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 President’s Commission, October 1979: Inadequate quality assurance Perrow (1984): Tightly coupled complex systems should be avoided Three Mile Island accident, Pennsylvania, March but can we?

Control crisis is followed by control revolution: Information society evolves Are they implementing Total Quality Management (TQM), or are they pretending to do so? How do people handle control crisis in highly complex environments?

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 Matching Pennies – zero sum quality control game based on having “real TQM” management commitment Stag Hunt – trust game of doing “real TQM” or “fake TQM” depends on culture Monopoly – mechanism design game Controlling process improvement projects Controlling the survival of the TQM programme Controlling cultural change

Cultivating information infrastructure on a mission to “conquer the world” The Health Information System Programme (HISP) controls and expands itself as a network of research and development across 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

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 Real World TQM installed base (“real TQM”) Model Monopoly game Model conclusions Bootstrap Algorithm Real world conclusions TQM information infrastructure (“real TQM”) Formulate Deduce Interpret RH1: The BA is stable RH: The BA is an optimal mechanism design for implementing TQM RH3: The BA is optimal RH2: The BA is efficient

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 : 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 : 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 : 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) THIRD CYCLEFIRST CYCLESECOND CYCLE Size of population (improv. projects)

Outcome of hypothesis test (RH1) Real World TQM installed base (“real TQM”) Model Monopoly game Model conclusions Bootstrap Algorithm Real world conclusions TQM information infrastructure (“real TQM”) Formulate Deduce Interpret RH1: The BA is stable RH: The BA is an optimal mechanism design for implementing TQM RH3: The BA is optimal RH2: The BA works

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) Real World TQM installed base (“real TQM”) Model Monopoly game Model conclusions Bootstrap Algorithm Real world conclusions TQM information infrastructure (“real TQM”) Formulate Deduce Interpret RH1: The BA is stable RH: The BA is an optimal mechanism design for implementing TQM RH3: The BA is optimal RH2: The BA works

BA optimality hypothesis (RH3) 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) By following optimal strategy it should take about 25 years to implement TQM at NTAX?

Outcome of hypothesis test (RH = RH1 + RH2 + RH3) Real World TQM installed base (“real TQM”) Model Monopoly game Model conclusions Bootstrap Algorithm Real world conclusions TQM information infrastructure (“real TQM”) Formulate Deduce Interpret RH1: The BA is stable RH: The BA is an optimal mechanism design for implementing TQM RH3: The BA is optimal RH2: The BA works

Contribution to knowledge 1: Monopoly as a model of II dynamics Old knowledge New knowledge Kernel theory

Contribution to knowledge 2: The BA as a Genetic Algorithm (GA) Old knowledge New knowledge Kernel theory Design theory

Contribution to knowledge 3: Use of game theory in action research 1. Diagnosis: Phenomenological attitude 3. Testing of treatment : Positivist attitude 2. Finding a treatment : Mathematical analysis of the game model

Implications for practice Matching Pennies – zero sum quality control game based on having “real TQM” management commitment Stag Hunt – trust game of doing “real TQM” or “fake TQM” depends on culture Monopoly – mechanism design game Controlling process improvement projects Controlling the survival of the TQM programme Controlling cultural change FAKE TQM REAL TQM Self-oppression through capitalist consumerism 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