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%

Bu

sin

ess

Valu

e

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 13 Band 1 Attrition – FY 12 13 Attrition 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

[email protected]

Tel: +91-7838871701

mailto:[email protected]



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