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Mechanism Design for Total Quality
Management: Using the Bootstrap
Algorithm for Changing the Control Game
Petter Øgland
Presentation of thesis
Oslo, November 27th 2013
Plan for presentation
• Motivation (7 minutes)
– Problem: Critical systems are getting too complex to be controllable
– Possible solution: Bootstrap Algorithm (BA), if it works as claimed
• Theoretical model and hypotheses (7 minutes)
– A game theoretical perspective on total quality management (TQM)
– Interpreting the BA through Monopoly and Genetic Algorithms (GA)
– Testable BA hypothesis: The BA is efficient, stable and optimal
• Research method and results (7 minutes)
– 20 years of action research, three cycles; DNMI + NTAX + NTAX/UiO
– BA hypothesis supported
• Contributions to theory and implications for practice (7 minutes)
– Use of Monopoly, GA and game theory to strengthen BA theory
– The BA is useful for implementing TQM in complex environments
Tightly coupled complex systems in
crisis: Climate, finance, technology
Three Mile Island accident, Pennsylvania, March 1979
Perrow (1984):
Tightly coupled
complex systems
should be avoided
...but can we?
President’s Commission, October 1979: Inadequate quality assurance
Control crisis is followed by control
revolution: Information society evolves
How do people handle
control crisis in highly
complex
environments?
Are they implementing Total
Quality Management (TQM), or
are they pretending to do so?
80% TQM implementation failure
Explanation: ”FAKE TQM”
The TQM standards industry
(ISO 9000, CMM, etc)
creates a global network of
organised hypocrisy
What is needed: ”REAL TQM”
The Bootstrap Algorithm (BA) is a
way of developing information
infrastructure (quality control
infrastructure) by cultivation and
spreading
But are we sure the BA actually works?
• Nonfalsifiable theory (ideological)
– It gives the impression of being normative (algorithm), but is
descriptive (Hanseth & Lyytinen, 2004), meaning that it is more
like a metaheuristic than an algorithm (Talbi, 2009; Luke, 2011)
• Anecdotal empirical evidence
– It is based insights from information infrastructure development
case studies (Hanseth & Aanestad, 2003)
• Cannot be tested according to normal scientific procedures
like ”comparison of treatment” laboratory studies
– It is used as a guideline for doing ”networks of action” research
on international health information systems (Braa et al, 2004)
– It has so far not been critically investigated from a practitioner’s
point of view (i.e. action research on the BA itself)
Theoretical model and hypotheses
”REAL TQM” & critical theory
The organisation must break
loose of ’false consciousness’
and liberate itself from the
oppression of the hypocrisy
Critical theory and game theory
Tragedy of the commons (Hardin,
1968), political activism and social
theory in general can be formulated
through game theory (Binmore,
2009; Elster, 1981; Gintis, 2009).
Three levels of TQM game play
Controlling cultural change
Controlling the survival of the
TQM programme
Controlling process
improvement projects
Monopoly –
mechanism
design game
Stag Hunt – trust game of
doing “real TQM” or “fake
TQM” depends on culture
Matching Pennies – zero sum quality
control game based on having “real TQM”
management commitment
Cultivating information infrastructure
on a mission to “conquer the world”
In the Monopoly game the players control
and expand their assets as a network of
real estate trades and developments
across the game board
The Health Information System
Programme (HISP) controls and expands
itself as a network of research and
development across the world
Thinking about the Bootstrap
Algorithm (BA) as a Monopoly strategy
Start with
 simple, cheap, flexible solution
 small network of users that may benefit
significantly from improved communication
with each other only
 simple practices
 non-critical practices
 motivated users
 knowledgeable users
1. Repeat as long as possible: Enrol more users
2. Find and implement more innovative use; go
to 1
3. Use solution in more critical cases; go to 1
4. Use solution in more complex cases; go to 1
5. Improve the solution so new tasks can be
supported; go to 1
Hanseth & Aanestad (2003)
Thinking about the Bootstrap
Algorithm (BA) as a Genetic Algorithm
Genetic Algorithm (GA) (Holland, 1995)
Frayn (2005) uses the GA as a Monopoly
strategy when studying the game by
computer simulation
RH: The BA is an optimal mechanism
design for implementing TQM
RH2: The BA is efficient
Real World
TQM installed base
(“real TQM”)
Formulate
Model
Monopoly game
RH: The BA is an
optimal mechanism
design for
implementing TQM
Real world conclusions
TQM information infrastructure
(“real TQM”)
Deduce
RH3: The BA is
optimal
Model conclusions
Bootstrap Algorithm
Interpret
RH1: The BA is stable
Canonical Action Research (CAR)
• The research process was not originally
designed as CAR, but CAR is useful for
explaining how things were done
• Twenty years of TQM implementation by
trying to bootstrap the information
infrastructure
• Three cycles (DNMI + NTAX + NTAX/UiO)
First cycle 1992-99: Det Norske
Meteorologiske Institutt (DNMI)
• Diagnosis: Complexity made
project management based on
water-fall model unsuccessful
in developing Climate
Database (KLIBAS)
• Treatment: Complex adaptive
systems (CAS) was used to
define a BA that proved
successful for developing and
improving KLIBAS in the
context of TQM
implementation
• Outcome: Formulation of BA
and experience from using it
Second cycle 1999-2005: Skatteetaten
(NTAX)
• Diagnosis: Strong elements of
“fake TQM” in a world of
bureaucracy, politics and
complexity
• Treatment: The BA approach
developed at DNMI was able
to change “fake TQM” into
“real TQM” but ultimately
failed
• Outcome: Need to investigate
why the “what gets measured
gets done” idea, as used in the
BA design, did not give
expected results
Third cycle 2006-2011: Collaborating
with UiO for creating change at NTAX
• Diagnosis: The “what gets
measured gets done” idea did
not work among COBOL
programmers at NTAX as there
was lack of management
commitment to TQM
• Treatment: Improve the audit
process by being more specific
in the formulation of the audit
game, which helped, but in the
end the process failed
• Outcome: The importance of
having game theoretic
representations of the social
theories used when studying
BA through action research
BA stability hypothesis (RH1)
Size of
20
population
(improv.
projects) 15
FIRST CYCLE
SECOND CYCLE
THIRD CYCLE
10
5
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
0
Im provem ent projects
Upper Control Lim it
Process centre
Low er Control Lim it
Outcome of hypothesis test (RH1)
RH2: The BA works
Real World
TQM installed base
(“real TQM”)
Formulate
RH: The BA is an
optimal mechanism
design for
implementing TQM
Model
Monopoly game
Deduce
Real world conclusions
TQM information infrastructure
(“real TQM”)
RH3: The BA is
optimal
Model conclusions
Bootstrap Algorithm
Interpret
RH1: The BA is stable
BA impact hypothesis (RH2)
1. Opening: Get involved in
as much and as diverse
TQM work as possible
(random)
2. Property trading:
Hamlet game, Pac-Man
game, “what gets
measured gets done”
game, self-protection
game
3. Property development:
Deconstruction game
4. Endgame: Auto-pilot
Outcome of hypothesis test
(RH1 + RH2)
RH2: The BA works
Real World
TQM installed base
(“real TQM”)
Formulate
RH: The BA is an
optimal mechanism
design for
implementing TQM
Model
Monopoly game
Deduce
Real world conclusions
TQM information infrastructure
(“real TQM”)
RH3: The BA is
optimal
Model conclusions
Bootstrap Algorithm
Interpret
RH1: The BA is stable
BA optimality hypothesis (RH3)
2022
2018
2014
2010
2006
2002
1998
1994
1990
1000
900
800
700
600
500
400
300
200
100
0
EFQM score
Logistic regression curve
By following optimal strategy it should take
about 25 years to implement TQM at NTAX?
• Usually 3-5 years to
implement TQM,
following the CSF
(Hendricks & Singhal,
2001)
• When using the BA to
compensate for not being
able to meet CSF, this
study suggests 25 years to
implement TQM
• At Toyota it took 50 years
(Liker, 2004)
Outcome of hypothesis test
(RH = RH1 + RH2 + RH3)
RH2: The BA works
Real World
TQM installed base
(“real TQM”)
Formulate
RH: The BA is an
optimal mechanism
design for
implementing TQM
Model
Monopoly game
Deduce
Real world conclusions
TQM information infrastructure
(“real TQM”)
RH3: The BA is
optimal
Model conclusions
Bootstrap Algorithm
Interpret
RH1: The BA is stable
Contribution to knowledge 1:
Monopoly as a model of II dynamics
Kernel theory
Kernel theory
Old knowledge
New knowledge
Contribution to knowledge 2:
The BA as a Genetic Algorithm (GA)
Design theory
Old knowledge
New knowledge
Kernel theory
Design theory
Contribution to knowledge 3:
Use of game theory in action research
3. Testing of treatment :
Positivist attitude
2. Finding a treatment :
Mathematical analysis of the game model
1. Diagnosis:
Phenomenological attitude
Self-oppression
through capitalist
consumerism
Implications for practice
FAKE TQM
Controlling cultural change
Controlling the survival of the
TQM programme
Controlling process
improvement projects
Monopoly –
mechanism
design game
REAL TQM
Stag Hunt – trust game of
doing “real TQM” or “fake
TQM” depends on culture
Matching Pennies – zero sum quality
control game based on having “real TQM”
management commitment
Emancipation
by academic
idealism
Summary of presentation
• Motivation
– Problem: Critical systems are getting too complex to be controllable
– Possible solution: Bootstrap Algorithm (BA), if it works as claimed
• Theoretical model and hypotheses
– A game theoretical perspective on total quality management (TQM)
– Interpreting the BA through Monopoly and Genetic Algorithms (GA)
– Testable BA hypothesis: The BA is efficient, stable and optimal
• Research method and results
– 20 years of action research, three cycles; DNMI + NTAX + NTAX/UiO
– BA hypothesis supported
• Contributions to theory and implications for practice
– Use of Monopoly, GA and game theory to strengthen BA theory
– The BA is useful for implementing TQM in complex environments