Systems Thinking for Design Martin Kunc Associate Professor of - - PowerPoint PPT Presentation

Systems Thinking for Design

Martin Kunc Associate Professor of Management Science

Martin.Kunc@wbs.ac.uk

Warwick Business School

A bit of history

 Cross (2001) suggests the 1960s was the ‘design

science decade’ based on science, technology and rationalism to overcome the human and environmental problems that he believed could not be solved by politics and economics.

 System Dynamics (SD) also started in 1960s in the

MIT with similar ideas: the use of control theory to design social and economic policies to improve the performance of systems.

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A bit of history

 Many of the principles Forrester articulated were

targeted to modelling the design of corporations, especially in the seminal book “Industrial Dynamics”.

 Industrial Dynamics (1960) contributed with a set of

four principles for modelling of complex systems:

 counter-intuitive system behaviour is driven by system

structure,

 structure involves non-linear relationships,  simulation is necessary to explore behaviour, and  the application of the principles provides a way for

managers to improve the design of organizations.

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A bit of history

 Herbert Simon in “Sciences of the Artificial” made a

specific plea for the development of ‘a science of design’ in the universities: ‘a body of intellectually tough, analytic, partly formalisable, partly empirical, teachable doctrine about the design process.’

 Forrester, the founder of SD, has also made a plea in

the fiftieth anniversary of SD to have “universities of social system design” based on the principles of System Dynamics.

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Two areas to explore from SD in this presentation:

 System Dynamics as a body of intellectual, analytical

and teachable doctrine about the design of social systems.

 System Dynamics supporting the process of design

addressing project management dynamic issues, especially “rework cycle”

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System Dynamics as a tool for the design of social systems

www.neilengineering.co.uk

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System Dynamics as a tool for the design of social systems

 SD has been successfully embedded in a masters

programme for sustainable resource management (Biber and Kasperidus, 2004).

 Kunc and Morecroft (2007) discuss SD modelling for

strategic rehearsal to help people understand how strategies will perform over time, and what type of interventions can improve performance.

 Some authors have developed “archetype models”,

simple models, yet conceptualised through real cases to illustrate a key driver of the structure of dynamic complex systems: feedback loops

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System Dynamics as a tool for the design of social systems

 Modelling is perceived as a tool for conceptual

development as students articulate the problem and question the elements and linkages related to the problem.

 Students improve their skills for designing organisations

by understanding the strategic problem in terms of resources and feedback processes (Kunc, 2012).

 When students change variables and linkages, they

improve their mental models and the simulation helps them to learn how the new structure drives behaviour (Schaffernicht, 2006)

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System Dynamics as a tool for the design of social systems

 Main objectives in teaching SD as a tool for designing

 Use of time series to understand the behaviour over time of

system

 Identification of the structure of the system responsible for the

behaviour observed in terms of feedback loops

 Being able to replicate the behaviour observed using a

simulation model

 Explain the impact of changes in the design of the structure of

the system

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Project management dynamic issues

 The impact of the design errors is one of the

important issues related to factors generating project changes.

 Uncertainty propagates in a project as each activity is

influenced by/influences other upstream and downstream activities. Uniqueness, complexity, and uncertainty lead to significant cost and schedule

• ver-runs across many projects.

 There is a rich literature in system dynamics that

covers project modelling in general (Lyneis and Ford 2007) with particular contribution in the rework cycle formulation (Sterman 2000).

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Project management dynamic issues

 Formulating the multi-phase project models were

discussed in detail by (Ford & Sterman, 1998) in the semiconductor industry and many applications have used different variants of this formulation (Khoueiry, Srour, & Yassine, 2013).

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Conclusions

 SD can provide a useful platform to explore the

social dimensions and long term performance of the outcomes of design processes through “designing the social system” supporting the new designed product/service.

 SD can help making the process of design more

efficient by detecting issues in the design process that requires further resources to address.

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Questions

Martin.Kunc@wbs.ac.uk

Warwick Business School

References

Biber P, Kasperidus HD. 2004. Integrated modeling approaches and system dynamics in education related to sustainable resource management, forestry and land use management. In Proceedings of the 22nd System Dynamics Conference, Oxford, UK. Cross, Nigel (2001). Designerly ways of knowing: design discipline versus design

• science. Design Issues, 17(3), pp. 49–55.

Ford, D. N., & Sterman, J. D. (1998). Dynamic modeling of product development

• processes. System Dynamics Review, 14(1), 31–68.

Forrester, J. W. (1961). Industrial Dynamics. Lyneis, J. M., & Ford, D. N. (2007). System dynamics applied to project management : a survey , assessment , and directions for future research, 23(2), 157–189. Khoueiry, Y., Srour, I., & Yassine, A. (2013). An optimization-based model for maximizing the benefits of fast-track construction activities. Journal of the Operational Research Society.

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References

Kunc M, Morecroft J. 2007. System dynamics modelling for strategic

• development. In Supporting Strategy: Frameworks, Methods and Models,

O’Brien F, Dyson RG. (eds). Wiley: Chichester; 157–190. Kunc, M. (2012). Teaching strategic thinking using system dynamics: lessons from a strategic development course. System Dynamics Review, 28(1), 28-45. Schaffernicht M 2006. Detecting and monitoring change in models. System Dynamics Review 22(1): 73–88. Simon, H A . (1969), The Sciences of the Artificial, MIT Press, Cambridge, Mass.