HR ca not operate in traditional ways any more The technology driven data management is a necessity . HR analytic is pretty useful in driving crucial decisions.about work force especially in IT sector. Here are few tips.If you liked least you could do is to share also read my latest book in Amazon

1. ECTOTHERMIC –HR-
ANALYTICS
PREDICT AND
PRESERVE
Dr. Sarma
HR SME
6/27/2013 Dr.sarma/hr/analytic 1

2. What is covered
The new vocabulary
Ectothermic analytic
Social media impact
Why and what predictive analytics can do
HR analytics new normal
HR to Create the driver
Predict or perish
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3. New Vocabulary
• Corporations need to look
“outside-in” for robust analytic
reporting
• i will call it ectothermic analytic
• Risk is mostly from out side
• Even attrition is more due to pull
power than push power
• Revenue loss is due to
competition from out side
• Fraudulent intrusion biggest
security threat is from out side
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4. Past to future
tetra bites of data of
information being generated
every single which is being
used to answer, fairly
accurately, what will
probably occur in the future
Analytics is shifting
emphasis from trend
analysis based purely on
internal data to presenting
scenarios of the future
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5. Social media impact
Predicting
the future
sounds
mystical
Predictive
ANALYTIC
is touching
every
human on
Earth who
accesses
internet
day to day
existence
is now
being
exploited
by social
media and
then the
analytics.
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6. Ectothermic analytic
• HR must shift gear to
what I would call
Ectothermic analytic
• Just as an organism that
regulates its body
temperature largely by
exchanging heat with its
surroundings business
entities must focus on
external data sources to
adjust internal heat
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7. Why ectothermic?
• Competition- risk comes from out
side
• Growth- depends on external
market changes
• Fraud risk- enormous intrusion
happens from outside
• Customer expectation-changes as
per competitive offerings outside the
organization
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8. Traditional BI is not valid
• Standard business intelligence
and reporting methods provide
value by summarizing the
past.
• Scorecards, dashboards, KPI
metrics, OLAP, ad hoc queries
deliver a retrospective analysis.
• They are all
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9. Analytic impacts every day life:
• When you shop in
Supermarkets they know
more about you as frequent
shopper card
• Credit rating companies
gather every person’s financial
history in order to predict how
credit worthy that person is –
how much money to lend,
employers determine how
responsible a person is,
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10. Life is no more isolated
• In Major League Baseball data about
every move made by every player
during every game is gathered to
predict who the starter should be against
a particular team.
• Satellites collect enough digital
information on people, which if printed,
can fill the whole earth , and these data
mining and predictive capabilities were
instrumental in finding and tracking
Osama Bin Laden
• Companies are mining millions of
tweets and stock transactions a day in
order to predict stock performance
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11. • Analyzing historical data is no
more effective but predictive
analytics is necessary as
enterprise wide practice to
sustain competitive advantage
• predictions are being made
about behaviors as information
that comes from several
thousands of sources.
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12. What predictive analytics can do
• Every business’s success is all about
managing risks that arise in future.
• Decision makers therefore have to bet
top dollar to determine the best course
of action to minimize challenges.
• Employee related risk management ,by
measuring monitoring and predicting -
must be the core HR process
• From people point of view everything -
indifferent employee, non performing
ones, high performing ones, the
sentiment they have about values
spoken by leaders pose the risk if not
managed with foresight and not
hindsight .
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13. HR Reporting is next phase back0ffice
automation
• HR is currently delivering information
to managers and executives on items
that they already know, --headcount
forecasted to be by quarter-end or year-
end
• what a past performance rating was,
how many may be going on vacation.
• These items are important but do not
tell the business anything new and is
primarily they are nothing but the next
phase of Human Resource “back office”
automation.
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14. Analytical Technology.
• Built upon mathematics,
probability, statistics, and
database technologies,
predictive modeling
capabilities, known as
machine learning -- proven
routes.
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15. • HR to be true “business partner”,
needs to tell the business scenarios’
that are predicted with high
accuracy to happen in the future,
across all levels of the organization,
and provide recommendations on
how to fix or exploit it.
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16. What HR analytics need to do
• Use dimension-free data exploration to
find answers on employee productivity
and qualifications, to help to determine
the appropriate size for the workforce.
• Dash board on how work experience
and education should affect starting pay
grades
• Shift from Head count reporting to telling
that X additional people need to be hired
because specific individuals in specific
levels with specific skills are expected to
leave and join the competitors
• Report on the reasons they will leave
e.g., the pay increase that has been
given in the past 24 months, or not
meeting the top performers expectation.
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17. Non traditional reporting
• Report is never made on actions
HR is taking if 16 of your top
performing rare skill leave and
join your customers after
analyzing top line impact of
attrition?
• Factor analysis of engagement
• if index is below 50% on trust
will HR sit quiet?
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18. Now or Never
• Human Resource organizations
are having difficulty in delivering
even defect free accurate
headcount reports
• How then they are going to predict
well?
• An attitude that predictive analytic
is something to be explored is the
wrong approach.
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19. Justify HR Funding
• Forrester Report -companies spend
less than 1% of their
business intelligence budget on HR.
• With HR making up, on average, 31%
of a company’s total operating costs,
HR analytic must be one of the top 3
funding areas.
• The current model for today’s HCM
Analytics just does not provide that
“business driver” to spend more
• HR needs to find “business driver”, as
discovered by other functional areas, to
tell the organization what it does not
already know,
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20. Gain support to get the
funding
• All of this is predictive analytics and
without it HR will continue to struggle to
obtain the funding and support for their
must-have analytics initiatives.
• HR can do predictive analytics today by
partnering with organizations (e.g. sales,
marketing and engineering) that have
predictive analytics already in place to
make quantifiable and actionable
predictions about the workforce in areas
that the business does not know about.
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21. Create the Driver
• In 3 weeks Oracle was able
to predict which top
performers were predicted
to leave the organization
and why - this information is
now driving global policy
changes in retaining key
performers and has
provided the approved
business case to expand
the scope to predicting high
performer flight .
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22. Critical areas for HR Predictive analytics
• 1.Turnover modeling. Predicting future turnover in
business units in specific functions, geographies by
looking at factors such as commute time, time since last
role change, and performance over time. One can
accelerate hiring efforts accordingly, reducing lead time
time and panic hiring, which can lead to lower cost, higher
quality hiring.
• 2. Recruitment advertising /HRBranding
effectiveness: HR Branding efforts based on Response
modeling for advertising jobs.
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23. HR –Predictive analytic
• 3.Targeted retention. Find out high risk of churn in the
future and focus retention activities on critical few people
• 4. Risk Management: profiling of candidates with higher
risk of leaving prematurely or those performing below
standard.
• 5. Talent Forecasting. To predict which new hires, based
on their profile, are likely to be high fliers and then moving
them in to fast track programs
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24. Final words
• HR is at a cross roads where analytics
is concerned.
• In order for HR to be successful in
analytics it must embrace the shift
towards predictive analytics. Without
making the shift, HR will not be able to
deliver on the promise of being a
“Business Partner”.
•
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