Big Data in HR: Insight on the Meaning and the Opportunity

Big Data in HR: Insight on the Meaning and the Opportunity

Donna Quintal Senior Manager of Strategic Sourcing Sears Holdings Corporation

Glen Cathey Vice President, Sourcing and Recruiting Center of Expertise Randstad Sourceright

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Agenda

• The Moneyball phenomenon

• What do we mean by Big Data?

• The Opportunity• Big data in action: Moneyball recruiting• Creating real workforce intelligence

• Wrap up: transforming HR and changing the conversation

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The Meaning

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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

• premise: 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

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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.

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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

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Much of what is accepted as sourcing, recruiting, interviewing and hiring, and talent management best practices today is largely based upon conventional wisdom - ideas or explanations that are generally accepted as true.

However, the problem with any conventional wisdom is though the ideas or explanations are widely held, they are also largely unexamined and untested, and thus not necessarily true.

Moneyball

The Moneyball approach a real opportunity for companies today

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Analyzing massive data sets (30K – 100K employees), Evolv has identified undervalued characteristics and discovered non-intuitive insights, such as: • For hourly workers, people who fill out

online applications with 3rd party browsers (Firefox or Chrome) rather than IE perform better and change jobs less often

• For call center employees, people with a criminal background actually perform a bit better than those who do not, and "job hoppers" are no more likely to quickly quit than those who have stayed in previous jobs for long periods of time

Moneyball

Source: The Economist, Robot Hiringhttp://www.economist.com/news/business/21575820-how-software-helps-firms-hire-workers-more-efficiently-robot-recruiters

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A large financial services firm believed that employees with good grades who came from highly respected universities made good sales performers.

Moneyball

Source: Forbes, Josh Bersinhttp://www.forbes.com/sites/joshbersin/2013/02/17/bigdata-in-human-resources-talent-analytics-comes-of-age/

Sales productivity and turnover analysis was performed for new sales employees over their first 2 years of employment and correlated with total performance and retention against various demographic factors.

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Big Data

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What Big Data Is

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.”

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What Big Data Is

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.

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Data Volume

Source: Mashable

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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 400,000,000 tweets/day mark on March 21, 2013 - that’s 2.8 billion updates every week!

Data Velocity

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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

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Big Data & Analytics

Many people use the term "big data" when they're really referring to analytics.

Big data refers to data sets that are typically high in volume, variety and velocity. A large volume of data doesn't qualify as "big data" unless the other attributes are present – velocity and variety (structured and unstructured).

Analytics is the discovery and communication of meaningful patterns in data, which can be achieved with any data set.

Correlating employee performance and retention data with demographic data or assessments is an example of analytics, but not "big data."

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The Opportunity

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Big Data in Action: How can the Moneyball approach improve your competitive edge in talent acquisition?A few ways we could apply the Moneyball

concept/analogy to talent acquisition:

1. Assessing Talent: Moving away from using largely subjective means of assessing talent and making hiring decisions to more objective, fact and empirical data-based means

2. Out-recruiting Traditional Talent Acquisition: Identifying and acquiring top talent looking for traits, experience, accomplishments and information overlooked by traditional recruiting and assessment methods

3. Looking in New Places: Challenging conventional wisdom of what top talent looks like and where it comes from (Ivy league schools, high G.P.A., certifications, M.B.A’s, experience at certain companies, etc.)

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Big Data in Action: What Could Moneyball Recruiting Look Like?

Talent Competitive Edge (cont’d.):

4. Real Measures of Performance: Developing objective performance measurements that are relevant across any role, responsibility, company, and industry and that stick with each person as they move through their career, similar to a credit score

5. Secret Sauce: Individual companies developing “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

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Can you answer?

How many current employees are retiring in 2013?

How many current employees are under preforming?

What companies provided your top and bottom performers in 2012?

What skills do current incumbents have in common with one another?

What are each managers 360 Leadership scores or rank?

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Moneyball in Action: What data should be shared?

Personnel Data Education Level/School

Outside Work History 360 Leadership Scores Talent Management Mobility Review Scores

Business Results Skills

Influence

ProactivePredictive

Transparency

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Moneyball in Action: Getting the Data

Talent Management Data, HRIS, & ATS

Data Warehouse

Create

ReportingShare

Analytics

MakeDecision

sTake

ActionShow Value

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Gaining Details of Competitive Hires

2.5 & Below Below AVG 3.2 & Above Above AVG Grand Total Total Rank

Competitor #1 10 16.13% 6 9.68% 62 -6.45%

Competitor #2 2 5.00% 16 40.00% 40 35.00%

Competitor #3 6 15.38% 8 20.51% 39 5.13%

Competitor #4 8 24.24% 13 39.39% 33 15.15%

Competitor #5 9 31.03% 11 37.93% 29 6.90%

Competitor #6 2 7.41% 6 22.22% 27 14.81%

Competitor #7 6 23.08% 10 38.46% 26 15.38%*Example Only Data Invalid

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Example of Skills and Competencies by Position

*Example Only Data Invalid

Managing Hourly TeamsMicrosoft Word or equivalentManaging Salaried TeamsMicrosoft Excel or equivalentDelivering/facilitating training to othersServing as a MentorManaging a P&L statementTurning around a Poor Performing Microsoft PowerPoint or equivalentDelivering formal/informal presentations to various audiences

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What Schools Did Top Performers attend?

*Example Only Data Invalid

Univ of South Alabama AL

Florida State University FL

Univ of Iowa IA

Florida A & M University FL

Pennsylvania State University PA

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Find.ly Talent Community

Builds patented Social Talent Graph

Capture

One click, once.

Performs real-time social updatesInfo is always up to date

Find.ly can capture active candidates,

passive visitors and employees to build a large Talent

Hive. Capture, Engage, and Save

Job BoardsCareer Site

Facebook

LinkedIn

ATS

File Upload

iPad

Smart Phone

EmployeesEmail & more...

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Big Data: Social Media Trends Find.ly

*Example Only Data Invalid

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Wrap up: transforming HR and changing the conversation

Data is the Great Equalizer

Recruiters and hiring managers a two-way street

The proverbial “seat at the table”Objective measurable intelligenceconnects talent to the business

Changing “what matters” to reflect real talent performance and potential

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Thank You! 

Donna Quintal Senior Manager of Strategic Sourcing, Sears Holdings Corporation

Glen Cathey Vice President, Sourcing and Recruiting Center of ExpertiseRandstad Sourceright

Q&A

www.randstadsourceright.com SolutionsInfo@randstadsourceright.com