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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