When Big Data Meets Recruiting - HRM Asia March 2015 Presentation
1. When Big Data Meets
Recruiting
Social Recruiting Asia Congress, 24 March
2015
From
Dheeraj Shastri
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
2. Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
3. What is Big Data
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
4. What is Big Data
Big data is a buzzword, or catch-phrase, used to describe a
massive volume of both structured and unstructured data
that is so large that it's difficult to process using traditional
database and software techniques.
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
5. Big data is: rapidly increasing amounts of data,
generated by multiple sources, in many formats;
analyzed for new insights
The variety of data types are increasingly diverse.
Structured data* often comes from transactional
systems, while unstructured data comes from a
number of sources
such as photos, video,
text documents, etc.
Variety
Velocity
Volume
Veracity
Value
The volume of data being produced
has increased rapidly. Organizations
are faced with data from numerous
sources including the enterprise,
the cloud, and social media.
Data is being generated at
increasing rates.
Organizations not only need
to address how quickly data is generated,
but also how quickly
the data needs to be analyzed
before it becomes stale or obsolete.
Getting value out of
big data is dependent
on having quality data. If
an organization’s data lacks veracity
(correctness), decisions may be made that
do not actually benefit the organization.
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
7. Predictive Analytics an enabler of Big Data
Internal Data
• Number of hires in past
24 months
• job level & job function
• Attrition predictions
• Business & job level
External Data
• GDP
• Inflation
• Unemployment rate
• Age group
• Education
• Sector
Data sources
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
8. Big Data and Predictive
Analytics enable HR from
“I Think to I Know”
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
9. For Recruitment: The Basics Have Not Changed…
Need To Find & Attract The Best Talent, As Quickly
As Possible, For The Best Cost
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
10. Identify and prioritize:
Pivotal Roles
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
11. Specialist Key
Flexible Fundamental
Vacancy Impact
Scarcity
Short & Long-Term Impact
Vacancy in role has
significant impact
on short-term;
Specialized skills or
knowledge that
must be recruited
and/or developed
Vacancy in role has
significant impact on
short-term;
General knowledge
and skills
Vacancy in role has
little impact on
short-term;
Specialized skills or
knowledge that
must be developed
and/or developed
Vacancy in role has
little impact on short-
term;
General knowledge
and skills
Focus On Positions That Have The
Greatest Impact
Long-Term Impact
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
12. Know Your Typical Funnel
40
Sourced
14
Responses
5
Interviewed
1
Hired
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
13. Strategize the activities
Forecasting
Where are the most strategic
places to advertise?
Activity Summary
What does my recruitment
marketing activity look like?
Competitive
Analysis
How did my investment work
for me compared to my Talent
Competition?
Marketing
Effectiveness
How well did my investment
work for me?
Big Data
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
14. Market Your Message
In The Right Places, The First Time… Ahead Of The Competition
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
15. How To Apply Big Data In Talent Acquisition
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
16. The sourcing method
chosen is based on the
scarcity of talent and the
importance to the business
strategy.
Each method requires its
own strategy!
Specialist Key & Critical
Flexible Fundamental
Value Creating / Short-Term Impact
Scarcity
Affected by Strategy Affects Strategy
Pipelining
Sourcing
Build pipelines and direct
source for roles that will
yield valuable, recyclable
intelligence.
Labor Market
Research
“Quick wins” that yield high
intelligence but are easy to
execute and can be managed
with less resources
Agency
Engagement
Outsource roles that are
resource intensive but will yield
little intelligence.
Consultation &
Development
Leverage opportunities to
help managers increase
their networking skills, etc.
Determining The Best Sourcing Methods
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
17. Which Pond To Fish In?
17
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
18. • Know Your Data – by Position &
Labor Market
• What? So What? Now What?
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
19. In the end – it’s all about driving
Find Candidates, Fill Jobs Faster, Spend Smarter!
Source info: October 2012, 2013 Harvard Business Review, oracle Human capital management; eQuest Big data
In most enterprise scenarios the data is too big or it moves too fast or it exceeds current processing capacity. Big data has the potential to help companies improve operations and make faster, more intelligent decisions
While the term may seem to reference the volume of data, that isn't always the case. The term big data, especially when used by vendors, may refer to the technology (which includes tools and processes) that an organization requires to handle the large amounts of data and storage facilities. The term big data is believed to have originated with Web search companies who needed to query very large distributed aggregations of loosely-structured data
Today, big data is understood more or less from a technology perspective:
the possibility of better storage (volume),
the ability to process the information and make it available in real time (velocity)
the correctness and authenticity of data ( Veracity) and
the ability to deal with various kinds of data sources, including structured, semi-structured and unstructured ones (variety).
Businesses collect vast amounts of real-time customer data and predictive analytics uses this historical data, combined with customer insight, to predict future events.
Predictive analytics enable organizations to use big data (both stored and real-time) to move from a historical view to a forward-looking perspective of the customer.
For example, stores that use data from loyalty programs can analyze past buying behavior to predict the coupons or promotions a customer is most to participate in or buy in the future. Predictive analytics could also be applied to customer website browsing behaviors to deliver a personalized website experience for the customer.
Which pond?
…and getting to the good pond before the others!