1. HR Analytics
Application of statistics, modelling, and analysis of
employee-related factors to improve business
outcomes.
Presented By:
Chandan Ray (D/15/EE/001)
Biswajit Changkakoty (D/15/EE/106)
Abhishek Kumar (D/15/EE/108)
Amit Jyoti Deka (D/16/EE/202)
2. HR Analytics?
Human Resource analytics is about analysing
an organizations’ people problems using data.
Datas are being used to answer questions
like: How High is your employee annual
turnover?
How much of your employee turnover
consists of regretted loss?
Do you know which employees will be the most
likely to leave your company within a year?
3. Need of HR Analytics
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) HRpractices 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
4. Why HR Analytics?
Performance
Improvement
“Global Organizations with
workforce analytics and
workforce planning
outperform all other
organizations by 30%more
sells per employee.”
-CedarCrestone
Return Of
Invesstment
The business demands on HR
are increasinglygoing to be onanalysis
just becausepeople are so expensive.
Manage and
Measure
“What gets measured, gets
managed;What gets
managed, gets executed”
- PeterDrucker
Linkage of Business
Objectives and
people strategies
“ Toclearly demonstrate the
interaction of business
objectives and workforce
strategies to determine a full
picture of likely
outcomes”
HR DashBoard - SAP
5. Terminologies:
Business Intelligence
Business Analytics
Business Intelligence:
Technology-driven process for analyzing data
and presenting actionable information to help
executives, managers and other corporate
end users make informed business decisions.
Business analytics:
the skills, technologies, applications and practices
for continuous iterative exploration and
investigationof pastbusiness performanceto gain
insightanddrivebusinessplanning.
Analytics
Decision
Business Intelligence
=
Core
Terminologie
s
7. LEVELS of HR
Analytics
Descriptive Analytics : Insight into the past
Descriptive Analytics : Insight into the past
Predictive Analytics : Understanding the future
Prescriptive Analytics : Advise on possible outcomes
12. Critical areas for
HR Predictive
analytics
Turnover modeling. Predicting future turnover in business units
in specific functions, geographies by looking at factors.
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.
Risk Management: profiling of candidates with higher risk of
leaving prematurely or those performing below standard.
14. Finding the right talent to
run HR analytics.
A lack of confidence Currying executive support. Data quality.
Challenges to make Analytics Work
1 2 3 4 5
Data Deluge.
15. Conclusion
The model gives vision to HR leader to make right decision.
Understand the relationship between turnover and compensation.
Helps the organization to reach their goals.
16. Thank You
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