1.
Building Next-Gen HR
Solutions with People
Analytics

2.
Housekeeping
• Webinar recordings and slides will be shared
with all attendees
• Type in your questions and comments using
the question pane on the right hand side
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3.
Presenters
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Lalit Kumar
Business Analyst
Harbinger Systems
Gautam Mainkar
Data Analyst
Harbinger Systems

4.
Agenda
• Modern day HR solutions
• Need of People Analytics
• People Analytics: role and implementation
• Use cases:
– How people analytics improved the talent acquisition quality while
significantly reducing the effort needed?
– How an established organization bridged the skill set gap and
improved the employee engagement in training programs by using
people analytics in decision-making?
• Q&A
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5.
Evolution of HR Solutions
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No
Specialized
Tools
Specialized
HR Tools
Integrated
HR Systems
What's
Next ?

6.
Modern Day HR Solution : How Does it Look?
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Cloud Based Social Media
Integrations
Analytics
3rd Party
Application
Integration

7.
Modern Day HR Solution: What does it do?
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Automates
Information
Sharing
Automates
Processes
Automates
Clerical Work
Automates
Reporting

8.
HRManagerEmployee
Modern Day HR Solution: What it does not do?
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• Does not aid in decision-making
Fill Review Form
Receives Promotion
Promotion
Provide Ratings
Gives Org Feedback
Define Role
Validates
Record & Calibrates
Rating
End
No
Yes

9.
Decision Making is a Bottleneck
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• More examples:
– Identifying employees at flight risk
– Select right employees for training
• Decisions based on experience, pre-set rules, precedent
and intuitions
• Decisions made with incomplete information
• Processes lack transparency
• Knowledge base is not easy to share

10.
People Analytics: Enabling Data-Driven Decisions
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• People analytics leverages data to help decision-making
• Lots of data is available:
– Internal Source: HCM System Databases
– External Sources: LinkedIn, Glassdoor, GitHub
• Systems covering entire life-cycle

11.
Analytics
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Analytics in HCM Stack
Dashboard Report KPI MetricAAR
Recruitment
Learning Management
Benefits
Payroll
Workforce Planning
Leave Management
Reporting
Predictive
Reactive
Sales Data Operational
Data
Business Logic
Data layer
Presentation
HCM Data External
Data

12.
Role of People Analytics
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Tactical to strategic roleCloser integration of HR Functions with
core business functions
Evidence centric decisions Actionable, driven by result
methodology

13.
People Analytics: Extract Insights from Data
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• HR data hides tremendous amounts of insights:
– Trends, patterns, causal factors, behavioral insights
• Insights from data can be used to make decisions:
– Reporting
– Reactive analytics
– Predictive analytics

14.
Methodology: Types of Problem
• People analytics problems can be reduced to:
– Clustering
– Regression
– Classification
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15.
Clustering Problem
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16.
Regression Problem
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17.
Classification Problem
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80% Promoted 30% Promoted 20% Promoted 5% Promoted
Tenure Experience
Performance Rating
All Employees
>7
>3 <3 >10 <10
<7

18.
Methodology
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Identify data required
Identify data sources (internal
and external)
Define algorithms and tech
stack
Verify quality of results

19.
Use Cases
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20.
How people analytics improved the talent acquisition quality
while significantly reducing the effort needed?
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21.
Candidate Profiling and Sentiment Analysis
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Scenario
Company uses recruiting software to hire talent
Candidate profiling and credentialing is done manually
Time consuming process and prone to human bias
Need an intelligent filter to facilitate recruitment process
Data
Candidate Data : Candidate CV, LinkedIn Profile, GitHub
Profile, etc.
Requisition Data: Educational Qualification, Experience,
Roles and Responsibilities
Solution Benefits
Text analysis to compare CV and social media profile
against job description
Sentiment analysis on feedback received about candidate
to evaluate strength and weakness
Improved decision-making as candidate evaluation is
more objective
Significantly reduced manual efforts making
recruitment workflow more efficient

22.
How an established organization bridged the skillset gap and
improved the employee engagement in training programs by
using people analytics in decision-making?
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23.
Improved Employee Engagement in Training Programs
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Scenario
Company runs training programs for all employees
Employees are chosen for training program based on
manager recommendations
Choice of employee is not well adapted: Organization faces
talent gap
Data
Solution Benefits
Employee Data: Demographic, Skills, Educational
Background, Experience
Job Roles Data: Designation, Roles and Responsibilities,
Used clustering algorithms to create employee segments
Identified characteristics and training needs of each
segment
Create recommendation system to identify employees to
be enrolled in a training program
Improvement in design of training programs
Training objectives more aligned to organizational needs
Employee engagement in training programs is improved

24.
Conclusion/Summary
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• People analytics: an emergent field with huge potential
• No substitute for HR people: engaging with employees
on a personal level is still crucial
• Helps HR professionals make strategic decisions about
their people

25.
Q&A
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26.
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