confident, fact-based decisions?”
Source: SAS ad

45. “What if you could increase revenue by 66% using human
capital data to make confident, fact-based recruiting and
hiring decisions?”
Source: SAS ad

46. Big Data
Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/

47. Big Data
Wikipedia claims that "Big data is a term
applied to data sets whose size is beyond
the ability of commonly used software tools
to capture, manage, and process the data
within a tolerable elapsed time."
"Big data sizes are a constantly moving
target currently ranging from a few dozen
terabytes to many petabytes of data in a
2.5 exabytes (quintillion bytes) of data
single data set.” are being generated every day

48. Big Data
Other sources attempting to define big data include "the
tools, processes and procedures allowing an organization to
create, manipulate, and manage very large data sets…"
Regardless of definition, the big data concept centers around huge
amounts of data that are not only increasing in volume, but also in
velocity and variety.

49. Data Volume
Source: Mashable - http://mashable.com/2012/03/06/one-day-internet-data-traffic/

50. Data Velocity
The data velocity aspect is the speed at which new data is
generated. One example of the increasing velocity of human
capital data would be social media posts/updates.
For example, Twitter crossed the 340,000,000 tweets/day mark
on March 21, 2012 - that’s 1 billion tweets every 3 days!

51. Data Variety
Human Capital Data:
• ATS CV's
• LinkedIn, Facebook, Twitter, Google+, etc. profiles and updates
• Youtube, Quora, Flickr, Github, Stack Overflow, etc.
• Mobile check-ins and updates
• Recommendations/awards/endorsements
• Blog posts and comments
• Press releases/announcements
• and much, much more!

52. The Big Deal
"The amount of data in our world has been exploding and
analyzing large data sets—so-called big data—will become a key
basis of competition, underpinning new waves of productivity
growth, innovation, and consumer surplus…"
- The McKinsey Global Institute
Big data: The next frontier for innovation,
competition, and productivity

53. The Big Deal
"From the standpoint of competitiveness and the potential
capture of value, all companies need to take big data seriously. In
most industries, established competitors and new entrants alike
will leverage data-driven strategies to innovate, compete, and
capture value from deep and up to real time information.
Indeed, we found early examples of such use of data in every
sector we examined."
The McKinsey Global Institute
Big data: The next frontier for innovation,
competition, and productivity

54. How Powerful is Big Data?
"Make no mistake: Big Data is the new definitive source of
competitive advantage across all industries. Enterprises and
technology vendors that dismiss Big Data as a passing fad do so at
their peril and, in our opinion, will soon find themselves struggling
to keep up with more forward-thinking rivals."
- Big Data Manifesto,
Wikibon*
*Wikibon is a professional community solving technology and business problems through an open source sharing of free advisory knowledge.

55. Big Data Potential
Big Data isn't a new concept – just new to HR
Forbes estimates big data to be a $50B market in 5 years!
Big Data is more than an I.T. play - the majority of the 2011 big
data-related revenues came from services (44%), followed by
hardware (35%), and then software (21%).

56. How Powerful is Big Data?
Catalina Marketing is in the coupon and promotions business, and
they can deliver real-time insights in less than a second of a retail
transaction.
Their primary database holds more than 2.5 petabytes (1015) of
information and adds data on more than 300 million retail
transactions per week.

57. How Powerful is Big Data?
"When you check out with a loyalty card at any one of 50,000
grocery, drug, or mass-merchandise retail stores in the
U.S., Europe, and Japan (and in many stores, more than 90% of
customers use loyalty cards), insight derived from Catalina's
database triggers promotions and offers based on your past
purchases. The coupons stream out of Catalina's point-of-sale
printers at every checkout lane and are handed to customers
along with their receipts within seconds of the transactions."
Source: http://www.informationweek.com/global-cio/interviews/catalina-marketing-aims-for-the-cutting/231600833

58. How Powerful is Big Data?
Target figured out that there are about 25 products that, when
analyzed together, allow them to assign each shopper a
"pregnancy prediction" score.
They can even estimate a due date to within a small window, so
Target can send coupons timed to very specific stages of
pregnancy.
Source: http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

59. How Powerful is Big Data?
An angry man went into a Target outside of Minneapolis,
demanding to talk to a manager:
"My daughter got this in the mail!" he said. "She’s still in
high school, and you’re sending her coupons for baby
clothes and cribs? Are you trying to encourage her to get
pregnant?"
Source: http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

60. How Powerful is Big Data?
After the manager apologized in person and
then called a few days later to apologize
again, the father admitted:
"I had a talk with my daughter," he said.
"It turns out there’s been some activities
in my house I haven’t been completely
aware of. She’s due in August. I owe you
an apology."
Image: http://www.flickr.com/photos/craigmdennis/3027962567
Source: http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/

61. Moneyball Recruiting
"You don't put a team together with a computer."
- Grady Fuson, former Oakland A's Scouting Director

62. Yes, You Do.
Salesforce.com wanted to hire top
sales people from Oracle, so what did
they do?

63. Oh, the things people tweet
Salesforce.com was able to identify 83 of Oracle's top sales people
based on social data, including people tweeting about attending
Oracle's annual president's club trip to Hawaii.
They identified one person because their spouse tweeted several
times about the president's club trip – evening using the event
and company hashtags
While Salesforce used their own Radian6 tool to accomplish
this, any company can accomplish mush the same thing with
Hootsuite

64. How Powerful is Big Data?
Salesforce.com also generates "derived intelligence" from the
data they collect, and they can predict whether someone is loyal
to their current employer or non-loyal and thus more likely to be
"recruitable"
They leverage data in the form of employment status
changes, social network updates, relationship status updates
(yes, divorce can render someone more recruitable), poor
company earnings releases/stock performance, commute
length, company re-orgs, and even weather dissatisfaction!

65. The Big Data Deal
The dig deal about big data is that data can be used to make
better decisions.
While McKinsey found that some companies are using data
collection and analysis to make better management
decisions, there is a huge opportunity to collect and analyze
human capital data, specifically to make better hiring decisions - to
gain a holistic advantage over competitors by
finding, identifying, and enabling the recruitment of top talent.

66. Source: Karmasphere

67. Social Data Aggregation and Disambiguation
The Social CV and TalentBin are two brilliant examples of social
data aggregation and disambiguation solutions. You can use either
to search for and find people they've indexed across multiple
social channels and internet sources.
Each can determine the difference between people with the same
name, and for each person, you can see and gain access to their
social and online presence
(LinkedIn, Facebook, Twitter, Blogs, StackOverflow, YouTube, Quor
a, Meetup, Github, etc.)

68. TalentBin

69. TalentBin

70. SocialCV

71. Geologists and Geophysicists Too!

72. Data Science
The sourcers of tomorrow will be
human capital data scientists
Data scientist = the hottest job you
haven't heard of
Source: http://www.dataists.com/2010/09/the-data-science-venn-diagram/

73. Data Science
Data scientists are an integral part of competitive intelligence.
Ken Garrison, CEO of the industry group Strategic and Competitive
Intelligence Professionals (SCIP), explains, "The field involves
collecting data, analyzing it and delivering the data as intelligence
that is actionable," giving businesses a competitive edge.

74. Human Capital
The future belongs to the companies who figure out how to
collect and use human capital data successfully.
That’s because the companies that can consistently hire great
people, through identifying people and basing hiring decisions on
data and not intuition and conventional wisdom, are more likely
to develop the best teams.
And the best teams win.

75. Moneyball
The old guard in baseball thought that using statistics and
unconventional measures of performance defied everything they
knew about baseball.
They were right.

76. Moneyball Recruiting
If you think the idea of leveraging data and statistics to find and
hire top talent defies everything we know about human resources
and recruiting, I say you’re right.
I also say it’s a good thing, and that we’re just getting started.

77. The Naïve Question
"If we weren't already doing it this way, is this the
way we would start?"
– Peter Drucker