Lecture given at HHL on 19 February 2019 on failures of management orthodoxies in the face of complex change

1. Emperors without clothes
Failures of management orthodoxies
in the face of complex change
Dr. Johannes Meier

2. Modern leadership context characterized by
increasing volatility, uncertainty, ambiguity
Complex
Modern
Leadership
Context
Global
context
Fragmented
societies
Techno-
logical
progress
Regulation
and policy
risk
Sustain-
ability
Reflexivity

4. 4Source: https://www.genome.gov/27565109/the-cost-of-sequencing-a-human-genome/

5. Risks are interconnected and impacts non-linear
5Source: http://reports.weforum.org/global-risks-2018/global-risks-landscape-2018/

6. The future is open, ambiguous, dialectical
Fundamental trends Future space
Age of Age of
Large information and
communication streams
… of freedom and ideas … of confusion and
propaganda
… collective intelligence
cooperative solutions
… of individualism
… of joint and civil
engagement
… of trivial pursuits
Compression of time, distance
and access
… of global reach … of global disruptions
Increasing access of poor
nations and in parallel
increasing asymmetries
… of global well-being … of self-interest and
protectionism
Inadequate ethical and spiritual
codes in the face of global risks
… of higher awareness … of ideological battles
Source : based on Ketan Patel „The Master Strategist: Power, Purpose and Principle“ 2005
Source: Ketan Patel, Master Strategist 6

7. The methodological challenge
• Interdependencies between trends, risks, interventions,
orthodoxies
• Decoupling of societal action from space and time restrictions
• Reflexivity of life in modern societies: social practices are
constantly being evaluated and adapted in the face of new
information which is changing their character fundamentally
(Anthony Giddens)
• Divergent interpretations and fundamental assumptions across
cultural and semiotic contexts
Process of production of shared meaning and values is critical
This process is inherently non-linear
7

8. Conventional management practice:
Four emperors without clothes
(all related)
1. Emperor of command
and control
2. Emperor of you-get-
what-you-measure
3. Emperor of
extrapolated
forecasts
4. Emperor of
reductionism
My central thesis:
All these emperors
have no clothes and
lead to fragile
systems
8

9. Conventional management practice:
Four emperors without clothes
(all related)
1. Emperor of command
and control
2. Emperor of you-get-
what-you-measure
3. Emperor of
extrapolated
forecasts
4. Emperor of
reductionism
My central thesis:
All these emperors
have no clothes and
lead to fragile
systems
9

10. Command-and-Control Thinking
• Perspective Top-down, hierarchy
• Design Functional specialization
• Decision-making Separated from work
• Measurement Productivity output, targets
• Attitude to customers Contractual
• Attitude to suppliers Contractual
• Role of management Manage people and budgets
• Ethos Control
• Change Reactive, projects, linear
• Motivation Extrinsic
Source: John Seddon 2008 10

11. Traditional governance (1.0)
Goals:
• Balanced Budgets
• Financial Compliance
KFS:
• Regularity
• Standardized accounting
• Clear leadership hierarchy
Perspective:
• Internal only
timabbott
Issues:
• Backward orientation
• Year-end „games“
• No accounting for
contingencies
11

12. Conventional management practice:
Four emperors without clothes
(all related)
1. Emperor of command
and control
2. Emperor of you-get-
what-you-measure
3. Emperor of
extrapolated
forecasts
4. Emperor of
reductionism
My central thesis:
All these emperors
have no clothes and
lead to fragile
systems
12

13. Traditional governance (1.1)
Graphics www.lumaxart.com/
Goals:
• Performance indicators
• Balanced scorecards
KFS:
• Modelling dependencies
• Mapping actions to indicators
• Clear leadership hierarchy
Perspective:
• Internal processes with external
performance indicators
Issues:
• Incomplete models of
dependencies
• Measuring output, not
outcome
• Still many „gaming“
opportunities
• Little accounting for
contingencies
• Doing less of the wrong
thing is not doing the right
thing
13

14. Common observations
WaveCult (luis.m.justino)
• Targets drive people to use their
ingenuity to meet the target, not
improve performance.
• End-to-end measures show huge
variance, dysfunctional
performance despite star-ratings
for all departments.
14

15. Why do most call centers meet their targets?
15

16. Conventional management practice:
Four emperors without clothes
(all related)
1. Emperor of command
and control
2. Emperor of you-get-
what-you-measure
3. Emperor of
extrapolated
forecasts
4. Emperor of
reductionism
My central thesis:
All these emperors
have no clothes and
lead to fragile
systems
16

17. 17
Example complex system: Butterfly effect
• Weather forecasts for just a few days work pretty well.
• But the “flap of the butterfly’s wings” (the 0.000001 difference) is enough to
separate the long-term fates of the system.
• Note we can still predict climate change over longer time scales, but not the
exact long-term behavior
r = 1.8

18. 0 kg
1 kg
2 kg
3 kg
4 kg
5 kg
6 kg
Jan Feb Mrz Apr Mai Jun Jul Aug Sep Okt Nov Dez
Example Thanksgiving : A Turkey‘s Tipping point
Weight Turkey
Surprise!!
Source: N. Taleb, The Black Swan 18

19. Black Swans
Black Swans are large-scale unpredictable
and irregular events of massive
consequence.
Man-made complex systems tend to
develop cascades and runaway chains of
reactions that decrease, even eliminate,
predictability and cause outsized events.
So the modern world may be increasing in
technological knowledge, but,
paradoxically, it is making things a lot
more unpredictable.
The rarer the event, the less tractable, and
the less we know about how frequent its
occurence.
Foto: Baden de
19

20. Tipping point Financial Crisis:
Managerial failure to deal with complexity?
Failure of regulation?
Limitation of linear thinking?
20

21. Tipping point German reunification:
Unforeseen even two weeks before the end of the wall
21Foto Andreas Krüger,

22. Tipping point end of Easter Island civilization:
The power of linear thinking?
von vtveen
2222

23. The risk of tipping points from climate change
23Source: PIK

24. Learning from tipping points in nature
• All ecosystems are exposed to gradual changes in climate,
nutrient loading, habitat fragmentation or biotic exploitation.
• Nature is usually assumed to respond to gradual change in a
smooth way. However, studies on lakes, coral reefs, oceans,
forests and arid lands have shown that smooth change can be
interrupted by sudden drastic switches to a contrasting state.
• Although diverse events can trigger such shifts, recent studies
show that a loss of resilience usually paves the way for a switch to
an alternative state.
• This suggests that strategies for sustainable management of such
ecosystems should focus on maintaining resilience.
24
Source: Marten Scheffer, Steve Carpenter, Jonathan A. Foley, Carl Folkes & Brian Walkerk, Catastrophic shifts in ecosystems, NATURE, VOL 413, 11
OCTOBER 2001, p. 591-596

25. Hysteresis and path dependency
25
Path 1: Start looking at image
from the upper left corner
proceeding to the lower right
corner.
Path 2: Start looking in inverse
direction.
 Perception of image changes
at different points.
Source: H. Haken (1983), Synergetik, Springer-Verlag.

26. Greenland Ice Sheet tipping point model
26Source: Nordhaus, William (2013). The Climate Casino – Risk, Uncertainty, and Economics for a Warming World. Yale UP

27. Different types of risk
• Manageable Risks vs. Unmanageable Risks
(W. Nordhaus – 2018 Nobel laureate)
• Problem of long tails and discounting of long-term uncertainty
(N. Taleb)
• Relevance and the law of declining love
(D. Kahneman, O. Hondrich) 27

28. Risk domains
Interesting,
normal life
Black Swan
Domain
Classical
management
domain
Insurance
and Casino
domain
High exposure to
rare, tail events
Low exposure to
rare, tail events
Incomputable
events
Computable
events
„Robustification“
28

29. The moral dimension
of climate risk
At what probability of getting hit
by a car would you still let your
child play in the street?
Muhammad Yunus
29

30. Precautionary principle in the face of tipping points
1992 United Nations‘ Rio Declaration on Environment and
Development: „Where there are threats of serious or irreversible
damage, lack of full scientific certainty shall not be used as a reason
for postponing cost-effective measures to prevent environmental
degradation.“
Game-theory minimax strategy: In the absence of scientific
certainty, society should make policies that prevent the worst
outcome.
Nordhaus‘ cost-benefit perspective: If the damages are uncertain,
highly nonlinear, and clifflike in the Climate Casino, then a cost-
benefit analysis will generally lower the optimal target to provide
insurance against the worst-case outcomes.
As complex systems do not have obvious one-dimensional cause-
and-effect mechanisms, you should not mess with such systems
under opacity.
30

31. Conventional management practice:
Four emperors without clothes
(all related)
1. Emperor of command
and control
2. Emperor you-get-
what-you-measure
3. Emperor of
extrapolated
forecasts
4. Emperor of
reductionism
My central thesis:
All these emperors
have no clothes and
lead to fragile
systems
31

32. Real world, science, and consultants
32Source: Real World vs. Science according to N. Taleb, Skin in the game
Consultants
Consultants often reduce a
complex reality to a problem that
can be solved with a given
methodology.
Powerpoints are not very precise
forms of communication when it
comes to qualifying solution
claims.
In a complex system this often
leads to unforeseen higher-order
effects and non-sustainable
impacts.

33. Counterintuitive observations about the collective
• The average behavior of the market participants will not allow us
to understand the general behavior of the market
• The psychological experiments on individuals showing „biases“
do not allow us to automatically understand aggregates or
collective
• The higher the dimension, i.e. the number of possible
interactions, the more disproportionally difficult it is to
understand the macro from the micro, the general from the
simple units
Fundamental limitation of behavioral economics on how to play
the market or generate policy
Mathematically speaking, the mean-field approach, where one
generalizes from the average interaction to the group is only
possible if there are no asymmetries
33Source: Taleb, Skin in the game, appendix to book 3

34. Homo sapiens vs. Homo economicus
Most social processes are not neatly decomposable into separate
subprocesses – economic, demographic, cultural spatial.
Yet, this compartmentalization in insular departments and journals
is how we tend to organize the study of social systems (e.g., finance
vs. strategy vs. marketing departments in B-schools)
In order to develop realistic and relevant models it is essential to
begin with solid foundations regarding individual behavior and
spatial structures. Current laboratory social science (e.g. Tversky
and Kahneman) are giving us an ever-clearer picture how homo
sapiens – as against homo economicus – actually makes decisions.
Agent-based modeling offers an integrative, inherently multi-
dimensional alternative.
34Joshua M. Epstein (2006). Generative Social Science: Studies in Agent-based Computational Modeling. Princeton UP

35. The concave nature of travel
35
• A small disturbance in a congested traffic system can lead to major disruptions/delays.
• Systems like traffic rarely experience positive disturbances.
• Traffic is a system with „one-sided disturbances“ which leads to underestimation of
randomness and harm.
• Buffers are important to avoid major failures. The average does not matter.
Foto basykes

36. Fragility – The concave
Example: Driving a car against an obstacle
36
Speed
Harm
The nature of fragility:
• For the fragile, shocks bring higher harm as their intensity increases (up to a
certain level)
• For the fragile, the cumulative effect of small shocks is smaller than the single
effect of an equivalent single large shock.
• The more concave an exposure, the more harm from the unexpected, and
disproportionately so.
Concave or negative
convex curve
For a set deviation in a variable
the concave loses more than it gains
Reference: Taleb, Antifragility

37. Case: Fannie Mae
2003 internal risk report of Fannie
Mae showed
• Move upward in an economic
variable led to massive losses
• Move downward in same variable
led to small profits
• Acceleration of harm in concave
curve visible as simple fragility
detection heuristic
High fragility indication possible
even without good model for risk
measurement
37
Fragility is quite measurable, risk in real life not so at all, particularly risk associated with
rare events. Not seeing a tsunami or an economic event coming is excusable; building
something fragile to them is not.
Reference: Taleb, Antifragility, Chapter 19

38. Antifragility – The convex
Antifragility: Some things benefit from shocks; they thrive and grow when exposed to
volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty.
Detecting antifragility:
For the antifragile, shocks bring higher benefits as their intensity increases
38
Variable
Gains
Convex curve:
For a set deviation in a variable
the convex gains more than it loses
Reference: Taleb, Antifragility

39. Different types of exposures of systems
Fragile Robust/Resilient Antifragile
Errors Hates mistakes
Irreversible, large (but
rare) errors, blowups
Mistakes are just
information
Loves mistakes (since they are
small)
Produces reversible, small
errors
Biological &
economic systems
Efficiency, optimized Redundancy Degeneracy (functional
redundancy)
Science &
technology
Directed research Opportunistic research Stochastic tinkering, bricolage
Regulation Rules Principles Virtue
Political systems Nation-state,
centralized
Collection of city-states,
decentralized
Economic life Bureaucrats,
Agency problem
Entrepreneurs,
Principal operated
Physical training Organized sports, gym
machines
Street fights
39Reference: Taleb, Antifragility

40. Solutions to antifragility
You are antifragile for a source of volatility if potential gains exceed potential losses
(and vice versa)
• Simple test: If I have „nothing to lose“ then it is all gain and I am antifragile.
• Recognize path dependence: No upside without survival
• First step towards antifragility: Decrease downside, protect yourself from
extreme harm (negative Black Swan) and let the upside (positive Black Swan)
take care of itself
Solution to antifragility is combination of aggressiveness and paranoia
Solution takes form of a barbell (bimodal strategy)
„Provide for the worst; the best can take care of itself.“ (Yiddish proverb)
Yet, there is ample evidence from insurance that people are averse to small losses,
but so much toward very large Black Swan risks (which they underestimate)
40

41. Examples of barbell strategies
• Ray Dalio on speculative bets: „Make sure that the probability of the
unacceptable (i.e. the risk of ruin) is nil.“
• Montaigne‘s life strategy as a serial barbell: First „doer“ then „thinker“
• In social policy, protect the very weak and let the strong do their job,
rather than helping the middle class to consolidate ist privileges
• In publishing, avoid having 100% of the people finding your mission
acceptable, but instead aim for high percentage of people disliking you
and your message combined with a low percentage of extremely loyal
and enthusiastic supporters
41

42. Factors affecting the fragile-antifragile balance
Antifragility
Fragility
• Specialization
• Departmentalization
• Silo Thinking
• Bureaucracy
• Privatization of gains,
socialization of risk
• Numerical predictions
• Overconfidence of
experts
• Success and fear of loss
• Narrative knowledge
• Curiosity
• Interdisciplinarity
• Systems Thinking
• Entrepreneurialism
• Skin in the game
• Large libraries
• Wisdom in decision-
making
• Mentally adjusting to „the
worst“
• Optionality
42

43. Outlook: Mastering non-linear change
Butterfly effect
Future intelligencePublic value
Generative social science
Types of risk
Sustainability
Networktheory
Systems
architecting
Antifragility
Holistic leadership
Adaptiveleaders
Personal mastery
Tipping
points
Viral growth
Blackswans
Hysteresis
Resilience
Transition
managementIntegral
governance
Intangibles
Network externalities
Agent-based modeling
Systems thinking
Heuristics
Complexity
science
Reflexivity
Restructuring Skin in the game