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Stefan Morcov
Supervisors:
Prof. dr.ir. Liliane Pintelon
Prof. dr. Rob J. Kusters
Public defence of the PhD thesis dissertation
- Readable slides -
IT projects and products are more and more challenging,
but more and more rewarding
IT projects are often complex
Projects derail, face significant challenges
Failure rates in IT are particularly high
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Standish Group, 1995:
•31% of projects are canceled
•52% of projects cost 189% the original
estimate
•16.2% are on-time/on-budget
Standish Group, 2020:
•31% of projects are successful
•50% are challenged
•19% fail
Some projects are particularly large and complex
The cost may be huge
Schengen Information System (SIS II) launched in 2013 - 6 years late, 8 times more expensive
than the initial estimate, at a final cost of €500 million
Arianne 5 rocket –exploded in 1996, due to an erroneous data conversion from 64-bit floating
point value to 16-bit signed integer, because of reusing legacy software from Arianne 4 - 370
mil Eur loss.
x-ray machine –Therac-25, 11 machines in 1982, 6 accidents, 3 deaths
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Despite all these challenges, we are doing
more and more complex IT projects and products.
The main concern of system engineering is not
how to eliminate complexity, but how to make
it work. Because complexity works (Maurer).
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The smart-phone is a very complex product, built with complex
processes.
Because of this complexity, the software crashes, the battery doesn’t
last, screens break, there are issues related to interoperability,
standardization, dependencies, privacy, security, GDPR.
But the smart-phone works.
Complexity works. Complexity is ubiquitous:all around us.
Facebook, SMS, AI, smart-cars, smart-phones:
examples of technology used differently than
intended.
Sometimes we don’t even understand exactly
how this technology works - but it does.
Facebook is different than the sum of its
components. Changing the brand to Meta adds
even more complexity, which they embrace.
Extraordinary impact of technology in Covid-2019
society. Our world changed and adapted. Faced
with new challenges, we started to use
technology in new ways. We are not limited by
skeumorphism = mimic the physical world.
Instead we change the way we collaborate and
communicate.
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Complex projects create complex products, for complex markets,
in complex organizations, with complex processes.
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Complexity works.
Modern IT engineering
uses complexity
to deliver value,
benefits, functionality.
Goal: contribute to the understanding and management of complex IT
projects
◦Enterprise and IT governance: why, how, alignment
◦Why are we doing these complex IT projects?
◦How to deliver them succesfully and aligned with organizational goals?
Objective: Design, validation, and evaluation of a set of tools for the
identification, analysis, and management of IT project complexity
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•Constructivist philosophy
•Qualitative, iterative approach.
•Design science –Wieringa.
•Typical for solving wicked problems, and
engineering problems
•Validation: in a theoretical, laboratory setting
•Checking if the artifacts support the initial
assumption
•Equivalent to Technology Readiness Level TRL 4
•Evaluation: after actual deployment/
implementation in practice, in relevant industry
environement
•Equivalent to TRL6
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Sub-projects have intermediary
objectives
◦resulted in published papers.
P1: Investigation
P2: Theoretical foundation. Choices
regarding our approach to IT prj.
complexity
P3: Framework to support
◦Structured approach to IT project
complexity management
◦Anchoring new tools
◦Inventory of tools; identify gaps in the
inventory
P4-P5: Design, validate, deploy and
test in practice the proposed tools
and concepts
◦2 design-cycles and 1 engineering cycle.
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Sub
-project
Research questions
. Results hightlights
Chapter
Published results
P1.Investigation.
Systematic
literature review
RQ1. Definitions and approaches
RQ2. Characteristics
RQ3. Identification & measurement tools
III
(Morcov, Pintelon, &
Kusters, 2020a)
P2. Theoretical
foundation
RQ4. Appropriate theoretical
foundation/approach.
Positive, Negative, & Appropriate Complexity
IV
Published as part of
P4
P3. Framework
design
RQ5.
IT-PCM Framework
support
ing the tools design & deployment
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(Morcov, Pintelon, &
Kusters, 2021a)
P4. Tools
design
-and-
validation
RQ6. Tools for complexity identification,
analysis, management:
Complexity Effect Scale
–CES
Complexity Source/Effect Segmentation Matrix –
COSM
Mitigation Strategies Matrix
–MSM
Complexity Register
–CoRe
VI, VII
(Morcov, Pintelon, &
Kusters, 2020b)
P5. Practical
evaluation
RQ7. What is the contribution of the designed
tools to project success
VIII
(Morcov, Pintelon, &
Kusters, 2021b)
“Difficult to understand, foresee and keep under control, even
when given reasonably complete information about its
components.”
Structural complexity: complicated.
Consisting of many varied
interrelated parts
Dynamic complexity: ambiguity, uncertainty, propagation,
chaos
◦nonlinearity, complex feedback loops, emergence,
adaptiveness
◦Significant impact of small factors: Lorenz’s Butterfly
effect 1963, Ray Bradbury’s A sound of Thunder 1952.
◦and of very rare events: Taleb’s Black Swan
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Complex
Difficult
Large
Complicated
Unmanageable
Fashionable
Fancy
Baroque
Significant ambiguity in
the terminology
and in the domain
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Management effort: Low
Exponential
Aristotle Euclid
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A complexity of complexities
P2. Holistic view
A complex project system is formed
of complex project sub-systems.
These interact with each other and
generate effects such as
propagation.
Internal vs. external complexity.
Ethical, legal, regulatory,
compliance sub-system.
(based on Maurer’s complexity domains)
In contemporary research and practice , project complexity is always negative –a purely
pessimistic perspective
The only recommended strategies for complexity management are reduce, decompose,
eliminate complexity, simplify, divide-et-impera
This approach misses out on opportunities
New perspective:
Positive complexity is the complexity that adds value to our project, and whose
contribution to project success outweighs the associated negative consequences
Appropriate (requisite) complexity is the complexity that is needed for the project to
reach its objectives, or whose contribution to project success balances the negative
effects, or the cost of mitigation outweighs negative manifestations
Negative complexity is the complexity that hinders project success”.
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Innovation, creativity, adaptiveness have always been related to complexity.
Innovation occurs at the edge of chaos.
Systems must be taken outside equilibrium to innovate (Stacey, 1995)
Systems acquire complexity to evolve & survive (Beer, 1972)
Opportunities in the chaotic domain for decision-making (Cynefin, Snowden)
Law of requisite complexity/variety –cybernetics: in order to remain viable, systems must
increase their internal complexity to match and exceed the complexity of the external
environment (McKelvey & Boisot, 2009)
Antifragility: new approach, contrasting with the traditional resistance + resilience
approaches to vulnerability management (Taleb, 2012)
Similar to opportunities in risk management (in PMBoK since 1996)
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the project management Knowledge Area that includes processes to
understand, plan strategy and responses, and manage project
complexity
It supports project success, by
◦enhancing Positive Complexity
◦reducing Negative Complexity
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•5 processes
•Inputs, outputs, tools and techniques
•1. Plan: red-flag complexity - initial
complexity assessment
•2, 3. Analysis: dependency modeling,
detailed analysis
•4. Actions
•5. Monitor, control, evaluate
•Main tool for dynamic complexity:
monitor for change
•Inventory of available tools + gaps
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◦Configuration management
◦Change management
◦Dependency (DSM, DMM, MDM) & traceability matrix
(requirements, stakeholders, changes) (Maurer 2017)
(Marle&Vidal 2016)
Multiple Domain Matrix (MDM)
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Effects
Sources
Positive &
Appropriate Negative
Internal
Reusability *)
Many varied inter-
dependent
technologies
External
Large budget,
political priority.
New technologies.
Unclear objectives –
scope agility
Large number and
variety of
stakeholders.
Unclear objectives
*) Examples
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Response strategy
Complexity Effect
Positive Appropriate Negative
Create, enhance x
Use (exploit) x
Accept / ignore x x x
Simplify / reduce x
Avoid / eliminate x
“In order to be useful, any tool must generate actions”.
Tools deployed, tested and evaluated
repeatedly over several months
◦5 live IT projects
◦18 participants
◦7 months
◦Video recorded interviews
◦Text analysis
Focus on qualitative and negative
feedback.
Why, when, why not, how
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EPALE is the pan-European,
multilingual, open membership
community of adult learning
professionals and policymakers
European Commission project
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Solution:
Collaboration and eLearning portal, mobile app.
(Drupal, Open Europa, Moodle, AWS)
Content, hosting, maintenance, operation
Management of the EU Central Support Service
Coordination of 38 National Support Service centers,
community management
Communication, social media,
large-scale events
Stakeholders:
5 Directorates and Agencies of EC
National authorities
Consortium of 2 partners
Various subcontractors
Central Support team
38 National teams
4000 participants attended the
Annual Conference 2020
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Hass tool
Cifter tool
Strong support to red-flag
complexity.
Strong support for action plan
/ MSM.
Lower scores from top-mgmt
for introducing new tools, due
to overhead
Recommendation: combine
complexity and risk mgmt.
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Fit-for-purpose: only projects “red-flagged” as complex should receive
special treatment
Any tool to support understanding is important
Checklists and templates needed
Tools should be deployed as early as possible
Risks and complexity management overlap, but are also complementary
The importance of awareness
Positive complexity supports focusing on opportunities
Complexity generates risks, but also risk generates complexity
◦Positive complexity generates opportunities
◦Negative compl. generates risks
Risk is reactive, focused on external events, like vulnerability mgmt.
◦Risk mgmt. doesnt analyse internal behaviour or structure
Complexity focuses on the system. It is proactive.
Risk & complexity are complementary, should be applied together
The importance of awareness: choosing the right tools
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Review of the state-of-the art
◦Common language. Structured literature review (RQ1-3)
◦Inventory of approaches, classifications, measures
Insights, new perspectives on complexity
◦Positive, Negative & Appropriate Complexity. Holistic model (RQ4)
◦IT Project Complexity Management. IT-PCM Framework (RQ5)
Practical tools
◦Measurement tool
◦Complexity Effect Scale –CES
◦Complexity Source/Effect Segmentation Matrix –COSM
◦Mitigation Strategies Matrix –MSM
◦Complexity Register –CoRe (RQ6-7)
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Theoretical and practical contributions
No golden bullet or universal solution
◦These tools will not provide a magic solution to project complexity
◦Implementation of management tools is context-dependent
◦Inventory cannot be exhaustive nor definitive
Qualitative research / design science is a journey,
formed of trial-and-error cycles
◦The roles of academic and consultant often overlap
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The proposed tools aim to support
◦recognizing, understanding, managing complexity in a structured way
◦prioritizing projects, resource planning
◦reducing risks, increasing project success rates
Complexity is a ubiquitous reality in modern engineering &
management
◦It generates risk, but also creates opportunities.
Modern IT engineering uses complexity to deliver value
◦Positive & Appropriate complexity can act as catalysts for opportunities
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Morcov, S., Pintelon, L., & Kusters, R. J. (2021). A Practical Assessment of Modern IT Project Complexity
Management Tools. International Journal of Information Technology Project Management
Morcov, S., Pintelon, L., & Kusters, R. J. (2021). A Framework for IT Project Complexity Management.
IADIS IS 2021 (pp. 61-68)
Morcov, S., Pintelon, L., & Kusters, R. J. (2020). IT Project Complexity Management Based on Sources
and Effects: Positive, Appropriate and Negative. Proceedings of the Romanian Academy - Series A,
21(4), 329-336
Morcov, S., Pintelon, L., & Kusters, R. J. (2020). Definitions, characteristics and measures of IT Project
Complexity - a Systematic Literature Review. International Journal of Information Systems and Project
Management, 8(2), 5-21
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Baccarini, D. (1996). The concept of project complexity, a review. International Journal of Project
Management, 14(4), 201-204
Benbya, H., & McKelvey, B. (2006). Using coevolutionary and complexity theories to improve IS alignment: a
multi-level approach. Journal of Information Technology, 21, 284-298
Lorenz, E. N. (1963, March). Deterministic Nonperiodic Flow. Journal of the Atmospheric Sciences, 20(2),
130–141
Marle, F., & Vidal, L.-A. (2016). Managing Complex, High Risk Projects - A Guide to Basic and Advanced
Project Management. London: Springer-Verlag
Maurer, M. (2017). Complexity Management in Engineering Design –a Primer. Berlin, Heidelberg: Springer
PMI. (2017). PMBOK Guide
Snowden, D. J., & Boone, M. E. (2007, Nov.). A Leader’s Framework for Decision Making. Harvard Business
Review, 85(11), 68-76
Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House
Taleb, N. N. (2012). Antifragile: things that gain from disorder. New York: Random House
Wieringa, R. J. (2014). Design Science Methodology for Information Systems and Software Engineering.
Berlin, Heidelberg: Springer
Pictures under Creative Commons / Wikimedia.org
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