1. Empowering Success With Big Data-Driven Talent
Acquisition
David Bernstein – VP Data Analytics
July 15, 2013

2. Background
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3. Market Interest In…
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4. Huge Interest in “Big Data”
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5. Why Is There So Much Interest?
• The promise of what you can do with Big Data
• Golden opportunity to contribute to the success
and profitability of the business
• A new way to look at data and business issues –
Real time, patterns and trends, and forecasting
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6. So, What is Big Data?
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7. What is Big Data?
Buzz phrase – Squishy….no single definition
• Official Oxford Definition (2013) - data of a very large size, typically to the extent that its
manipulation and management present significant logistical challenges
• Unofficial definition: Convergence is building around the following:
» Gartner’s 3 “V’s – A data set that is created through the combination of high Volume and
Velocity from a Variety of sources
» IBM’s 4th V – Veracity
• Technical Component - Due to the enormity of the data traditional data
acquisition, storage, and processing tools will not suffice
• Paradigm Shift: Traditional Structured vs. Creative Discovery Models
=====================================================================
• Key Facets- Big, Fast, and “Different” – Blended together, Allowing for
Predictive/Forecasting and Real-Time Analysis
• Layman’s definition is emerging. Less focus on “what it is.” Instead the focus is
shifting to “why it is important?” and “how it can be used?”
» i.e. “Big Data” is collection of activities that center around the analysis of large sets of data to
determine if there are any Patterns that could be used to Predict Performance.

8. Hallmarks of Big Data
• Data in Motion - Streaming vs. Snapshot
– See the “story” unfolding. Able to mitigate if
needed
• Discovery - Pattern and Trend Analysis
– Leverage those insights faster
• Statistical Analysis – Hindsight to Foresight
– Correlation and Causation
– Predictive Analytics
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9. Question…Does HR Really Have Big
Data?
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• Volume – Does not have to be terabytes
– Thousands of candidates, Hundreds to tens of thousands of employees
• Velocity – Does not have to be data created every second
– HR data is created on daily, weekly, monthly, and quarterly cycles
• Variety – Does not have to be from hundreds of sources
– Numerous HR systems
(ATS, HR, Comp, Benefits, Payroll, LMS, Performance, etc.) , Non HR
internal sources (Social Media, Web logs, Financial Performance, etc.)
and external sources (Government, Social, Vendors, etc.)
Answer: Yes. The volume, velocity, and variety are therefore relative
to the business function of HR. The quantity, speed, and variety of
the sources that comprise HR Big Data are relative to the business
cycles, transactions, and the size of the business that HR is operating
in.

10. Big Data in HR
Examples of where Big Data can and is being used by HR
today:
• Compensation Benchmarking
– Common
• Workforce Planning
– Nascent/Emerging
• Selection Testing
– Moderate
• Areas ripe for “Big Data” analysis:
– Team Performance
– Learning & Development
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11. Evolution of HR
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HR’s role is participating in and creating business strategy. 80% of
HR Leaders now report to the CEO. What stories does the data
tell? What insights can be derived and applied?

12. HR’s Big Data Challenges
• No clear understanding of what it is or how to
apply it
• Lower comfort level with metrics and analytics
in general
• Skills gap
• Bandwidth issues - Daily Priorities
• Limited Budgets
And Yet – A Growing Understanding of the Need
to “Speak” the Language of Business
– $’s and Data 12

13. Analytic & Big Data Readiness
Let’s Go To The Polls…
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14. The Facts
• Only 6% of HR organizations report that they have excellent analytic
skills internally. Most have not yet invested the time it takes to build a
holistic analytics function. Due to limited headcount, priority is given
to core responsibilities.
• Only 8% of companies report that they have begun to implement a
Predictive Analytics strategy into their HR Strategy and Planning
activities.
• Most reporting has been focused on HR Operational metrics vs. using
data to drive planning and decision making.
• The United States alone faces a shortage of 140,000 to 190,000 people
with analytical expertise and 1.5 million managers and analysts with
the skills to understand and make decisions based on the analysis of
big data.
The Opportunity:
• Companies in the top third of their industry in the use of data driven
decision making were, on average, 5% more productive and 6% more
profitable than their competition.

15. Who Said This?
“Today, many companies are reporting that their number one
constraint on growth is the inability to hire workers with the
necessary skills.”
15
Peter Capelli– Professor of Management, The Wharton School
Of Business - Present
William Jefferson Clinton – President of the United States of
America 1993 - 2001
John Francis “Jack” Welch, Jr. – Chairman and CEO of General
Electric 1981 - 2001

16. Why Applying Big Data To
Talent Acquisition Matters
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• Talent Is Clearly A Differentiator
• Talent is what drives innovation
• “War for Talent / Competitive Talent Acquisition
• Candidates can only take on job at a time
•
• Talent Constraint Issues
• PwC Study
• Boston Consulting Group Study

17. Paradigm Shift
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18. Moving From a JIT/Customer Service
Orientation
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To Being Proactive and Strategic

19. Value Propositions for
Talent Acquisition
• Paradigm Shift–
– Proactive and Foresight driven
• Talent needs assessment – What, When & Where
– Focus on building talent sourcing strategies that align to the business plan
– Increase focus candidate and hiring manager engagement vs. transactional
aspects of the process
– Tied to a “Workforce Plan”
• Smarter Spend –
– Reduced Cost Per “Applicant” and “Hire”
– Ability to reduce or get broader coverage with the marketing budget
• Precision and Speed –
– Know before you begin – Sources and Difficulty
– Narrow casting – No more Post & Pray/Spray
– Timeliness

20. What if you could accurately predict the
outcome?
20

21. What If?
• What would you be able to do if you could…
– More accurately forecast which channels to source from, how long the
sourcing cycle will take and how much candidate flow you can
anticipate?
– Be able to use that information to be “proactive” in your talent
acquisition activities?
– To understand the effectiveness of any mitigation actions you’ve taken
in real-time?
– To have the competitive “talent” intelligence regarding how well your
marketing efforts are working, in real-time?
– Have insight into the available supply and demand for talent?
• “Recruitability Index” and “Poaching Protection”
– Could tie Sourcing to future Performance and Retention
Think about how these insights and being proactive can give you a competitive
advantage. Make faster, evidenced-based decisions. Take quicker actions.
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22. Talent Acquisition Sources
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The Number of Communication Has Exploded

23. Sources
Greatest Scrutiny Should Be Put Where Money is Spent!

24. Applying Big Data To Talent
Acquisition In Your Shop
• Start With The End in Mind – Decide What You
Want to Address
– Reduced Attrition, Align TA with Business Objectives
(Growth, Pace of Business, Smarter Budget/Spending)
• Workforce Planning / Talent Needs Assessment
– Focus on Mission Critical Positions
– Keep it Simple
• Formula: (# of Incumbents x Attrition Rate) + (# of Incumbents
x Growth %) /12
• Know Your Typical Conversion Funnel
– By Job and Source 24

25. Applying Big Data To Talent
Acquisition

26. Big Data Doesn’t Have To
Be Hard!
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27. 27
Big Data Doesn’t Have To
Be Hard!
Begin With The End In Mind!

28. 28
Big Data Doesn’t Have To
Be Hard!
• Start with your internal data in your core ATS and HR systems
• Review your Employment Site weblogs
• Benchmark – Compare the above metrics with external sources – i.e. consulting
firms, peer companies, consortiums, etc.
• Work with your job boards to capture the key metrics they have about your
company – i.e. how often your company is searched for, how often your jobs
are viewed, how often they are clicked on, etc.
• Know your Candidate Conversion Funnel Metrics – including cost per milestone
• Subscribe to data services – i.e. Web traffic data, Google Ad-Words, Vendor and
Government Labor Data, etc.
• Social Data/Sentiment Analysis – measure your Facebook, Twitter, and LinkedIn
Traffic – i.e. number of Likes, Follows, Re-Tweets, etc. and determine if there is
a correlation with your employer brand and recruitment marketing efforts
• Partner with your outsourced vendors who are supporting any of your
transactional activities to capture the data they capture and blend with your
analysis.

29. 18
Sourced
8
Responses
3
Interviewed
1
Hired
Sample Conversion Funnel

30. Sentiment Analysis - LinkedIn

31. Sentiment Analysis - Facebook

32. Avoid Creating Dashboard
Dizziness
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Create The Right Visuals That
Reveal The Right Story!

33. Big Data & Talent Acquisition
In Action – Brief Case Studies
• Manufacturing employer
– Achieved “fully staffed” status for their hourly workers for the first time
ever by determining attrition patterns and adjusting their sourcing
strategy accordingly
• Software and services employer
– Determined skills gaps and built out training and talent acquisition
strategies that enabled them to meet customer demands
• Financial services employer
– Increased recruitment marketing coverage, reduced number of media
outlets, increased quality of candidate ratio, and reduced time to hire –
all without increasing their spend
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34. Appendix
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35. A Tale of Two Recruiters
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36. Can You Relate?
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Barely Able To Keep Up With The Requisition Load
And Resume Flow

37. Then, Another Hiring Manager
Calls And Says,
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“I Finally Got My Requisition Approved. How Soon Can We Get
Someone To Start?”

38. And There You Are…
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Trying To Remain Cool & Calm

39. Your Management Thinks…
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40. But In Truth, I Feel Like This…
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41. How Will I Market This Job?
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42. Too Many Choices
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Not Enough Time

43. Which Pond To Fish In?
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44. Talent Acquisition Is Competitive –
I Know It Is Critical That I Can…
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Market My Message In The Right Places, The First Time…
Ahead Of The Competition

45. I Wish There Were An Easier Way
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46. I Wish I Could
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Work Smarter Not Harder!

47. I Wish I Had Better Tools
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48. Put Big Data To Work For You
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49. No More Just Using The Usual
Outlets
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50. 50
No More Relying On Single Sources

51. No More Posting And Spraying
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52. The Talent Pipeline Challenges
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How To Build It? Will It Have The Talent?

53. A Tale of Two Recruiters
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Which One Would You Rather Be?

54. In the end – it’s all about ….
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Find Candidates, Fill Jobs Faster, Spend
Smarter!

55. Questions?

56. David Bernstein
VP – Big Data for HR
925-275-8102
David.Bernstein@eQuest.com
Blog: www.equest.com/news/floating-point
LinkedIn Profile: www.linkedin.com/in/davidsethbernstein
LinkedIn Group: http://linkd.in/VMZzqm
Twitter: www.twitter.com/dbernste 56