NHRD HR Analytics Presentation

HR Analytics Workshop
NHRD , Sept 2015

© Copyright- Cerebrus Consultants© Copyright- Cerebrus Consultants
Contents
• Session Objectives
• What is HR Analytics ?
• Analytics Maturity Model
• Measurement Focus at each level
• Applications of HR Analytics
• Analytics Process Steps
• Talent Data & Metrics
• Solution Steps
• Case Study
• Data Collection
• Analytics
• A Sample Dashboard
2

Session Objectives
• What is HR analytics ?
• What can HR Analytics do ?
• What are the different types of analytics ?
• How to solve a business problem using analytics ?
• How to present analysis findings ?
3
To trigger thoughts around the potential of Talent Analytics for solving business
problems by understanding…

What is HR Analytics ?
Which of these words best describes HR Analytics ?
4

HR Analytics
Data Insight Action
Talent / Business
Process Data
Transform using Statistics
/ Operations Research /
Computer Programming
Techniques
Application of Analytics techniques
to gain insights on talent and aid
talent decisions is “HR Analytics”
Answers “Why” ;
Predicts “What will
happen”,
Decisions to improve
business performance
What is HR Analytics ?
5

Analytics Maturity Model
Reporting
56%
Business
Value
Complexity
Analysis &
Monitoring
40%
Predictive
Analytics
4%
What is happening?
Why is it happening?
What can happen?
Hindsight
Insight
Foresight
Level 1
Level 2
Level 3
6

Measurement Focus at each level
Maturity Level
Answers the
question
Measurement
Focus
Sample Metrics / Analysis
1 - Reporting
What
happened ? /
What is
happening.
Reactive
Rate, Volume ,
Composition, Cost, Time,
Quality
Input Metrics ,
Measures
Efficiency,
Compliance
Headcount, Learning
Hours, Time to hire, Cost
per hire, Performance
Scores, Channel Mix
2 –Analysis &
Monitoring
Why is
something
happening?
How can it be
better ?
Proactive
Trends , Distributions,
Averages, Correlations
Output Metrics,
Benchmarking
Trend of attrition rate by
month, tenure, gender etc.
, Learning Effectiveness
Measures, ROI Measures,
7

8
Maturity Level
Answers the
question
Measurement
Focus
Sample Metrics / Analysis
3 – Predictive
Analytics
What can
happen ?
Futuristic
Regression Analysis,
Factor Analysis
Probability
Prediction of flight risk at
the time of hiring,
predicting which hire will
be a top performer,
Predicting satisfaction in
employees based on
parameters like
developmental
opportunities, training
provided etc.
Measurement Focus at each level

Applications of HR Analytics
• How to predict if the person hired
will be a top performer ?
Talent
Acquisition
• How to predict if the new hire will
continue in the organization for
18 months ?
Talent Retention
• What are the chances the
promoted candidate will be
successful in new role ?
Talent
Performance
• Will this person be the right fit for
this position ?Job Allocation
Can answer critical questions to improve performance of talent processes
9

Analytics Process Steps
10

Talent Data & Metrics
11
• Data from across
various HR / Business
processes.
• Data external to
organization may also
be included viz. social
data ( comments from
glassdoor for e.g.)

Solution Steps
• What is the Business Problem Statement ?
What is happening, What is the impact ?
“The problem of call drops affects the customer, the impact of which is reduced customer
satisfaction “
• What is the analytics problem statement ?
What will be analyzed, what needs to be identified ?
“Analyze new hire data to identify the characteristics of a potential top performer “
• What data will be collected ?
Data Sources, Basic data, Derived Data
• What analysis will be performed ?
Basic Analysis ( Numbers, Ratios etc) , Historical Trends, Find Correlations,
Identify independent variables, Define Hypothesis to be tested, Build Data
Models, Run Statistical Analysis 12

Case Study
You are the HR Manager for Hero Global Services Ltd, a provider of business
and knowledge processing services to global clients. It operates out of two
locations in India and has an employee headcount of 8000. The Insurance
business vertical is facing the problem of high levels of attrition amongst its
staff. Annualized attrition rates stand at 40%. This is heavily impacting
business, existing staff is highly stretched at work and morale is low. There is
talk of high stress levels, inflexible HR policies and engagement amongst staff.
Many employees have joined competitors with good salary hikes.
The business hires employees who are graduates. About 50-75 employees are
hired every month. They may be hired right after college or with 2-3 years
experience in similar profile. They are then trained for 4 weeks (class room)
and then provided on the job training ( 4-6 weeks) and then moved to various
processes. There are ten levels within the organization, the front line
employees accounting for about 70% of the overall population.
13

Data for Analysis
# Data Item # Data Item # Data Item
1 Employee Name 16 Date of Joining 28 Age
2 Date of Birth 17 Work Location 29
On boarding Feedback
Score
3 Qualification 18 HRBP
4 Experience 19 CTC
5 Gender 20 % increment
6 Marital Status 21 Number of times promoted
7 Residence location 22 Training Hours
8 Source of hire 23 Performance Rating
9 Recruiter 24 Date of Resignation
10 Hiring Score 23 Notice Period
11 Time to Hire 24 Date of Leaving
12 Grade 25 Reason for leaving
13 Department 26 Buddy Allocation
14 Supervisor Name 26 Number of absences
15 Department 27 Tenure
14

Data Analysis /tics
# Analysis / Cuts Type / Tools Insights
1
Attrition Numbers / Rates
by year, location, tenure,
Department, supervisor,
gender, Grades, Education,
Experience levels, Age,
Type, Life Stage,
Confirmation Status,
Basic Reporting /
Level 1 / Excel
To identify attrition trends,
to zero down areas
where the problem is
severe and needs more
attention
2
Reasons of Attrition (%
contribution) by Grade,
Tenure, Level, Life Stage,
Supervisor
Basic Reporting /
Level 1 / Excel
To identify the top
reasons for attrition, zero
down the same by
various categories.
15

16
# Analysis / Cuts Type / Tools Insights
3
Define & Check Hypothesis –
“% increase in compensation
offered at hiring stage impacts
retention rate “, “ Fresher's
more likely to quit than
experienced staff”
Analysis / Level
2 / Excel
(Rations /
Correlations)
To identify independent
factors that impact
retention.4 Define independent variables
e.g. Compensation /
experience level / Age etc that
can impact retention & build
data model
Analytics / Level
3
5 Linear / Logistic Regression
Analysis
Analytics / Level
3 / Statistical
Package
To find an equation to
predict the probability
of retention
Data Analysis /tics

A Sample Dashboard
17
0-90 days accounts for 41%
Highest attrition in 3-6 mths bucket (23%)
Band 1 biggest contributor to attrition
Total Attrition – FY 12 13Band 1 Attrition – FY 12 13Attrition Rate Trends– FY 12 13
Tenure wise Attrition – FY 12 13
Reason wise Attrition – FY 12 13
• 7.7% (22 nos) of those who
quit voluntarily were top
performers
• 6.67% (19) of those who quit
voluntarily were on a PIP
during the course of the year.
• 25.62% ( 72 nos) of those who
quit voluntarily were females.
• The average salary of those
who quit for better prospects is
1.8 Lacs pa.
• Those in the salary range of
1.5 - 2.0 are very vulnerable to
moving out.
• Fresher's are susceptible to
abandoning jobs and pursuing
higher studies (16-17%) than
experienced staff ( 6-10%)

Thank You
For further details, contact
supriyat@cerebrus-consultants.com
Tel: +91-7838871701

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