David Swanagon: The Future of Work = People + Machines People Analytics Conference 2022 Winter Website: https://pacamp.org Youtube: https://www.youtube.com/channel/UCeHtPZ_ZLZ-nHFMUCXY81RQ FB: https://www.facebook.com/pacamporg

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The Future of Work = People + Machines
How to leverage AI to optimize human capital performance
David Swanagon | December 9 2022
People Analytics Camp

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01 Leading Machines in the Digital Era
02 Ethical AI and the role of Data Privacy
03 Critical Skills for Future CHROs
Agenda

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The Future of Work = People + Machines
• Merger of CHRO and Chief Digital Officer
• Employee Workspace (3 Dimensions)
Physical, Hybrid, and Metaverse
• Bot as the Hiring Manager
• 75% of talent will be borrowed
• Digital Avatars for non-working hours
Emerging Trends
Success Requires an AI Driven Framework

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CHRO of the Future
Traditional HR Activities
• CEO Succession and Board Engagement
• Talent Management
• Employee and Labor Relations
• HR Business Partner for C-Suite
Data Driven Insights and Technology
• Strategic Workforce Planning (emphasizing critical skills)
• Business process design
• Neural Networks re: engagement, predictive attrition, and succession
• Machine Workforce (Bot as a Hiring Manager)
• IT Cost of Ownership—Full suite of cloud-based HR applications
25%
75%
In the next ten years, the CHRO and Chief Digital Officer roles will
merge. Talent will be fully embedded into the broader data strategy.

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Metrics that Matter
New Hire Attrition
Day 1, 30, and 90 are strongly correlated to
new employees being retained.
~5%
EPS
Learning Velocity
Percent of new learning achieved and
retained each year by employees.
~4%
EPS
Succession Plan Strength
# of Critical Roles that lack top talent has a
detrimental impact on profitability.
~7%
EPS
Bottom
Line
Impact
Many firms rely on HRBPs for root cause analysis
Many firms have difficulty tracking critical skills
Data-driven talent lists are an emerging trend
Degree of Sophistication among Fortune 500s
~16% Earnings per Share

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People Analytics follows four stages of maturity
Maturity Model [3-7 years to build]
Technical Focus:
Trend Analysis
KPI Dashboards
Leadership Skill:
Data Storytelling
Reporting
Technical Focus:
Regression
Sentiment Analysis (NLP)
Leadership Skill:
Change Management
Insights
Technical Focus:
Neural Networks
Time-Series Forecasting
Leadership Skill:
ML Ops
Predictive
Technical Focus:
Reinforcement Learning
Computer Vision
Leadership Skill:
Ethical AI Governance
Prescriptive
Most
Companies
HR Business Partner Data Scientist Sr. Data Scientist Principal Data Scientist

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Engineering/Technical Talent HR Professionals and related SMEs
Data Driven
Culture
Data Privacy and
Governance
Applied
Research
Data
Ecosystem
Automation &
Service Delivery
Dashboards and
Modeling
Programming
and Tools
Community
of Practice
Industry
Partnerships
Leadership and
Culture
Technology and
Methods
Talent And
Services
1-2 Years
5+ Years
1-3 Years
Time to Build
Evolving People Analytics Framework
Top Talent (Successor)

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Most critical skills (LinkedIn Talent Insights)
Skill Criticality Based on Market Demand
Excel
PowerQuery
Cloud
Computing
DevOps | CI-CD
Agile Methodologies
Python/R/SQL
Programming
ML Ops
HRIS Vendor Management
Tableau
Power BI
Legacy
Technologies
Neural Networks
Reinforcement Learning
Computer Vision
Storytelling (soft skill)
High
Talent
Availability
Low
Needed Critical
External Market Analysis: Data Scientist Critical Skills (example only)
Blue boxes are
the critical
skills, but most
difficult to hire
Critical Skills for People Analytics

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Consultancy
Service Delivery
Data Analytics
Data Engineering
Stakeholder Engagement
PMO/Governance
Build Models
Collect Data
Customer Facing
Technology Facing
Data Scientist ML Ops Senior Manager
Data Engineer
Demand Management
Solution Architect
Data Visualization
Engineering/Technical Talent HR Professionals and related SMEs Top Talent (Successor)
The Org Structure blends HR and STEM talent
Data Architect
Data Quality Manager
I/O Psychologist

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Ethical AI and Data Privacy are Critical Skills
Diversity, Equity
and Inclusion
Executive
Decision Making
Employee
Data Privacy
Employee
Connectivity
Regulatory
Pressures
Social
Pressures
----------- Machines Scale Human Strengths and Flaws -------------
Data Privacy is part of the Employee Experience