HR Analytics Data Driven Insights for Proactive HR Management

How HR Analytics has Evolved.. Reporting in the HR space has evolved over the years and we find a continuum across various kinds of organizations

Operational

Advanced

Strategic

Predictive

“What can happen and what can be done about it ?” • Scenario Planning and

development of predictive

models

• Risk analysis & mitigation

“Why is it happening?” • Segmentation, statistical analysis,

development of ‘people models’

• Causal analysis and actionable

solutions

“What is happening?” • Benchmarking & Decision-making

• Multi-dimensional & dashboards

“What am I doing phase?” • Measurement of Efficiency and compliance • Data Exploration & Integration

Adapted from “Bersin & Associates, 2012, BigData in HR Research Study”

Recruitment

• Employee Success - Can I predict the success of an employee

based on the details in the resume?

• Optimization – Is there a way to manage capacity optimally

Attrition Management

• Early Warning Indicator - Can I predict which of my high performers are going to leave six months before they walk out the door?

• Retention - What are the most high impact and cost effective retention measures?

Business Planning & Engagement

• Workforce Management - What will be my workforce demands 1 year from now? (Both quality and quantity)

• Engagement - How can we engage and retain our top talent

People Development

• Promotion - Who out of my current workforce is most likely to be the next in line for a leadership position?

• Leadership Pipeline - What is the profile of a leader who can take the organization ahead 5 years from now?

• Training - How do we select the right employees for training and maximize ROI

An Employee Success Probability Score based on historical data

can help us get an idea of the probability of success in the

organization at the time of hiring.

Dipping levels of engagement is one of the early signs of an

impending addition to the attrition score

Workforce Management tuned in with business requirements is

an essential cost management tool and is essential for optimal

utilization of resources

Identification of the critical employees and grooming them to

be ready for leadership positions is an arduous task

Why do we need HR Analytics.. Large amounts of scattered HR data over the years is a treasure trove of information. We can look at answering business

problems like the following…

Shift of key HR decisions from gut feeling to actual and logical criteria derived out

of organizational data

What do we Offer Reporting in the HR space has evolved over the years and we find a continuum across various kinds of organization

JIFY Pro

JIFY Advanced

JIFY Lite

• Distilling all sources of employee data

• Analysis of existing trends and variations

• Identification of metrics and linkages

• JIFY Lite Features +

• Causal analysis & relationship between key metrics

• Model Building to identify key success parameters

• ESP (Employee Success Propensity Score)

• JIFY Advance Features +

• Predictive Analysis and Scenario Planning

• Keys to business problems around Recruitment, Attrition

Management, Business Planning & Engagement, and People Development

HR challenges vary from one organization to another. Our products are designed

to maximize impact depending on the maturity of the HR ecosystem

JIFY Lite Reporting in the HR space has evolved over the years and we find a continuum across various kinds of organization

0%5%

10%15%20%25%

5-8 lk 8-12 lk lessthan 2

3-5 lk 2-3 lk 20-35lk

12-20lk

Compensation Distribution - Age Wise

28 - 30 Years 31 - 33 Years

34 - 39 Years 40 And Above

Less than 28 years

32%

2%

38%

Performance Distribution

0%

5%

10%

15%

20%

25%

30%

16 to 25 Above 25 Less than 9

high Low medium

0%2%4%6%8%

10%12%

Age Distribution across Functions

28 - 30 Years 31 - 33 Years

34 - 39 Years 40 And Above

Less than 28 years

11%

12% 3% 7%

46%

21%

Manpower Distribution Across Functions

Finance &Accounts

HR, Admin &IT

Liaisoning

Maintenance

JIFY Advanced Causal analysis of data generated with JIFY Lite will be used to report key scores for each individual in the organization

Employee Loyalty Score

• For prospective candidates and can be used at he time of hiring

• Causal analysis of data generated with JIFY Lite • Model building to come up with key success

parameters • Reduces possibility of a misfit

Employee Success Propensity

Score (ESP)

• Showcases the probability of the success of a candidate based on details in the resume

• Use established measures of employee performance at a workplace to screen and hire candidates better.

• Provide an objective reference that will complement a subjective candidate assessment.

• Can be used for prospective candidates and existing employees as well

0

1

2

3

4

5

Attrition Heat Map

Compensation

Immediate Manager

Career Growth Challenging Job

Office Culture Early Warning Score (EWS)

• For existing employees in the system • Identification of key anchors for probable attrition • Weightages of anchors will vary for each employee • EWS can be refreshed on a periodic basis to check the

pulse of the organization

JIFY Pro Take informed Business Decisions using predictive analytics based on logistical regression.

Manpower

Planning

Is there a way to

manage capacity

optimally

What will be my

workforce demands 1

year from now?

Attrition

Management

How do I provide for

corrective

improvements to

control anchors of

attrition, i.e. nature of

hike, designation and

benefits.

Can we assess the

potential impact of a

new HR policy to be

introduced?

People

Development

Who are my future

leaders and what

development do they

need.

How do I maximize

the training ROI for my

organization

Decision making based on actual historical data and probability of similar trends

in future - HR Analytics is the answer

What Makes us Different

UNIQUE

SCORING

MECHANISM

Varying levels of output caters to your specific

level of HR readiness

KNOWLEDGE Globally experienced team delivering high

productivity consulting to Corporates

TECHNOLOGY Availability of cutting edge technology experts on

a regular basis

PRODUCTIVITY Deployment & management of productivity

enhancing HR output for businesses

What We Deliver

1 Reduced Cost of Decisions taken by the HR team and

increased impact on the organization

2 Increased Productivity with decisions being taken on real

time organizational data and not on gut feel

3 Higher impact of any changes in the HR policies / targeted

attrition mitigation mechanisms to minimize high performer

exit

4 Increased effectiveness of the HR team without additional

time and effort

Case Study : ESP for a Real Estate Major

The ESP Score is being used in the hiring process. Outlier data will be used over a

period of time to strengthen the model performance

Model Development Process

1 2 3 4 5

Creation of Variables for

Model Development

• Evaluate variables,

measure correlation,

check distribution &

shortlist high impact

variables

• Check variables against

other data and test cases

identified

Build Univariates

• Model type: Binomial

logistic regression

model

• Outcome = Prediction

of event occurrence i.e.

possibility of high

performance

Checks & Balances

• Model success rate =

60% high performance

prediction

• Model tested against

different sets of data

• Effectiveness of the

model can be increased

with more data points

Individual &

Organizational

Variables

• Individual Parameters

- Age, Cumulative

Experience, Time in

organization,

Educational

Background

• Organizational

Parameters -

Function,

Compensation, Team

size, Manager

behavioural

competencies,

Designation,

Promotion history

Identify Evaluate Build Check Sample Data

Sample Design and

Sample Data Creation

• Identification of

consistent sets of data

fields across the years

of test data

• Removal of Outliers to

reduce skew of data

• Cleaning up of data to

minimize errors due

to manual intervention

Case Study : ESP for a Real Estate Major

• Customised, easy to use spreadsheet.

• Can be built for multiple concurrent usage.

Business & Consulting

Data Science & Technology

Team

Deepa Krishnaswami (DK): 10+ years experience in developing & deploying analytics solutions across domains. Has lead

analytics projects across top 10 players in IT, Life Sciences, BFSI & consulting domains. Recipient of prestigious Gates

Cambridge scholarship, DK holds a Masters from Cambridge University, London, a research masters from Rice

University, Houston Texas and a bachelors from Stephens, Delhi University (Gold medalist)

Srikant Rajan (SR): Strategy expert with 8+ years of experience in strategy development, project management, business

development & marketing. Set up initiatives of digital learning, social media usage at IIM Bangalore. SR leads client

engagements & conceptualizes insights & solutions to be developed & delivered. (B. Tech & MBA)

Dr. Suneel Sharma (SS): Professor-in-charge Big Data & Visual Analytics, & heads High-Technology professional

Programs at SP Jain School of Global Management. With degrees in Engineering, Humanities, Science, Education &

Business Administration from BITS-Pilani, IIM-Bangalore, Stanford University & Lancaster University, SS provides

strategic insight & direction to all projects.

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Kavya Kandhala (KK): Database & programming expert, KK sets up systems to extract & manage data. Proficient with

SQL, PHP, HTML, & JavaScript.

Mr. KS Praveen (KSP): Founder & CEO of Human Touch & chief-editor of ‘People Pulse’ a premier HR Magazine. KSP

has over 2 decades of experience in companies such as Aditya Birla Group, Hitachi, & Siemens. KP serves as visiting

Faculty in many B-schools and is also a people coach and advisor. KSP acts as a domain expert & advises on the

functional relevance of data analytics & new model developments/improvements.