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Complexity & innovation
in IT, engineering, management
Stefan Morcov
22 Nov. 2024
1
with AI
and in LIFE
1. Know the rules education
2. Shortcut the rules experience
3. Invent new rules disruption
2
Projects and products become more and more challenging,
while more and more rewarding
31% of projects are canceled
52% of projects cost 189% the original estimate
16.2% are on-time/on-budget
(Standish Group, 1995)
3
Technology projects
are complex
Some projects are particularly complex
=> huge cost
Arianne 5 – 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
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
4
Complex projects
are expensive
5
So, why do we do complex projects?
Complexity works !
Delivers value & benefits.
Complex projects
create complex products
for complex markets
in complex organizations
with complex processes.
6
7
Artificial
intelligence
8
SMS
9
Pls. interrupt me
11
Let's make this interactive
12
Innovation
13
AI: Utopia or Dystopia !?
Innovation occurs at the edge of chaos
Systems must be taken outside equilibrium to innovate
Systems acquire complexity to evolve & survive
15
Innovation,
Positive & Appropriate
complexity
The myth of the lonely
cowboy programmer
Tester
QA Analyst
Domain expert
UI/graphics
UX/usabilty
Architect
Project manager
Sys admin
DBA Technical leader Support
Communication
complexity
n*(n-1)/2
What is a project
(PMBoK)
18
A temporary endeavor
to create a unique
product/service
Difficult to understand, foresee and
keep under control,
even when given reasonably complete
information about its components.
Structural complexity (complicatedness)
Dynamic complexity
19
A complex project
Complex
Difficult
Large
Complicated
Unmanageable
Fashionable
Fancy
Baroque
Consisting of
many
varied
interrelated parts
20
Structural complexity
21
Systems complexity
Ambiguity, uncertainty,
propagation, chaos
Emergence, adaptiveness
Nonlinearity, complex feedback loops
22
Dynamic complexity
Significant impact of small factors and
rare events
Lorenz’s Butterfly Effect
◦Ray Bradbury: A Sound of Thunder, 1952
◦Lorenz: Deterministic NonPeriodic Flow, 1963
Black Swan (Taleb, 2007)
◦Fractals & long-tail vs. Gaussian distributions
23
Dynamic complexity
Vulnerability management
= Resistance + Resilience
Anti-fragility (Taleb 2012)
24
Dynamic complexity
Framework contracts for the specification, development and maintenance of IT systems in the field
of:
◦Fiscality - FITSDEV –40 mil
◦Customs - CUSTDEV - 140 mil
◦Joint: SOFT-DEV (starting 2020)
FwC for operation of applications and infrastructure:
◦ITSM-operations = support and operations for central apps, 177 mil
◦ITSM-Trans-european =support to member states, 35 mil
◦ITSM-integration = mostly QA and consultancy, 26 mil
eLearning, capacity building and communication - BTrain, 10 mil
Middleware & communication infrastructure - CCN, 55 mil.
Network services - CCN/WAN2, 10 mil
Intramuros support – TIMEA, 42 mil
Quality assurance – QA, 35 mil
25
Case study: DG Taxud
Ecosystem of IT Framework Contracts
BTrain3 @ DG Taxud
26
Stakeholders Map – Target Audience
28
We help companies
win public contracts
Tender
monitoring
Leads
Forecast
Commercial
analysis
Background
Competition
Tender
summary
AI, LLM, GPT
Market
intelligence
AI / ML
29
Business complexity
Product
Brand,
marketing
Sales
Team
Budget
Level 1. Know the rules, standards, procedures
(Project) management / engineering school
Level 2. Know when to ignore rules / cut corners
Experience
Level 3. Make new rules
Create knowledge
30
Systematic project management
frameworks
Iron-triangle
31
1. Basic ingredients to successful projects
- by the (PM)book
32
The Iron-triangle
of project management
Invoicing, cost,
profit
Project objectives
Statement of work
Deliverables
Features, requirements,
stakeholder needs& interests
Success criteria
Planning
When?
How much?
What?
(and what
not
)
Any system does something right –
Not necessarily what it was supposed to do.
◦Objectives
◦Requirements
◦Stakeholder management
◦Configuration management
◦Change management
33
1. Basic ingredients to successful projects
- by the (PM)book
Scope
Risk management
Communication management
Leadership, people, motivation
34
1. Basic ingredients to
successful projects
Know your tools –classical school
Project management: PMBoK, IPMA, Prince2, PM2@EC, RUP@EC
Quality: ISO 9001, Total Quality Management, CMM, Six-sigma
IT Service Management & Governance: ITIL, COBIT
Software development: Waterfall, incremental, RUP, Agile, SCRUM, FDD, XP, RAD,
prototyping, OOAD, UML, dependency modelling, traceability matrices
IT architecture: TOGAF
Software estimation: FPA, COCOMO
Testing: ISTQB
Security: ISO 27001/2, CRISC, CISM, CISA, CISSP
35
Methodologies &
frameworks
1. Decomposition (X-BS,
modularization, COTS components,
reusability)
2. Dependency modelling
3. Causal-loop, systems thinking
4. Brainstorming
5. Mind-maps
6. SWOT / PEST / STEEP
7. Checklists
8. Decision trees
36
Tools for analysis and
decision 9. Decision matrices
10. Cost-benefit
11. Cause-effect / Ishikawa
12. Paretto (the 80-20 rule)
13. Delphi
14. Focus groups
15. Toyota way
16. 5 why-s
17. WWWWWH
Know your tools –classical school
37
How many of these tools do you know?
a) More than 10
b) More than 5
c) Less than 3
1. Decomposition (X-BS,
modularization, COTS components,
reusability)
2. Dependency modelling
3. Causal-loop, systems thinking
4. Brainstorming
5. Mind-maps
6. SWOT / PEST / STEEP
7. Checklists
8. Decision trees
9. Decision matrices
10. Cost-benefit
11. Cause-effect / Ishikawa
12. Paretto (the 80-20 rule)
13. Delphi
14. Focus groups
15. Toyota way
16. 5 why-s
17. WWWWWH
Tools for analysis and
decision
Know your tools –classical school
Which is the best
project management
tool?
38
Open question
39
1. Excel / sheets
2. Word / docs
3. Jira
4. Confluence
5. Miro
6. Monday
7. MS Project
8. Primavera
9. ….
The best project
management software tool
Email, collaboration, knowledge mgmt: Google Drive,
Docs, Sheets, gmail, gmeet, Confluence
Development/test environment – AWS cloud, Azure, full
stack
Configuration management, CI/CD – Github
Planning – Jira, Kanban
Sales, marketing automation –CRM, Hubspot
Marketing: LinkedIn, PhantomBuster, Apollo, Google
Analytics, …
40
1. Project tools setup –
example @Hermix
Project management performance
Traditional scope & QA management:
“compliance with agreed written specifications”
Project success = RESULTS
41
2. Lessons learned –
modern IT/mgmt school
In theory, practice is simple; but in practice, it’s not.
Clear theoretical solutions are applicable only to perfectly spherical cows in a vacuum
under zero-gravity conditions.
42
2. Lessons learned –
modern IT/mgmt school
Agile management: iterative, wave-crest planning /scope analysis
Manage a complex project as a program
Management fallacies –Murphy laws
Mongolian horde concept
First rule of cyclism
We can fill-in the details later
The 95%-ready paradox
The KLOC paradox
43
2. Lessons learned –
modern IT/mgmt school
Agile management: iterative, wave-crest planning /scope analysis
Manage a complex project as a program
Management fallacies
Mongolian horde concept: just throw-in more people
First rule of cyclism: always run up-hill and against-wind
We can fill-in the details later
The 95%-ready paradox: 95% ready, 97%, 99, 99…, 99…….
The KLOC paradox: measuring software code quantity vs. quality
44
2. Lessons learned –
modern IT/mgmt school
Mix different contract types (fix-price, time&means, mixed)
Mix different suppliers
Informal team communication and collaboration
The right team. Balance people vs. Structure
Management vs. leadership
Do not oversimplify. Manage complexity & risk
A well-managed project is not a project without a mess,
but a project with a well-managed mess
45
3. Lessons learned –outside
PM school
Ford never asked customers what they wanted
46
3. Innovate
= consisting of many
varied
interrelated parts
Tools for managing structural complexity:
◦Complexity measurement
◦Configuration management
◦Change management
◦Dependency (DSM, DMM, MDM) & traceability matrix (requirements, stakeholders, changes)
(Maurer 2017) (Marle&Vidal 2016)
47
3. Structural
complexity
Ambiguity, uncertainty, propagation, chaos
Nonlinearity, complex feedback loops and significant impact of small factors
Lorenz’s Butterfly Effect
◦Lorenz: Deterministic non periodic flow, 1963
◦~Ray Bradbury short story, 1952
Nicolas Taleb: Black Swan (2007)
◦Fractals & long-tail vs. Gaussian distributions
Vulnerability management = Resistance + Resilience
Anti-fragility (Taleb 2012)
48
3. Dynamic complexity
Systems (projects, products) are:
49
3. Complexity in engineering
management
1.
Simple
Managing ≈ no effort
1.
Complicated
(≈ structural complexity)
Managing ∝ effort
1.
Complex
Managing ∝ effort times x
1.
Really complex
Managing ∝ exponential to effort
50
3. Complexity domains
based on the Cynefin framework (Snowden)
Management effort: Low
Exponential
Aristotle Euclid
51
3. Complexity effects &
mitigation
Positive complexity Appropriate complexity Negative complexity
Benefits > Cost Benefits ≃ Cost Benefits < Cost
Desirable Accepted Undesirable
Innovation & creativity
Additional features
Large budget
Component reusability
Political priority
Integration/compliance with new
technologies
Unclear objectives – scope agility
Many varied technologies
Many interrelated components.
Unclear objectives.
New technology.
Large number and variety of stakeholders
Response strategy
Complexity Effect
Positive Appropriate Negative
Create, enhance x
Use (exploit) x
Accept / ignore x x x
Simplify / reduce x
Avoid / eliminate x
Deploying additional tools is expensive
More processes = more centralization
=> less innovation, less flexibility,
increased vulnerability
52
3. Complexity & cost
Innovation occurs at the edge of chaos
A system must be taken outside the equilibrium state in order to innovate
Systems must acquire complexity in order to remain viable
The law of requisite complexity
Positive/appropriate complexity
53
3. Innovation & positive
complexity
1. Learn the rules Education
2. Shortcut the rules Experience
3. Create your own rules Innovation
54
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
56
Selected bibliography
57
Tool: Stakeholder map
◦Who impacts the project: name, title, role
◦How: objectives/interests
◦Contact points
◦Communication channels/frequency
Monitor for change !
58
1. Stakeholder
management
Tool: risk register
1. Identify risks & opportunities
2. Analyze (qualitative / quantitative)
3. Plan mitigation strategies
◦Reduce, avoid, transfer, accept (risks)
◦Exploit, create, share, accept (opportunities)
4. Monitor & manage
59
1. Risk & opportunity
management
(Marle&Vidal 2016)
1. Define problem
2. Collect (ALL) ideas
3. Categorize ideas (e.g. card-sorting)
4. Prioritize ideas (e.g. by voting)
60
Brainstorming
61
Mind-maps
“divide et impera”
X-BS (Breakdown Structure)
◦Work-BS, Risk-BS, Cost-BS, …
Standardization, modularization &
reusability of designs/components (see
Ford)
62
De-composition
SWOT
◦Internal: Strengths, Weaknesses
◦External: Opportunities, Threats
PEST - Political, Economical, Social,
Tehnological
STEEP - Social, Tehnological, Economical,
Ecological, Political
63
Checklists, mnemonics
64
Decision
trees
65
Decision matrices
66
Ishikawa (fish-bone, cause-effect)
Problem trees
Design Structure Matrix (DSM) –between same components
Dependency Mapping Matrix (DMM) –between different
components
Multiple-Domain Matrix (MDM) (Maurer 2017)
DSM DMM MDM
67
Dependency modelling
68
Design Structure Matrix
(DSM) example
69
Multiple Domain Matrix
(MDM) example
70
3. Complexity measurement
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Time/cost
Team size
Team composition and
performance
Urgency/flexibility of
cost/time/scope
Problem/solution
clarity
Requirements volatility
and risk
Strategic/political
sensitivity/importanc…
Level of organizational
change
Level of commercial
change
Risk, external
constraints and…
Level of IT complexity
Average
Hass complexity scale - example
Prj 1
Prj 2
Prj 3
Prj 4
Prj 5
71
Hass tool
Cifter tool
3. Complexity
measurement
(Sheard, Sarah A, and Ali Mostashari. 2010)
72
A Complexity Typology for Systems Engineering
73
Large & very large
Long decision cycle - management
by committee
Critical projects – political agenda
Complex stakeholder map
Varied political interests –formal
and informal
Changing political priorities
◦Some organisations are very
vulnerable to political change, some
are more stable
Very complex regulations
Complex / complicated
74
Project
complexity
Market
complexity
Product
complexity
Process
complexity
Organisation
complexity
11/22/2024
75
Learning
Teaching
Evaluation
Testing
Monitoring
School
management
System
management
Content
Collaboration
Change
Management
Training
Students
Grades
Attendance
Scheduling
Activities
Results
History
Resources
Schools
Curricula
Personnel
Teacher’s
management
Employment
Management of
resources
Students
Management
of national
examinations
Collaboration
Federated content
Information
Analysis
Decision
National Education project example.
Holistic vision – project ecosystem
EPALE is the pan-European,
multilingual, open membership
community of adult learning
professionals and policymakers
European Commission project
76
Case study: EPALE - European
platform for adult learning
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
Project preparation stage: 1-2 years
Bid-proposal stage: 2-3 months
Evaluation stage: 2-4 months
◦Rarely - very long
Sign contract, take-over, ramp-up: 3-7 months
Project execution: 2-10+ years
Workarounds:
◦Framework contracts
◦Programs instead of projects
Typical project cycle –
public procurement
77
Fix-price (incl. service-mode, managed services, SaaS)
◦Responsibility & risk @ supplier
Time & means (dedicated team, sourcing...)
◦Responsibility & risk @ buyer
Mixed models
◦Quoted Time & Means
◦Mixed framework contracts
78
Public procurement: type of
contracts
Work expands so as to fill the time available for its completion
(Parkinson's law)
It always takes longer than you expect, even when you take into
account this law (Hofstadter's Law)
The Pygmalion effect, or Rosenthal effect, is the phenomenon
whereby higher expectations lead to an increase in performance
79
Internal politics: empirical evidence about the
functioning of bureaucratic organisations
Work expands so as to fill the time available
◦This law is true for both private & public organizations
Case-studies: UK Ministry of Naval Forces, UK Colonial Office
◦The staff rose by 5–7% per year irrespective of any variation in the amount of
work (if any) to be done
Driving forces :
◦An official wants to multiply subordinates, not rivals
◦Officials make work for each other
Which are the reverse driving forces ?
80
Parkinson’s empirical observations on
the functioning of bureaucracies
Comitology: how committees, government cabinets, and other such
bodies are created and eventually grow irrelevant
Larger organisation structure = less power
Large bureaucracies tend to diffuse responsibility and decision
◦Complex and long procedures for evaluation and career plan
➢Low incentive for taking personal responsibility: limited benefits vs.
high risk
➢Stable, conservative organizations, averse to risk
81
Management by
Committee
Centralized vs descentralized administrations
Language (e.g. European English)
Etiquette, small-talk, salutation, titles
Negotiation styles
Digitization, technology, remote collaboration
Covid / social distancing
82
Cultural aspects
+ European R&D is mostly public-funded
◦National & EC funds
◦Grants, universities, PhDs, research institutes
◦Horizon, EIC/SME instrument, FTI, FET
- Adoption of new technology is slow
◦~ 2-5 years behind private sector
◦Long-cycle, large programs
◦Low risk
83
Innovation in the public
sector