The document discusses HR analytics and predictive modeling. It defines key concepts like metrics, analytics, and business intelligence. Analytics uses data to understand past trends and predict future outcomes. The document outlines areas where predictive modeling can be applied in HR, like attrition, recruitment effectiveness, and talent forecasting. It also provides examples of companies like Oracle, Sprint, Starbucks, and Dow Chemical that have successfully used analytics to retain top performers, predict attrition, measure engagement impacts, and do workforce planning.

1. HR Analytics
Shubham Singhal
80303120053
PGDM
NMIMS, Hyderabad

2. Primer
 The core of HR Analytics is the "metric“
 Metrics can be said as data that conveys meaning in a given context
 Metric is to be distinguished from numbers
 Example:
- Employee turnover is 13.5% p.a. Data
- There is a 4 percent point rise in attrition rate on a year to
year basis
Metric
- Inappropriate Leadership styles of select managers
resulted in higher attrition of 3% on a comparable basis
Analytic
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3. Primer – Contd.
 Checklist, Dashboard, HRIS
- All of these are tools to collate and display information
 Hypothesis: u0 & u1
 Variables: Dependent and Independent
 Statistical Models
- E.g. Regression, ANOVA
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4. HR Analytics
 Analytics is not so much about numbers, as it is to do with logic and reasoning
 Analytics is different from Analysis, which is the equivalent of number
crunching. Analytics uses analysis but then builds on it to understand the 'why'
behind the figures and/or to predict decisions. Analytics is the methodology of
logical analysis
 Analytics requires the use of carefully constructed metrics
 HR Analytics is data based; it uses past data to predict the future
 It is not about the quantity of data churned; it is about the logic used to link
metrics to results
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5. Core concepts and terminologies
Analytics
Decision
=Business
Intelligence
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6. Business intelligence (BI) is a set of theories,
methodologies, processes, architectures, and
technologies that transform raw data into meaningful
and useful information for business purposes.
Business analytics (BA) refers to the skills,
technologies, applications and practices for continuous
iterative exploration and investigation of past business
performance to gain insight and drive business
planning.
6 Core concepts and terminologies

7. Past to future
Tera bytes of data of
information being generated
every single day 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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8. HR’s Evolution

9. Background
Need of HR analytics & reporting
 Many organizations have high quality HR data (residing with a multitude of systems, such as the HRMS,
performance management, learning, compensation, survey, etc.) but still struggle to use it effectively to
predict workforce trends, minimize risks and maximize returns.
 The costs of attrition, poor hiring, sub-optimal compensation, keeping below par employees, bad training
& learning strategies are just too high
 Data-driven insights to make decisions are always better than judgmental (subjective) HR practices in
terms of
 how to recruit
 whom to hire
 how to onboard and train employees
 how they keep employees informed and engaged through their tenure with the organization
Hence regular tracking and prediction of crucial HR metrics is indispensable
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10. Why HR Analytics?
“What gets
measured, gets
managed; What
gets managed,
gets executed”
- Peter Drucker
“ To clearly
demonstrate the
interaction of
business objectives
and workforce
strategies to
determine a full
picture of likely
outcomes”
HR Dashboards - SAP
Measure &
Manage
Linkage of
Business
Objectives
and People
Strategies
Return on
Investment
Performance
Improvement
“The business
demands on HR are
increasingly going
to be on analysis
just because people
are so expensive“
- David Foster
“Global organizations
with workforce
analytics and
workforce planning
outperform all other
organizations by 30%
more sales per
employee.”
- CedarCrestone
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11. Objectives11
Predict attrition especially amongst high performers.
Forecast the right fitment for aspiring employee
Predict how compensation values will pan out.
Establish linkages between Employee engagement score and C-Sat
scores(Work in progress)

12. What should/could be measured?
Recruitment
Organization
effectiveness
HR
Matrices
Workforce
Comp &
Benefits
Retention
Performance &
Career
Management
Training
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13. 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.
2. Targeted retention. Find out high risk of churn in the future and focus retention
activities on critical few people
3. Risk Management. Profiling of candidates with higher risk of leaving prematurely
or those performing below standard.
4. 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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14. Trendwise Analytics – HR analytics
capabilities
•Reporting of basic metrics, their frequencies & percentages by
various cuts followed by key highlights. These can be monthly,
quarterly, half yearly tracking reports
• Tool: SAS/REPORT
• Techniques: frequencies , means, percentages etc.
Level-1
Descriptive
analysis
•Derivation of some HR operational metrics which will help us in
tracking the efficiency of HR functions
• Tool: SAS
• Techniques: means, variance, control limits, ratios,
percentages etc.
Level-2
Operational
metrics
•Predictive analysis based on historical HR data. Attrition
forecasting, performance management, compensation
analysis, survey analytics, new hire strategies etc.,
• Tool: SAS BASE, SAS E-miner, Excel
• Techniques: Regression analysis, Time series analysis, cluster
analysis etc.
Level-3
Predictive analysis
Three levels of HR analytics and reporting
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15. Stages of Analytics
Predictive Analytics
What can happen?
Analysis & Monitoring
Why did it happen? What is
happening now?
Reporting
What happened?
Complexity
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16. Types of Analytical Models
PREDICTS
PREDICTS
PREDICTIVE ANALYTICS
Current
Predictive Analytics Data
PREDICTS
Future
INFERENTIAL ANALYTICS
Analysis & Monitoring
Past Data
Reporting
REPORT
Drawing
Conclusions or
Inferences
DESCRIPTIVE ANALYTICS
Representation of
Data and
Summarizing
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17. Critical areas for HR Predictive
analytics
 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.
 Recruitment advertising /HR Branding effectiveness: HR Branding
efforts based on Response modeling for advertising jobs.
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18. HR – Predictive analytics
 Targeted retention. Find out high risk of churn in the future and focus
retention activities on critical few people
 Risk Management: profiling of candidates with higher risk of leaving
prematurely or those performing below standard.
 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
18

19. Tools & Software Used
Typical tools / software:
• Microsoft Excel (max used)
• BI reporting tools
• ERP reporting tools, dashboards
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• Statistical software like SAS, SPSS etc.

20. 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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21. Executives; Corporate Strategy
Craft and guide long term
workforce plan based
on given information
Finance; Controlling; Budgeting
Give input regarding financial
figures and receives insights for
midterm financial planning
regarding the workforce
€$¥
HRBP
HR Business Partner
Consult with Business Units based
on workforce intelligence and
drives action plans as final
deliverable from the process
HR HR HR
HR Administration; HR Functions
Recruiting, Staffing, Talent Management
and other HR functions support
fulfillment of workforce action plans
HCM Analytics consumers by role
Stakeholders across the organization
√x
Middle Managers; Line Managers
Execute on strategic plans and
manage organizational performance
to assure strategic objectives are
reached timely and efficiently
MGR
Employee
Needs
contextual HR
data to better
perform
HR Analyst
Needs ad-hoc
capabilities to do
sophisticated
analysis and
planning

22. Real world case studies
Starbucks, Limited Brands, and Best Buy—can precisely identify the value of a 0.1%
increase in employee engagement among employees at a particular store. At
Best Buy, for example, that value is more than $100,000 in the store’s annual operating
income.
Many companies favor job candidates with stellar academic records from prestigious
schools—but AT&T and Google have established through quantitative analysis that a
demonstrated ability to take initiative is a far better predictor of high performance on
the job.
Employee attrition can be less of a problem when managers see it coming. Sprint has
identified the factors that best foretell which employees will leave after a relatively
short time.
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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23. Dow Chemical has evolved its workforce planning over the past decade, mining
historical data on its 40,000 employees to forecasts promotion rates, internal transfers,
and overall labor availability.
Dow uses a custom modeling tool to segment the workforce and calculates future head
count by segment and level for each business unit. These detailed predictions are
aggregated to yield a workforce projection for the entire company.
Dow can engage in “what if” scenario planning, altering assumptions on internal
variables such as staff promotions or external variables such as political and legal
considerations.
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Real world case studies

24. Thanks!