Glen Cathey presents on Moneyball Recruitment

The Moneyball Approach to Recruitment:

Big Data = Big Changes

Glen Cathey VP, Global Sourcing and Talent Strategy

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

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.

Moneyball

The Oakland A’s didn’t have the money to buy top players, so they had to find another way to be competitive. 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.

Moneyball

*Sabermetrics is the specialized analysis of baseball through objective evidence, especially baseball statistics that measure in-game activity. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research.

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.

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?

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.

Moneyball

"You don't put a team together with a computer."

- Grady Fuson, former Oakland A's Scouting Director

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.

Moneyball

"It's human nature to stick with traditional beliefs, even after they outlast any conceivable utility"

- Jim Pinkerton, What Comes Next

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.

Moneyball

What Could Moneyball Recruiting Look Like?

Moneyball

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.

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



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.

CEO Data

IAT

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

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

"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."

Leadership Height

-Malcolm Gladwell, Blink: The Power of Thinking Without Thinking

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."

CEO's Only?

"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")."

Australia Too Tall & Stupid – Meet the CEO

"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."

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!

Australia Too

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

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

Attractiveness

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…

Back to Moneyball

Identified.com

Identified.com

Identified.com

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.

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.

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

How Good is 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).

Intelligence

P&G: 130,000 employees in 80 countries Online, unsupervised cognitive assessments involving pattern recognition – no translation cost! Strongest prediction of performance available from a single test, developed and calibrated with 180,000 people and validated with 2000 employees.

Procter & Gamble

Source: Procter & Gamble

Is anyone using data and analytics heavily in their recruiting efforts?

Data and Analytics

"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.

Google

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: Wall Street Journal

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.


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


Individual 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:allfacebook.com

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?


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

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?

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?

Moneyball

“What if you could increase revenue by 66% using your data to make confident, fact-based decisions?”

Source: SAS ad

“What if you could increase revenue by 66% using human capital data to make confident, fact-based recruiting and

hiring decisions?”

Source: SAS ad

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 single data set.”

Big Data

2.5 exabytes (quintillion bytes) of data are being generated every day

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.

Big Data

Data Volume

Source: Mashable

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!

Data Velocity

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!

Data Variety

"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

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

The Big Deal

"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*

How Powerful is Big Data?

*Wikibon is a professional community solving technology and business problems through an open source sharing of free advisory knowledge.

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%).

Big Data Potential

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.


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.


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: Forbes

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: Forbes

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."


Source: Forbes

"You don't put a team together with a computer."

- Grady Fuson, former Oakland A's Scouting Director


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

Yes, You Do.

Salesforce.com also generates "derived intelligence" from the data they collect They can predict whether someone is loyal to their current employer or non-loyal and thus more likely to be "recruitable" Employment status changes, social network updates, relationship status updates…


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.

The Big Data Deal

Source: Karmasphere

TalentBin

TalentBin

SocialCV

Geologists and Geophysicists Too!

The sourcers of tomorrow will be human capital data scientists Data scientist = the hottest job you haven't heard of

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.

Data Science

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.

Human Capital

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

Moneyball

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.


"If we weren't already doing it this way, is this the way we would start?"

– Peter Drucker

The Naïve Question

Questions?

Glen Cathey presents on Moneyball Recruitment

Business

human capital

top talent

big deal

conventional

talent management

big data

grady fuson

procter amp