PMI Colloque en gestion de projet 2018 1 L’Intelligence Artificielle appliquée à l’analyse des risques dans la gestion des projets Bassem Monla Expert Intelligence Artificielle IBM 2. Colloque en gestion de projet 2018 2 I. Optimization of Project Scheduling: non AI Technique II. Probabilistic reasoning on tasks and schedule III. Difficulties to reason with uncertainty IV. Artificial Intelligence (AI) Bayesian Networks as a generic solution for Decision taking in an uncertain environment V. An Artificial Intelligence (AI) Bayesian Network risk model for Software Project Management 3. Colloque en gestion de projet 2018 3 Optimization of Project Scheduling There are powerful tools to optimize a Project Scheduling with limited resources using Meta-Heuristics methods . (like OptaPlanner) Non AI Technique 4. Colloque en gestion de projet 2018 4 I. Optimization of Project Scheduling: non AI Technique II. Probabilistic reasoning on tasks and schedule III. Difficulties to reason with uncertainty IV. Artificial Intelligence (AI) Bayesian Networks as a generic solution for Decision taking in an uncertain environment V. An Artificial Intelligence (AI) Bayesian Network risk model for Software Project Management 5. Colloque en gestion de projet 2018 5 Estimation of a task duration is confusing The probability distribution of a task duration is skewed. What are we estimating: Most likely (Mode), Median or Mean ? 26 % to complete before the Most Likely Source & Reference: Vose Software 6. Colloque en gestion de projet 2018 6 Project schedule risk analysis Probability distributions of the sum of Serial tasks Source & Reference: Vose Software 7. Colloque en gestion de projet 2018 7 Project schedule risk analysis Probability distributions of the sum of Parallel tasks: Tasks done in parallel take longer than estimated 26 % x 26 % = 7 %

1. Colloque en gestion de projet 2018
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L’Intelligence Artificielle appliquée à l’analyse des
risques dans la gestion des projets
Bassem Monla
Expert Intelligence Artificielle
IBM

2. Colloque en gestion de projet 2018
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I. Optimization of Project Scheduling: non AI
Technique
II. Probabilistic reasoning on tasks and schedule
III. Difficulties to reason with uncertainty
IV. Artificial Intelligence (AI) Bayesian Networks
as a generic solution for Decision taking in an
uncertain environment
V. An Artificial Intelligence (AI) Bayesian
Network risk model for Software Project
Management

3. Colloque en gestion de projet 2018
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Optimization of Project Scheduling
There are powerful tools to optimize a Project Scheduling with limited resources
using Meta-Heuristics methods . (like OptaPlanner) Non AI Technique

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I. Optimization of Project Scheduling: non AI
Technique
II. Probabilistic reasoning on tasks and schedule
III. Difficulties to reason with uncertainty
IV. Artificial Intelligence (AI) Bayesian Networks
as a generic solution for Decision taking in an
uncertain environment
V. An Artificial Intelligence (AI) Bayesian
Network risk model for Software Project
Management

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Estimation of a task duration is confusing
The probability distribution of a task duration is skewed. What are we
estimating: Most likely (Mode), Median or Mean ?
26 % to complete before the Most Likely
Source & Reference: Vose Software

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Project schedule risk analysis
Probability distributions of the sum of Serial tasks
Source & Reference: Vose Software

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Project schedule risk analysis
Probability distributions of the sum of Parallel tasks: Tasks done in parallel
take longer than estimated
26 % x 26 % = 7 % to complete before the Most Likely
Source & Reference: Vose Software

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Project schedule risk analysis
Classical Gant Chart augmented by probability incertitude
Source & Reference: Vose Software - Tamara

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Project schedule risk analysis
Classical Gant Chart augmented by probability incertitude
Source & Reference: Vose Software - Tamara

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Project schedule risk analysis
Probability distributions of the sum of Parallel tasks: Tasks done in parallel
take longer than estimated
Source & Reference: Vose Software - Tamara

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Project schedule risk analysis
Probability of Periodic cost
Source & Reference: Vose Software - Tamara

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Project schedule risk analysis
Probability of cumulative cost
Source & Reference: Vose Software - Tamara

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Project schedule risk analysis
Probability Scatter plot
Source & Reference: Vose Software - Tamara

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Project schedule risk analysis
Probability Gant chart
Source & Reference: Vose Software - Tamara

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I. Optimization of Project Scheduling: non AI
Technique
II. Probabilistic reasoning on tasks and schedule
III. Difficulties to reason with uncertainty
IV. Artificial Intelligence (AI) Bayesian Networks
as a generic solution for Decision taking in an
uncertain environment
V. An Artificial Intelligence (AI) Bayesian
Network risk model for Software Project
Management

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Difficulty to reason with Uncertainty
The taxi case.
adapted from
Kahneman &
Tversky, 1980
A taxi was involved in a hit-and-run accident at
night.
• Only two taxi companies operate in this city,
the Yellow Cab Co.
and the White Cab Co.
• 85% of taxis belong to the Yellow Cab Co.
• 15% of taxis belong to the White Cab Co
A witness says that the taxi involved in the
accident was white.
An expert witness explains that human vision
has an 80% accuracy in terms of distinguishing
between white and yellow given light
conditions at the time of the accident.

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Difficulty to reason with Uncertainty
The taxi case: A webinar poll (Reference Bayesialab)
What is the probability
that the taxi was white,
given that the witness said
it was white?
Correct answer: 41.38%
Only 30% percent of
people in the poll gave the
write answer

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I. Optimization of Project Scheduling: non AI
Technique
II. Probabilistic reasoning on tasks and schedule
III. Difficulties to reason with uncertainty
IV. Artificial Intelligence (AI) Bayesian Networks
as a generic solution for Decision taking in an
uncertain environment
V. An Artificial Intelligence (AI) Bayesian
Network risk model for Software Project
Management

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1) Marginal Probability
2) Hard evidence
3) Soft evidence
4) Reasoning / Inference
5) Indirect dependency &
Conditional
Dependency
6) Abduction Reasoning
from Lauritzen, Steffen L. and David J. Spiegelhalter (1988)
Bayesian Network (a classical example)
Bayesian networks are a type of Probabilistic Graphical Model that can be
used to build models from data and/or expert opinion.

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Bayesian Networks for Risk Management
Example of cause–consequence idiom instance joined showing multiple
causes, consequences, controls, and mitigants.

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I. Optimization of Project Scheduling: non AI
Technique
II. Probabilistic reasoning on tasks and schedule
III. Difficulties to reason with uncertainty
IV. Artificial Intelligence (AI) Bayesian Networks
as a generic solution for Decision taking in an
uncertain environment
V. An Artificial Intelligence (AI) Bayesian
Network risk model for Software Project
Management

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The full Bayesian Network Risk model for
Software Project Management
The MODIST models (Fenton et. al. 2004)

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The Bayesian Network Risk model for
Software Project Management
The model captures the classic trade-offs between: Quality, Effort, Time,
Functionality. MODIST models (Fenton et. al. 2004)
the model captures the
classic trade-offs between:
· Quality
· Effort
· Time
· Functionality

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A Bayesian Network Risk model for Project
Management. A simplified version.
A Simplified version of the MODIST models (Fenton et. al. 2004)

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A Bayesian Network Risk model for Project
Management
A The “People quality” subnet of the MODIST models (Fenton et. al. 2004)

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A Bayesian Network Risk model for Project
Management
Two scenarios in Risk Table view. Distributions when functionality delivered is
set as 'perfect' for new project. (AgenaRisk Software Project Risk Model)

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A Bayesian Network Risk model for Project
Management
Distributions when process and people
quality is 'medium' for new project.
Impact on:
1. Average number of people full time
2. Project Duration
(AgenaRisk Software Project Risk Model)

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A Bayesian Network Risk model for Project
Management
Functionality delivered if process and people quality = medium with resource
constraints set. (AgenaRisk Software Project Risk Model)

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A Bayesian Network Risk model for Project
Management
Risk Table (AgenaRisk)

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Cette présentation sera disponible sur le site web
du PMI Lévis-Québec à compter du 1er mai 2018