Project Management Competency Assessment Using AI Models- PMO Sydney Meetup

1. April 2020
PMOs’ Hacking COVID-19
Project Management Competency
assessment using AI models
Project 11
https://pmoga.world/pmohackathon/#1587387782914-b2374c83-0e07

2. Gaurav Dhooper is a strategic thinker, a seasoned program manager, a certified
professional Agile and IT Delivery Leader, an author and a speaker. Gaurav writes
articles on Digital Transformation, Agile Transformation, Agile Project Management and
Scrum. He also writes articles on Robotic Process Automation, Artificial Intelligence,
Machine Learning and Personal Agility in leading online publications.
Gaurav has been reviewer for PMI’s Standard for Earned Value Management and a book
on Agile Contracts. Gaurav has been recently appointed as the new Digital Media Global
Director of PMO Global Alliance and been awarded an honorary position of Senior
Official of IAPM, Switzerland for Metropolitan area of Noida, India.
LinkedIn:
https://www.linkedin.com/in/gaurav-dhooper-pal-i®-pmi-acp®-safe4®-csm®-lss-gb-b871a5a/
Email:
gauravdhooper@yahoo.co.in
About the Speaker

3. In this VUCA world, there needs to be strong and adaptable competencies
required for people working in the Project environment. The project
management competency drives the project success and realizes the business
benefits.
The project manager and the project teams need to have a system which allows
to predict and assess various hard and soft skill competencies. The system
should also allow measuring such competencies against well-accepted standards
and can be improved via training and development.
Problem Outline

4. To develop a predictable and adaptable competency framework for smooth
project execution. The Project Manager Competency Development (PMCD)
Framework from PMI® defines the key dimensions of competence and
identifies the competencies that are most likely to impact project manager’s
performance. The PMCD Framework provides an overall view of the skills and
behaviors one would need to develop competence as a project manager and
utilize it for building enterprise wide competence.
Project Summary/Solution

5. To create an AI-based Project Management Competency Assessment platform
to asses everyone who is involved in the projectized environment, to know their
strengths, their challenges, as well as talent gap for an individual and
organization collectively. Various classification (supervised learning), clustering
(unsupervised learning) machine learning techniques along with Sentiment &
behavioral analysis (reinforcement learning) will be used to assess the cognitive
and decision-making abilities in the PMCD framework.
Project Objectives & Solution
Approach

6. Since there are situations where PM competency cannot be assessed simply in
black and white, there is a need for AI models to reflect the actual performance
and predictability. Assessment could be in the form of Personal competence,
Performance competence and Knowledge competence
KPIs will be required around the following major components of competencies:
• Abilities
• Attitudes
• Behavior
• Knowledge
• Personality
• Skills
Business Needs

7. The AI based PMCD Framework assessment will provide a measurable overall
view of the skills and behaviors one would need to develop competence as a
project manager and a project-based organization. It will also help in analyzing
existing skill level and identifying the potential talent gaps proactively that may
require additional training or education for effective execution of projects and
decision-making. AI based model will help improve the current value and ability
to innovate.
Business Value

8. The scope of the project will be around the following three dimensions:
- Project Management Knowledge Competence - what the project manager
knows about project management
- Project Management Performance Competence - what the project manager
can do or accomplish while applying project management knowledge
- Personal Competency - how the project manager behaves when performing the
project or activity; their attitudes and core personality characteristics
Project Scope
Source: https://www.pmi.org/learning/library/project-manager-competency-development-framework-7376

9. The following items are in-scope :
- Simple Q&A normally involving Yes/No answers- Data is
labeled and classified
- Scenario Based Multiple choice question- Each answer will
reveal different level of competency- Data is again classified
and labeled.
- Interview based Questions- Answers will be subjective and
unstructured. The data is not labeled and there is no specific
pattern. For example, in order to check the effectiveness of
creating a project charter or any other artifact, simple answer
in the form of “Yes” or “No” will not work. AI based
assessment model will help in evaluating this type of
competency for a PM through text analysis.
In Scope

10. 1. Assess Performance : Involve self-assessment and Assessment at Org Level
2. Plan Competence Development: Prioritize and establish timeline
3. Conduct PM Competence Development: Execute and Monitor
Project Key Activities

11. 1. Deliver AI based statistical solution for assessing PM Development
competency allowing faster prediction and decision-making.
2. Following List of KPIs will be delivered:
Knowledge Indicator Level, Skills Rating, Personality Rating, Employee
Turnover Rate, Employee Satisfaction, Customer Satisfaction, Teamwork,
Motivation level, Commitment, Loyalty, learning ability, Adaptability,
Ability to create SMART goals, Implementation Effectiveness of PM
principles and practices, % of successful delivered projects, Business Value
related Metrics
Deliverables

12. 1. Importance of collaboration & collective intelligence for improved outcomes
2. Role of Performance Assessment for building capability
3. Identification of potential gaps in the competence levels
4. Proactive actions for improving the PM competency
5. Effective project execution and governance for delivering continuous value
Lessons Learned

13. Tutor: Mario Trentim
Mentors: Kartikeyan Ramamurthy , Mani Selvan Nadarajah, Turki Altamimi,
Gaurav Dhooper
Project Leader: Mani Selvan Nadarajah
Team Members: Abdallh Omran, Adama Bakayoko, Asmaa Osman,
Emmanouil Papadakis, Evgeny Saltykov, Laurie Ferrier, Magda Lungan,
Nourah Alhilal, Vipul Jindal
Project Team

14. Use case- Knowledge Indicator Level for Interview Based Questions
Team Size (2)- 1 Designer/Modeler, 1 Developer
 Requirement Gathering & Feasibility Study- 1 week
 Modeling and Creating MVP- 3-4 weeks
• Identify & Analyze the problem
• Collect & Prepare data - Get Data, Clean & Prepare Data, Train Model, Test Data, Improve
• Choose the algorithm(s) - Supervised, Unsupervised and Reinforcement Learning
• Train the algorithm(s) - Input data into model
• Choose a particular programming language/tool- ML as a service, Cloud-based, data pre-
processing, model training, evaluation prediction
• Run on a selected platform
 Testing & Roll Out- 1 week
• Acceptance testing
• Production testing
MVP Project Plan & Resourcing

15. April 2020
PMOs’ Hacking COVID-19
Remote Working for Dummies
Project 26 - Conceptual Phase
April 2020
Thanks