Machine Learning has been increasingly adopted by recent technology-based organizations aiming at achieving the competitive advantage among its competitors and move towards their future aspects of the digital needs that may come in future. As machines are replacing the human jobs and place of work is becoming more remote, the growing organizations must also revolutionize its traditional methods of leadership and it's KPIs (Key Performance Indicators) that are greatly influenced by Machine Learning. Machine Learning helps the leaders to understand and predict the performance rates of the workers with pre-loaded data of the performance to know the future brings a greater potential to the virtual leadership itself.

1. Simi Paxleal Jaiwant Simon (2003548 and 16)
Future of Organization
on Virtual Leadership

2. Thursday, April 30, 2020Machine Learning Influence on KPIs of Virtual Leadership 2
Proposal Idea
Digitalisation on Organization
Virtual Leadership using traditional methods
KPIs influence on Virtual teams
Virtual Leadership problems
Virtual Leadership formulate KPIs within companies

3. Agenda
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Future of the Organisation
Changes within Management
Outcome of Change by 2025
Unknown and Beyond

4. Thursday, April 30, 2020 Machine Learning Influence on KPIs of Virtual Leadership 4
Future Organisation
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Global service driven teams
Transformational Virtual leadership
Algorithmic values of Performance
Metrics on Quality of KPIs
Machine capability and Human intelligence
co-exist

5. Digitalisation Possibility
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1 Artificial intelligence and technology
2 Pace of change
3 New talent landscape
4 Purpose and meaning
5 Morality, ethics and transparency
6 Globalization

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Global monitoring
Virtual leader recruitment
Global industrial village
Connected workforce
Democratize learning
Conflict of EI and IQ
Flatter structure
Innovation Success

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1
Machine Learning
Ability to auto-learn explicit programmed
2
Virtual Leadership
Telecommute/ work globally
3
Virtual Team Implementation
Geographically dispersed team
4
VTMM – Maturity Models
Effective Virtual Working Habitat
5
VTMM KPIs
Virtual Team Key Indicators of Performance
6
Performance Management
Formulate the methods to calculate
performance values
7
Data Gathering
Collecting values of Performance
8
Update AI
Humanoid leadership by machine
How changes?

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Virtual Management Framework Increase in Global Competition
GOAL VERSUS OBJECTIVE
Recruitment of Virtual leaders Use highly-multi skilled individuals
Upgradable Virtual Leader knowledge Adapt to change in Virtual leadership
Design KPIs of Virtual teams For a Long run Vision and Mission
Optimize Virtual Leader to Virtual Teams Skilled to monitor virtual team needs
Create KPI value measurable Data Collection - Employee work

9. Tools and Resources
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Virtual Leaders VTMM
KPIs valuesVT with ML
Over come challenge of
global virtual team
management
Social loafing, Adapt change and
response and assessment within
team using Machine Learning
• Data Gathering - Scikit-learn function,
Multi-Output-Regressor, X regressors
• Data by The Balance Scorecard
Organize Get-to-know-
each other Framework
Process

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Huddly
Case
Study
Overview Virtual team
Framework
VTMM Process

11. Outcomes / Plans
• Practicality of the Global Virtual
Teams
• KPIs value from VTMM
• Easy calculation of Virtual Team
Performance using ML and AI
• Ease to collect data and update
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12. SWOT Analysis…
Strengths and Opportunities
• VTMM adds value to team performance
• Practicality of Virtual framework
• No to Travel Expense
• Global Employee Recruitment
• KPIs and Payroll calculation - Error Free
• Optimisation Virtual Leadership and Upgradable
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13. …SWOT analysis…
Weakness and Threats
• Language Barrier/ Internet Disrupts
• Difficult to train new teams with physical assistance
• Needs effective Communication and Rapport within teams
• Conflict of decisions in large virtual teams
• Wrong data in the ML/AI – Virtual setup compromised
• Algorithm malfunction when decision/goals between virtual leader
and virtual team members mismatch
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14. Reference
• DBKAY & ASSOCIATES 2003. A Balanced Scorecard for Customer Support Building the Business Case for
Improving Problem Resolution.
• POOLE, M. S. & VAN DE VEN, A. H. 2004. Handbook of organizational change and innovation, Oxford University
Press.
• P. Domingos, “A few useful things to know about machine learning,” Communications of the ACM, vol. 55, no. 10,
pp. 78–87, 2012.
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15. For further queries
Lets discuss in forum
Or
Contact me @linkedin.com/in/simipaxlealjaiwantsimon/

16. Thank you!.