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Transcript of HR Analyticshumantouchhr.com › wp-content › uploads › 2018 › 02 › Services-Peop… · HR...
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.