The Growing Role of Big Data in HR

Bernie Schiemer

Chief Executive Officer

HRBossClick on the twitter button to

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@bernieschiemer

About HRBoss

Founded in 2011 in Asia

We are a globally minded data driven HR software solutions provider

HRBoss fast facts:86 staff in Asia

58 Males / 28 Females

19 nationalities

35 languages spoken

Average age is 34 yrs old

7 countries (Singapore, China, Japan, Vietnam, Malaysia, Indonesia & Hong Kong)

3 software solutions

Award winning solutions

Gold Winner at the SiTF Awards 2013 for best Cloud Solution for Singapore

Winner of China HR Pioneer awards 2013 for top HR Big Data Solution in China

Finalist in the 'Best SaaS Solution' (outside of the US) at The Cloud Awards 2013-14

Big Data

In 2013 “Big Data” on Twitter was being mentioned

4,000+ times per hour!

25% of US organizations now have a data scientist

on staff

34% of organizations say they have no formal

strategy to deal with Big Data

DATA, DATA, BIG DATA….

38% of organizations don’t understand what Big

Data is according to CIO Magazine

75% of companies say they will increase

investments in Big Data within the next year according to Avanade

Agenda

Concepts of big data, analytics, Moneyball as they relate to HR and recruiting

How facts become our friends and how this drives competitive advantages through fact based decision making

The road to predictive analytics

Obstacles faced with data management

EmployeeBoss solution

Why now? - Time to value

Next steps

So What is Big Data?

Big Data is often characterized by the 3-V’s:

Volume

Large amounts of data, updating historical data sets

Velocity

Speed at which new data is created

Variety

Derived from many sources, and as a new event takes place, this can exponentially expand that variety and size of the data

Analytics versus Big Data

Many people use the term “big data” when they are really referring to analytics and data-based decision making

Many companies use analytics in human resources to analyze correlations between:1. Recruiting

2. Assessment data

3. Employee performance

4. Retention

Analytics versus Big Data

data-based decisions alone doesn’t correlate with “big data”… unless the data being analyzed meets certain criteria

Grasping the concept of big data, there is still confusion as to exactly what “big data” is and what it is not

So What is Big Data?

Data explosion explained….

Big Data for employees….

analytics does not equal big data unless it meets the V3 criteria

What is Moneyball?

Moneyball: The Art of Winning an Unfair Game by Michael Lewis

The premise of the book is that the collected wisdom of baseball insiders is subjective and often flawed

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

In 2002 they took a sabermetric approach to assembling their team, picking players based on qualities that defied conventional wisdom

Sabermetrics was originally defined by Bill James in 1980, as "the search for objective knowledge about baseball"

Facts become your friends

They found that on-base percentage and slugging percentage are better indicators of offensive success than batting averages

These qualities were cheaper to obtain on the open market than more historically valued qualities such as speed and contact

They often picked players that other scouts and teams would overlook because the players didn’t have the right body type or they had a funny swing

So what happened?

2002 Facts

In 2002 the salary cap of the Oakland A’s was $41 million

The A’s finished 1st in the American League West and set an American League record of 20 consecutive wins

New York Yankees spent over $125 million in payroll that same season

Though the Yankees made the World series finals they were swept by the Anaheim Angels in 4 four games

2002 Facts

The essence of “Moneyball” lies in using data and statistics to:

“arbitrage miscalculated pay rates” to avoid overvalued skills/experience

to identify undervalued skills when building teams

and to develop a competitive advantage without having to “buy” expensive talent

Though the A’s did not win the World Series, Moneyball allowed them to remain competitive and profitable in a market that was becoming dominated by big spenders

2013 Facts

The NY Yankees now employee a whole team of sabermetric analysts

There is a real focus now on using historical data sets to analyze and predict future player performance

The Boston Red Sox embraced the analytic Moneyballapproach when they tried to poach Billy Beane from the Oakland A’s in 2002

Though Billy did not accept their offer, since 2003, they have won 3 World series titles

These are the banners you see today on the Oakland A’s and New York Yankees websites...

Talent Analytics Maturity Model

The ultimate aim of a big data solution is to reach the holy grail of insight called predictive analytics

To be able to accurately forecast events before they occur

Bersin at Deloitte forecasts 5 years to achieve this goal

Of the 480 companies they spoke with only 4% have achieved any kind of predictive analytics capabilities

Why now?

Now is the time to focus on talent analytics. Key drivers for some of our clients include:

Employee retention – what creates high levels of engagement and retention?

Sales performance – what factors drive high-performing sales professionals?

Leadership pipeline – who are the most successful leaders and why are some being developed and others are not?

Customer retention – what talent factors drive high levels of customer satisfaction and retention?

Expected leadership and talent gaps – where are our current talent gaps in the organization and what gaps can we predict in coming years?

Candidate pipeline – what is the quality of our candidate pipeline?

How do we better attract and select people who we know will succeed in our organization?

START

2-3 years

later

the later you start the later you arrive…

The path to predictive analytics

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EmployeeBoss

Next Steps

Click here to read the Data Analytics post-event blog