This document discusses using people analytics for a sustainable remote workforce. It outlines how people analytics can help frontline managers with decision making, monitoring operations, productivity, safety and recruitment using metrics from applicant tracking systems. It also discusses the challenges faced by Chief Data Science Officers in areas like data wrangling, mature AI operations and building skilled teams. Emerging technologies around hyperautomation, internet of behaviors and total experience will facilitate real-time analytics and seamless workflows across HR and collaboration tools to drive business outcomes.

1. Using People Analytics for a Sustainable Remote Workforce
Mar 17, 2021
Shrikant Pattathil
President
Harbinger Systems

2. ─ Understand market shifts in People Analytics and the Future of Work
─ Learn about the challenges faced by Chief Data Science Officers(CDSO)
─ Bridge the data chasm between HRTech and WorkTech applications
─ Leverage emerging technology and design trends to deliver better analytics
By the End of this Session, You Will be
Able To…

3. Market Shifts in
People Analytics and the
Future of Work

4. • Create a Culture and Strategy
around data
• Focus on outcomes as opposed to
record keeping
Features of a
Data Driven Org.

5. Data Analytics for Front Line Managers
• Better HR decision making
• Using data to monitor operations
Productivity
Employee Safety, Employee
Wellbeing
Recruitment

6. Workplace Analytics Maturity Model
Level 1 – Operational Reporting
Level 2 – Advanced Reporting
Level 3 – Advanced Analytics
Level 4 - Predictive Analytics
ATS Talent Learning Payroll HRIS Emp.
Engagement …
n

7. Example – Metrics in Applicant Tracking
Time to fill Time to hire Source of hire
First-year
attrition
Quality of hire Cost per hire
Application
completion rate
Vacancy rate Fill rate
Applicants per
hire
Qualified
candidates per
hire
Time in workflow
step
Pass-
through/Convers
ion rate
Reach for hire
Yield ratio Source quality
Offer acceptance
rate
Hired to goal
Candidate Net
Promoter Score
- Most of metrics (12 out of 19) are primarily dependent on data generated by ATS
- Some dependency on Job Boards, HRIS(TM) and Payroll

8. Challenges faced by
Chief Data Science
Officers

9. Relevant CDSO Hot Buttons
Data Wrangling
(Scalable ETL)
Mature AI Ops
(Lab to Production)
Skilled Team
(Diverse Skills –
AI/ML, Design, Cloud,
Mobile)
CHRO Expectations From Data
• Predicting workforce availability
• Guiding whether to hire new or reskill
existing workforce
• Effectively moving to a remote work
model that is productive
• Need for faster AI-driven processing
of diverse data type (like raw data,
images, videos)
And more…

10. Problems and Solutions
Data Wrangling
Build an ETL or ELT(s)
strategy – work with
structured and
unstructured data
Mature AI Ops
Update and scale AI
components and ML
models from prototypes
to production cloud apps
Skilled Team
Form a team of data
scientists, data
engineers, cloud
engineers and UI
designers

11. The Data Chasm -
HRTech and WorkTech

12. WorkTech- Span of Data Sources is Multiplying
Productivity
Collaboration
• Faster action on HR tasks
• Nudge Learning
• Distributed workforce
management
HRTech
• Measuring Learning and
Training Effectiveness
• Correlating Productivity with
Engagement
Workday & Salesforce
Partnership for better
productivity, and back to
work solution
Microsoft & Workday
Partnership for Teams and
Azure integration
Harbinger’s WorkTech View

13. Focus on Business Outcomes
HRIS Systems
Drive Outcomes
(guided decisions)
Integrations Data Warehouse
Data Lakes
Increase Efficiency
(speed)
Increase
Effectiveness
(cost realizations)
Recruitment Systems
Productivity Systems
Collaboration Systems
…

14. Emerging Technology
and Design Trends

15. Tech Trends Impacting Future of Work
Hyperautomation Internet of Behaviors Total Experience

16. • People Analytics will be a key requirement for organizations
focused on data-driven decision making
• People Analytics should extend beyond HR platforms to
Collaboration and Productivity tools
• CDSO Pain points (scalable ETL, lab to production, skilled team)
• Emerging technologies like Hyperautomation, Total Experience
and Internet of Behaviors will facilitate real-time data analytics,
seamless workflows and rich user experience
Takeaways

17. hsinfo@harbingergroup.com
THANK YOU!​