John Molineux, “Macro-Cycles of Change – Learning from An Organisation’s History”
The paper reviews the macro-political and economic cycles impacting a large government agency in Australia and its change processes using the theory of punctuated equilibrium. The paper extends original work published in 2002 to include the current global economic crisis and change in the Australian federal government. It analyses problems in the corporate support area of the organisation, which seemingly has not heeded lessons learnt from its history and earlier major change programs.
The paper reviews proposed changes in the light of systemic thinking, systems archetypes, and a causal loop diagram. Conclusions are drawn that the organisation did not take into account the macro-cycles of change, nor the unintended consequences arising from decisions to change. Recommendations for improvement are made.
Takafumi Nakamura, Kyoichi Kijima, “A Methodology to Prolong System Lifespan and Its Application to IT Systems”
A system failure model to prolong system lifespan is proposed, for the purpose of preventing further occurrence of these failures. The authors claim such a methodology should have three features.
First it should clarify the structure of failure factors, second it should surface hidden failure factors using statistic method especially corresponding analysis and finding the way to change.
The proposed methodology is fundamentally different from the one to identify the root cause of the system failures in the sense of that it encompasses system failures as a group not as a single event.
An understanding system failure correctly is crucial to preventing further occurrence of system failures. Quick fixes can even damage organizational performance to a level worse than the original state. In this sense the proposed methodology is applicable over the long time spans and therefore could be useful to confirm the effectiveness of the counter measures without introducing any side effects. Then an application example in IT engineering demonstrates that the proposed methodology proactively prolong system life learning from previous system failures.
Key words: system failure model, structuring methodology, double loop learning, ISM, risk management
Louis Klein and Ernst Daniel Röhrig, “Balancing Cross-Cultural Complex Project Management: Untying Gordian Knots of Social Complexity, Or Towards An Ecology of Paradigms”
Managing cross-cultural complex projects
Projects nowadays turn out to be cross-cultural and complex projects. Project management has to deal with increasingly different expectations and cultural perspectives of stakeholders, clients, project managers and team members. Cross-cultural complex project management tries to handle the connectivity between the different views and expectations inside and outside of projects. If it fails, communication goes havoc, expectations run out of balance and behaviours become peculiar. It is the familiar catastrophe: schedules collapse, costs are running and quality deteriorates. – Wouldn’t it be nice to just execute to the plans best? “Projects fail on the human side”, they say.
Balancing technical and social complexity
We are quite advanced to manage technical complexity, the scope, the scale, and the dynamics. We master engineering at its best, day by day. However, there is again this undecided client, this nagging NGO, this lousy project manager and this bean counting controller and all the others who sprout all kinds of peculiar behaviour. Handling the human side, managing social complexity is not our pride and joy. In fact we are used to look away, to avoid any kind of systematic approach. Yet, how long can we afford to continue? Balance is needed.
Towards an ecology of paradigms
And yet, social complexity is nothing new or special. It comes with the territory. It seems to be a Gordian knot. Dealing with it and managing social complexity shows up as a key competence for any successful project management. All these expectations and views within any complex projects cannot be untied technically or violently without causing more damage than benefit. Engineering is for technical systems; it is not an adequate paradigm for social systems. It is not a one size fits all kind of case. Additional models, methods and instruments are required refereeing to an alternative paradigmatic background. And it will never be an either or, it will always be a as well as. The next society’s practices will be based on an ecology of paradigms.
Tools to untie Gordian knots of social complexity
Models, methods and instruments referring to social sciences, or even Niklas Luhmann’s Theory of Social Systems, will create the practice of cross-cultural complex project management. The paper will give some examples like Stafford Beers Viable system model, Peter Checklands Soft Systems Methodologies and Noel Tichys GRPI instrument. They all provide successful approaches which can pay into a larger understanding of an ecology of paradigms that is able to meet cross-cultural complex project management requirements.
It is a shaky sea of change ahead. If we really want to improve on cross-cultural complex project management it will move us outside our comfort zone. Yet, the reward is tremendous: we will win commitment and contribution money cannot buy, cooperation and creativity will flow together into co-creation: and not only efficiency and effectiveness in cross-cultural complex projects will rise.
Anson Li and Kambiz Maani, “Decision-making in Complex Systems – Learning and Mental Models”
Bounded by limited cognitive capabilities, decision-makers resort to using mental models (constructed versions of real world dynamics) for decision-making and interventions, as studied notably, by Simon (1957, 1979, 1987), Morecroft (1983, 1985), Senge (1990), and Sterman (1989, 2000). Mental models are constantly updated with new experience and knowledge acquired, facilitating a learning process. Through this learning process, mental models can be refined to better represent real world dynamics.
Systems theory suggests that updates of mental models happen in continuous cycles involving conceptualisation, experimentation, and reflection (C-E-R) (Maani & Cavana, 2007), where decision-makers investigate problems and develop interventions (C), and then carry out the interventions (E). They then contemplate on outcomes of interventions and evaluate the appropriateness and effectiveness of their interventions (R). This forms the theoretical foundation and practice base of Learning Laboratory technology (Maani & Cavana, 2007). It is through the reflection step that mental models get updated for forthcoming decision cycles. This C-E-R cycle closely resembles a dynamic decision-making (DDM) process where decision-makers are constantly informed by feedbacks from outcomes of previous decision tasks.
This study investigates the learning process of decision-makers in DDM tasks in an experimental setting. Participants involved in simulated environments (Management Flight Simulators and Microworlds) are observed, with proceedings of their DDM tasks recorded and analysed to trace and identify patterns of learning. Updates of mental models are recognized in changes of participants’ performance, measured by their dynamic performance indicators and systems behaviour, before and after the decision tasks.
Findings of this research, drawing from over 220 experiments, show significant changes in mental models after participation in DDM tasks. However, the level of learning varies for different tasks and across different performance measures. Implications of these findings to other application and domains especially the learning laboratory technology will be discussed.
These authors will lead discussions following the style of the Singerian Inquiring System as practiced in the SIG on Systems Applications in Business and Industry.
daviding July 5th, 2009
Posted In: ISSS