Lugano Summer School
OF SYSTEMS DESIGN
Continuing Education in Systems Thinking
Università della Svizzera Italiana (USI), Lugano, Switzerland
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Lugano Summer School OF SYSTEMS DESIGN Continuing Education in Systems Thinking Università della Svizzera Italiana (USI), Lugano, Switzerland |
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Note: The Summer School has ceased operations. |
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No further Doctoral and Postdoctoral Summer Schools or other events are planned. |
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(See
the "Announcements"
page) |
Doctoral and Postdoctoral Summer School on Soft and Critical Systems Thinking:
«Systems Thinking for Improving my Research and Professional Practice»
(18-29 June 2012)
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If
these themes interest you, the Lugano Doctoral and Postdoctoral
Summer School 2012 on Soft and Critical Systems Thinking
(LSS 2012) might be for you!
Faculty
(see "Faculty" page)
Topics and learning aim Applied systems thinking is about improving the practice of professional intervention or other forms of applied research and expertise. But what does it mean to "improve" the practice of research and professional intervention? What can applied systems thinking, and in particular the development of soft and critical systems methodologies such as Soft Systems Methodology (SSM) and Critical Systems Heuristics (CSH), contribute to good practice? This Summer School offers you a unique opportunity to get a first-hand introduction to SSM and CSH by their original developers, Professors Peter Checkland and Werner Ulrich, and to discuss with them the ways applied systems thinking may help you improve your research or professional practice.
Format Taught classes with discussions and exercises; 10 morning sessions of 3¼-3½ hours each (including a half-hour break). Coffee/tea and snacks/biscuits during sessions. Informal mood!
Total workload The total workload will be about 42 hours, including required reading and exercises but excluding time for optional essay writing if you elect the "publication option" mentioned below. For details, see the page "Workload, Class Schedule, Grading, Certificate, Credits" of this site.
Publication option Participants will have the option of preparing a paper in which they connect the ideas discussed in the Summer School to their current major research or professional projects, as a basis for subsequent publication. To help participants in achieving a publishable result, the Summer School will support those electing this option in the following ways:
Program
Description of the two main courses
Course Goal To provide an appreciation of the rationale and nature of Soft Systems Methodology (SSM) as an operationalization of "soft" or "interpretive" systems thinking. How can we deal systematically with unclear, messy problem situations so as to arrive at a shared understanding?
Course Summary The course will cover the emergence of soft systems thinking and SSM in the light of the failure of conventional systems engineering to cope with problem situations outside those defined in terms of technical objectives. SSM will be presented as a framework for tackling ill-defined problem situations with a view to taking action to improve them. The emphasis will be on understanding systems thinking as a systematic process of learning; as a learning cycle with specific principles and tools for exploring problem situations and action proposals from multiple perspectives. Its practice will be described and illustrated through examples and exercises drawn mainly from the areas of corporate and public management and of information systems design. Finally, the "mindset" and craft skills conducive to good practice will be discussed.
Course Outline
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(i) |
Why soft systems thinking? The rationale and nature of soft systems methodology – What can SSM be used for, why is it needed? |
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(ii) |
SSM core concepts and principles: Hard and soft systems thinking, action research, rich pictures and root definitions, purposeful activity models, action to improve. |
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(iii) |
SSM process: Intervention as a learning cylce; Analysis One, Two, and Three. |
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(iv) |
SSM practice: SSM in action – some essential craft skills and practical challenges. |
Course Goal To introduce the participants to the notion of critical systems thinking and how it translates into reflective professional practice. How can we become "good" or "competent" practitioners and researchers?
Course Summary The course will introduce Critical Systems Heuristics (CSH) as a framework for practicing critical systems thinking. What does critique mean, why is it essential for any kind of systems thinking (hard, soft, or critical), and how do we practice it systematically? The aim will be seen in developing our over-all competence as applied researchers or professionals rather than merely in equipping us with yet another specialized methodology or tool; that is, CSH will be understood as enhancing rather than replacing the use of hard or soft systems thinking approaches or any other tools. Accordingly, the emphasis will be put on what systems thinking can contribute to good research and professional practice regardless of the research methods and intervention tools used, and on the philosophical issues this quest for good practice raises. Examples and exercises will be drawn mainly from the areas of public policy making and planning (e.g., social and environmental planning, energy policy, public health), but participants will also be welcome to apply what they learn to their own professional experiences or current projects.
Course Outline
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(i) |
Why critical systems thinking? The rationale and nature of critical systems heuristics – What can CSH be used for, why is it needed? |
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(ii) |
CSH core concepts and principles: Mapping and designing situations – boundary judgments, reference systems, boundary categories and questions, ideal vs. actual mapping. |
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(iii) |
CSH process: The process of boundary critique: systemic triangulation, forms of boundary reflection and discourse. |
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(iv) |
CSH practice: Towards reflective practice –some essential craft skills and practical challenges. |
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Doctoral and Postdoctoral Summer School on Soft and Critical Systems Thinking:
«Integrating SSM and CSH into my Research and Professional Practice»
(2-13 June 2008)
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Are you interested in integrating principles of soft and critical systems thinking with your current research or professional practice? Would you like to get a first-hand introduction to Soft Systems Methodology (SSM) and Critical Systems Heuristics (CSH), the two major current approaches of soft and critical systems thinking? If these themes interest you, the Lugano Doctoral and Postdoctoral Summer School on Soft and Critical Systems Thinking might be for you. |
Faculty
(see "Faculty" page)
Topics and Learning Aim The learning aim will be that the participants acquire an authentic understanding of Soft Systems Methodology (SSM) and Critical Systems Heuristics (CSH), as the two major available approaches of "soft" and "critical" systems thinking, respectively. Accordingly, the two approaches are introduced by their originators. No other educational opportunity anywhere else offers this unique opportunity of simultaneously working with Professors Checkland and Ulrich, so that you can not only get a first-hand knowledge of the two approaches but also explore the ways they complement one another (both instructors will be present in all sessions) and together might strengthen your current research or professional practice. As an outcome of this Summer School, participants should be able to start practicing the two approaches in a way that is conducive to reflective professional practice, and should also have a good notion as to how they will integrate SSM and CSH into their current major research projects or professional mandates.
Format Combination of taught classes and workshop sessions.
Total workload The total workload will be about 45 hours, excluding time for optional essay writing if you elect the "publication option" mentioned below. For details, see the page "Workload, Class Schedule, Grading, Certificate, Credits" of this site.
Publication option Participants will have the option of preparing and (if desired) presenting a paper in which they connect the ideas discussed in the Summer School to their current major research or professional projects, as a basis for subsequent publication. To help participants in achieving a publishable result, the Summer School will support those electing this option in the following ways:
Program
Description of the two introductory courses
Course Goal To provide an appreciation of the history and nature of Soft Systems Methodology (SSM) so that students are in a position to begin to use it to tackle real-world problem situations.
Course Summary The course will cover the emergence of soft systems thinking and SSM in the light of the failure of systems engineering to cope with problem situations outside those defined in terms of technical objectives. SSM as a whole will be covered in its interpretive context; it will be treated as a systemic learning system with both “constitutive” and “strategic” rules. The methods which form the parts of the approach will be described and illustrated in practical examples. The use of SSM as a whole will be illustrated in real-world applications in "management" situations and in the field of information systems. Finally, the course will offer some reflections on the 30-year program of action research in which SSM was developed.
Course Outline
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(i) |
The emergence of SSM. Systems engineering and its failure in “management” situations. The emergence of interpretive systems thinking in its interpretive context. |
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(ii) |
SSM I: Basic concepts and tools. |
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(iii) |
SSM II: Applications (exercises and discussion). |
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(iv) |
SSM III: SSM in action in real-world situations. |
Course Goal To introduce the participants to the notion of critical systems thinking and how it translates into reflective professional practice. How can we become competent practitioners and researchers?
Course Summary In this course we aim to gain a new understanding of systems thinking as "critical" systems thinking (CST). What does critique mean, and what is its role in systems thinking? We will learn to understand systems thinking as a form of critique, and in this way will begin to appreciate the meaning and relevance of critical systems thinking for reflective research and practice. We will then introduce Critical Systems Heuristics (CSH) as a framework for practicing CST.
Course Outline
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(i) |
The critical turn of systems thinking. Systems thinking and the quest for comprehensiveness; the problem of holism. The critical significance of the systems idea; systems thinking as a form of critique. Heuristics and critique; critical systems heuristics as a way to practice critical systems thinking. |
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(ii) |
Critical Systems Heuristics I. Some basic lessons in critical systems thinking (with short exercises). The core principle: systemic boundary critique. Boundary categories and questions. |
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(iii) |
Critical Systems Heuristics II. Practicing boundary critique: three basic settings. Systemic triangulation: dealing with conflicting "facts" and "values." The unfolding process: stages of ideal mapping. The emancipatory employment of boundary critique. |
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(iv) |
Towards reflective practice. The unsolved problem of practical reason: towards a practicable model of rational systems practice. Critical systems thinking and professional ethics. The quest for professional competence: rethinking our notion of professional competence. |
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Young Reseachers' Conference (18-29 June 2007)
Special Program in cooperation with the
Business Ethics
Center of Corvinus University,
Budapest, Hungary,
on Systems Design and Ethical Practice:
"Business
Ethics, Professional Ethics, and Ethics of Whole Systems"
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Are you interested in the relationship between systemic thinking and ethical practice? Would you like to familiarize yourself with a broad spectrum of contemporary ideas on business and professional ethics? Do you feel calls for ethical practice often lack clear theoretical and methodological foundations and, based on them, practical tools? Are you looking for an academic event that combines the broadness of inputs that you can get from a conference with the didactic guidance you expect from a Summer School? If so, this Young Researchers' Conference should interest you. |
Host Faculty
Visiting Faculty
Program
Topic 1 – Basic Challenges
Topic 2 – Solution Concepts (I): Theoretical and Methodological Foundations
Topic 3 – Solution Concepts (II): Practical Tools
Topic 4 – Creating Impetus for Change: Essential Sources of Motivation and Legitimacy
Topic 5 – Conclusions: How Can We Promote Business and Professional Ethics, and How Not?
Didactic format Each topic will comprise two sessions of 3½ hours, including two coffee breaks per session (ten morning sessions in total), and will consist of three presentations and a final moderated discussion with comments prepared by both participants and faculty. Presentations will be ¾-1 hour.
Total workload The total workload will be about 42-45 hours, or 50-60 hours for participants electing to submit a publication. For details, see the page "Workload, Class Schedule, Grading, Certificate, Credits" of this site.
Summer School reader All presentations will be made available to participants in a Reader (distributed in digital form) prior to the Summer School, as a basis for preparing their comments as well as for drafting their individual essay (see below).
Publication option Participants may opt to write an individual essay on selected topics of the Summer School, with a view to producing a publishable result. The guiding question will be: How do I integrate the ethical ideas presented in the Summer School into my personal research and/or practice? For those participants choosing this option, additional afternoon sessions may be organized in the second week, so that they have an opportunity to present their drafts and receive feedback from both Faculty members and participants. The best resulting papers will be selected for publication in the Summer School book (see below)..
Summer School book Final versions of all invited contributions and (extracts of) discussion transcripts, along with final versions of the best papers submitted by participants, will be published in a post-Summer School book.
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Doctoral Summer School (30 May-10 June 2005) Since LSS 2005 will be held as a Doctoral Summer School, both the academic program and the didactic format will be different from the past. The following is a tentative outline that may still be subject to modifications.
Topics and learning goal The learning goal of LSS 2005 will be to explore possibilities for an integration of "soft" and "critical" systems thinking approaches, as represented by Soft Systems Methodology (SSM) and Critical Systems Heuristics (CSH). As an outcome of the Summer School, participants should not only understand the underlying assumptions and the application of the two approaches so that they can begin to practice them, but should also learn to overcome any false opposition of "hard," "soft" and "critical" systems thinking in favor of reflective professional practice.
Faculty Professors Peter B. Checkland, Lancaster, United Kingdom, and Werner Ulrich, Fribourg, Switzerland (see "Faculty" page).
Format The new format will be shorter than in previous years and will be more workshop-like. Didactically, we will use a combination of taught classes and workshop sessions.
Program Prof. Checkland will start out with a short course on Soft Systems Methodology (SSM), followed by a discussion session with him. Prof. Ulrich will then give a short course on Critical Systems Heuristics (CSH), equally followed by a discussion session. Subsequently, we switch to a workshop format in which the participants, together with the two professors, will begin to explore similarities and differences of the two approaches and, on this basis, will each develop their personal framework for integrating SSM and CSH into their future research and professional practice. They will be asked to apply this framework to a concrete case that is of current interest to them or, alternatively, to prepare a short presentation in which they outline the way they will use the framework in future. Some of these applications or application proposals will be presented and analyzed in class. Finally, the participants will define the ways in which they will transfer their new understanding into practice.
The academic program thus presents itself as follows:
Description of the two introductory courses
Course Goal To provide an appreciation of the history and nature of Soft Systems Methodology (SSM) so that students are in a position to begin to use it to tackle real-world problem situations.
Course Summary The course will cover the emergence of soft systems thinking and SSM in the light of the failure of systems engineering to cope with problem situations outside those defined in terms of technical objectives. SSM as a whole will be covered in its interpretive context; it will be treated as a systemic learning system with both “constitutive” and “strategic” rules. The methods which form the parts of the approach will be described and illustrated in practical examples. The use of SSM as a whole will be illustrated in real-world applications in “management” situations and in the field of information systems. Finally, the course will offer some reflections on the 30-year program of action research in which SSM was developed.
Course Outline
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(i) |
The emergence of SSM. Systems engineering and its failure in “management” situations. The emergence of interpretive systems thinking in its interpretive context. |
|
(ii) |
SSM I: Basic concepts and tools. |
|
(iii) |
SSM II: SSM in action in real-world situations. |
Course Goal To introduce the participants to the notion of critical systems thinking and how it translates into reflective professional practice. How can we become competent practitioners and researchers?
Course Summary In this course we aim to gain a new understanding of systems thinking as "critical" systems thinking (CST). What does critique mean, and what is its role in systems thinking? We will learn to understand systems thinking as a form of critique, and in this way will begin to appreciate the meaning and relevance of critical systems thinking for reflective research and practice. We will then introduce Critical Systems Heuristics (CSH) as a framework for practicing CST.
Course Outline
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(i) |
The critical turn of systems thinking. Systems thinking and the quest for comprehensiveness; the problem of holism. The critical significance of the systems idea; systems thinking as a form of critique. Heuristics and critique; critical systems heuristics as a way to practice critical systems thinking. |
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(ii) |
Critical Systems Heuristics I. Some basic lessons in critical systems thinking (with short exercises). The core principle: systemic boundary critique. Boundary categories and questions. |
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(iii) |
Critical Systems Heuristics II. Practicing boundary critique: three basic settings. Systemic triangulation: dealing with conflicting "facts" and "values." The unfolding process: stages of ideal mapping. The emancipatory employment of boundary critique. Towards reflective practice. |
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The academic program of LSS 2003 was very much along the lines of the successful program of 2002, except that Professor Hans Daellenbach returned with a new version of his much-appreciated 2001 introductory course, to replace Professor Jonathan Rosenhead's equally appreciated course of 2002. Professor Rosenhead may be returning in future years.
Course Goal To provide participants with a shared framework of systems concepts as a basis for problem analysis and structuring. The goal is to develop skills for capturing and representing essential aspects of a problem situation in systems terms, as a first step towards more insightful decision making.
Course Summary The main focus of the course is on systems thinking and its role and use in systems methodologies for insightful decision making. This requires a basic understanding of systems concepts, which is the first topic of the course. Since an appropriate system description for a decision problem depends on a thorough grasp of the context in which the problem is embedded, we next look at aids to capture the problem situation. We learn to use diagrammatic tools to represent relevant systems aspects. Finally, we incorporate systems thinking and these aids into a general framework of systems methodologies and give a brief overview of how "hard" and "soft" methodologies can support processes of problem analysis and structuring.
Course Outline
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(i) |
Systems concepts and systems thinking. Complexity, reductionist and cause-and-effect thinking, systems thinking. Systems as human conceptualizations. Basic systems concepts: inputs, transformation process, outputs; environment; system boundaries; emergent properties; hierarchy of systems (narrow system of interest, wider system of interest, relevant environment). World views and their effect on boundary choices for narrow and wider systems of interest. Examples and exercises. |
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(ii) |
System behavior; practical approaches to capture problem situations. System behavior and state of system, feedback in systems, control of system behavior; mind maps and rich pictures to represent a problem situation; cognitive mapping to capture an individual's view of the problem situation. Examples and exercises. |
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(iii) |
Systems models. Type of models; diagrammatic aids to represent systems or aspects of systems (causal-loop diagrams, influence diagrams, various flow charts). Examples and exercises. |
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(iv) |
A framework for systems methodologies. Problem formulation, systems modeling, systems improvement/exploration, implementation; hard versus soft systems approaches. Brief review of several problem structuring methods such as strategic option development and analysis (SODA), strategic assumption surfacing and testing (SAST), strategic choice approach, total systems intervention (TSI), and multimethodology. |
Course Goal To provide an appreciation of the history and nature of Soft Systems Methodology (SSM) so that students are in a position to begin to use it to tackle real-world problem situations.
Course Summary The course will cover the emergence of soft systems thinking and SSM in the light of the failure of systems engineering to cope with problem situations outside those defined in terms of technical objectives. SSM as a whole will be covered in its interpretive context; it will be treated as a systemic learning system with both “constitutive” and “strategic” rules. The methods which form the parts of the approach will be described and illustrated in practical examples. The use of SSM as a whole will be illustrated in real-world applications in “management” situations and in the field of information systems.
Finally the course will cover reflections on the 30-year program of action research in which SSM was developed.
Course Outline
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(i) |
Systems engineering and its failure in “management” situations. |
|
(ii) |
The emergence of SSM: the whole in its interpretive context. |
|
(iii) |
SSM: the parts, constitutive and strategic. |
|
(iv) |
SSM in action in real-world situations. |
Course Goal The main objective of this topic is to introduce the students to the use of quantitative modeling and simulation in the design and analysis of complex systems.
Course Summary Particular emphasis will be given to "Vensim," a widely used software for modeling and simulating complex systems based on System Dynamics. Using examples from the management and engineering fields, the course will first explain the use of ordinary differential equations for the purpose of describing systems. Basic concepts of modeling and simulation such as the importance of causal-loops, positive and negative feedbacks, S-shaped growth structures, etc. will be introduced.
Based on these fundamentals, the second, main part of the course will take place in the computer lab. Vensim will be introduced in a demonstration session. Subsequently, the participants will be invited to apply this tool for developing some simple models using the concepts of System Dynamics.
Previous knowledge: Although quantitative in its orientation, the course does not require any advanced mathematical knowledge.
Course Outline
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(i) |
Systems design and modeling with particular emphasis on simulation models. Structural modeling: methods and tools for the identification of elements and the analysis of a qualitative structure (feedback analysis, pulse analysis, etc.) |
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(ii) |
Simulation models. Different types of simulation models. The use of models: if–then analysis through simulation, experimentation, validation and related concepts. System Dynamics as a modeling methodology: the basic concepts and some simple models. The importance of feedback loops. The principles of System Dynamics; discussion of "System Dynamics, system thinking and soft OR," a paper of Jay Forrester. |
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(iii) |
Computer applications. Building system dynamics models with and without software packages such as Stella, I-Think, Powersim, or Vensim: the graphic representation and the associated mathematical structure. Demonstration of Vensim. Analysis of simple feedback loops (of first and second order, positive and negative). Practical exercise. |
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(iv) |
Practice and Conclusions. Discussion of the practical exercise done in the computer lab. Lessons to be learned. Evt. (if time is sufficient): advanced topics in System Dynamics (delays, quantifiable and non-quantifiable variables, multipliers, use of historical data, etc.). Examples of the use of System Dynamics in area such as engineering, social sciences, economics, environmental sciences and global models. |
Course Goal To introduce the participants to the notion of critical systems thinking and how it translates into reflective professional practice. How can we become competent practitioners and researchers?
Course Summary Mastery of methods is not the same as competence. Professional intervention cannot do without appropriate methods; but true professional competence reveals itself by the way in which it deals with its own limitations. In particular, methodological competence does not dispense professionals from making assumptions about what is to be considered relevant in a concrete problem situation and what would constitute an improvement of the situation. Contemporary "hard" and "soft" systems methodologies are strong in supporting processes of problem structuring and solving, but they are of limited use in surfacing and questioning the normative underpinnings of professional intervention. Critical systems heuristics (CSH) is an approach that can help us in this effort.
In this course we aim to gain a new understanding of systems thinking as "critical" systems thinking (CST). The idea is not to propose an alternative to "hard" and "soft" approaches but rather, to increase our competence in using these or any other approaches to professional intervention.
Course Outline
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(i) |
The critical turn of systems thinking. Systems thinking and the quest for comprehensiveness; the problem of holism. The critical significance of the systems idea; systems thinking as a form of critique. Heuristics and critique; critical systems heuristics as a way to practice critical systems thinking. |
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(ii) |
Critical Systems Heuristics I. Three basic lessons in critical systems thinking (with short exercises). The core concept of systemic boundary critique; boundary categories and questions. Practical exercise. |
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(iii) |
Critical Systems Heuristics II. The process of boundary critique; three basic settings. The principle of systemic triangulation. Stakeholder participation. Working through the context of application. Actual versus ideal mapping; pluralistic evaluation; stages of ideal mapping. The emancipatory employment of boundary critique. |
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(iv) |
The quest for professional competence. Two strands of critical systems thinking: CSH and TSI. How should we choose among different approaches? Beyond methodology choice: critically systemic discourse. Towards reflective practice: rethinking our notion of professional competence. |
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Course Goal Students will be introduced to some of the main methods for helping the multiple stakeholders in a complex, 'wicked' problem situation to agree on a shared problem formulation and a away forward. The aim is for them to gain both an awareness of the importance of problem framing and an appreciation of the range of methods available to achieve it.
Course Summary Problem Structuring Methods (PSMs) are a group of methods to help people who need to make progress in a mutual problem situation despite uncertainties, intangibles, and their diverse perspectives and interests. They do so by using models, usually verbal rather than quantitative, to structure information elicited from the participants, and to use these models in a workshop situation to establish agreed commitments to action. The course will give students an overview of these methods, and introduce them in particular to Strategic Options Development and Analysis (SODA) and to Strategic Choice Analysis (SCA). Students will have the opportunity to use the methods in case exercises.
Students will find it an advantage to have access to J. Rosenhead and J. Mingers (eds.), Rational Analysis for a Problematic World Revisited: problem structuring methods for complexity, uncertainty and conflict, Wiley, Chichester 2001. Copies of the book will be made available in class.
Course Outline
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(i) |
Overview and introduction. Problem structuring methods. Strategic Options Development and Analysis I. |
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(ii) |
Strategic Options Development and Analysis. Strategic Options Development and Analysis II. Oval Mapping. |
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(iii) |
Strategic Choice Analysis. Strategic Choice I. Strategic Choice II. |
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(iv) |
Making problem structuring methods work. Strategic Choice III. Robustness Analysis. Making PSMs work. |
Course Goal The main objective of this topic is to introduce the students to the use of quantitative modeling and simulation in the design and analysis of complex systems.
Course Summary Particular emphasis will be given to "Vensim," a widely used software for modeling and simulating complex systems based on System Dynamics. Using examples from the management and engineering fields, the course will first explain the use of ordinary differential equations for the purpose of describing systems. Basic concepts of modeling and simulation such as the importance of causal-loops, positive and negative feedbacks, S-shaped growth structures, etc. will be introduced.
Based on these fundamentals, the second, main part of the course will take place in the computer lab. Vensim will be introduced in a demonstration session. Subsequently, the participants will be invited to apply this tool for developing some simple models using the concepts of System Dynamics.
Previous knowledge: Although quantitative in its orientation, the course does not require any advanced mathematical knowledge.
Course Outline
|
(i) |
Systems design and modeling with particular emphasis on simulation models. Structural modeling: methods and tools for the identification of elements and the analysis of a qualitative structure (feedback analysis, pulse analysis, etc.) |
|
(ii) |
Simulation models. Different types of simulation models. The use of models: if–then analysis through simulation, experimentation, validation and related concepts. System Dynamics as a modeling methodology: the basic concepts and some simple models. The importance of feedback loops. The principles of System Dynamics; discussion of "System Dynamics, system thinking and soft OR," a paper of Jay Forrester. |
|
(iii) |
Computer applications. Building system dynamics models with and without software packages such as Stella, I-Think, Powersim, or Vensim: the graphic representation and the associated mathematical structure. Demonstration of Vensim. Analysis of simple feedback loops (of first and second order, positive and negative). Practical exercise. |
|
(iv) |
Practice and Conclusions. Discussion of the practical exercise done in the computer lab. Lessons to be learned. Evt. (if time is sufficient): advanced topics in System Dynamics (delays, quantifiable and non-quantifiable variables, multipliers, use of historical data, etc.). Examples of the use of System Dynamics in area such as engineering, social sciences, economics, environmental sciences and global models. |
Course Goal To provide an appreciation of the history and nature of Soft Systems Methodology (SSM) so that students are in a position to begin to use it to tackle real-world problem situations.
Course Summary The course will cover the emergence of soft systems thinking and SSM in the light of the failure of systems engineering to cope with problem situations outside those defined in terms of technical objectives. SSM as a whole will be covered in its interpretive context; it will be treated as a systemic learning system with both “constitutive” and “strategic” rules. The methods which form the parts of the approach will be described and illustrated in practical examples. The use of SSM as a whole will be illustrated in real-world applications in “management” situations and in the field of information systems.
Finally the course will cover reflections on the 30-year program of action research in which SSM was developed.
Course Outline
|
(i) |
Systems engineering and its failure in “management” situations. |
|
(ii) |
The emergence of SSM: the whole in its interpretive context. |
|
(iii) |
SSM: the parts, constitutive and strategic. |
|
(iv) |
SSM in action in real-world situations. |
Course Goal To introduce the participants to the notion of critical systems thinking and how it translates into reflective professional practice.
Course Summary The course aims to support students in their quest for becoming competent professionals. Competence is related to the use of appropriate methods; but what matters even more is that whatever methods we apply, we do so in a self-reflective, critical way. Critical systems thinking (CST) is an approach that can help us in this effort.
Students will learn to understand why systems thinking is a form of critique, and in this way will begin to appreciate the meaning and relevance of critical systems thinking for Systems Design. Critical Systems Heuristics (CSH) will be introduced as a framework for putting CST into practice. As far as time allows, the course will conclude with a discussion of the problem of selecting and combining methods in a critical manner; how can we become reflective practitioners?
Course Outline
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(i) |
The critical turn of systems thinking. Why critical systems thinking in addition to hard and soft systems thinking? Systems thinking as a form of critique. Professional competence and reflective practice. Three basic lessons in critical systems thinking. |
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(ii) |
CST at work: Critical Systems Heuristics I. The core concept of systemic boundary critique; boundary categories and questions. Practical exercise. |
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(iii) |
CST at work: Critical Systems Heuristics II. Alternative settings for practicing systemic boundary critique. The process of unfolding. The emancipatory employment of boundary judgments. Implications for Reflective Practice; some guidelines and an example. |
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(iv) |
The quest for professional competence. How can/should we combine different approaches? Critique of current concepts of combining methods; from informed methodology choice to critically systemic discourse. |
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Course Goal This course aims to provide the participants with a shared conceptual framework for the subsequent courses. To this end, the course will (a) offer a condensed primer to a number of systems concepts and tools that are basic to Systems Design, regardless of the specific approach or methodology used; and (b) try to build a bridge between the “hard” and “soft” systems approaches covered by the other courses.
Course Summary Cause-and-effect and reductionist thinking — the traditional approaches to problem solving — cannot adequately deal with many decision problems in today's turbulent and complex world. The planned benefits are often eroded or negated by unplanned adverse outcomes, both inside and outside the planning organization, through the inappropriate or careless selection of which aspects of the problem context are considered relevant and which ones are ignored. Systems thinking tries to remedy this.
The module starts with a brief review of essential systems concepts and systems models, including various systems diagrams. It discusses the effect of boundary selection on stakeholders, their implied objectives, and the decision choices. This reveals the inherent subjectivity of system definition and boundary selection. The insights gained are then applied to propose an effective OR/MS methodology that is more likely to result in better decision-making and to secure real and lasting improvements in performance. The module ends by contrasting hard OR/MS approaches with soft systems and problem structuring approaches to decision making.
Course Outline
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(i) |
Why systems thinking in addition to cause-and-effect and reductionist thinking? Concepts of effectiveness and efficiency; basic systems concepts; some examples of system descriptions. |
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(ii) |
Defining problem situations. Structural versus process approaches for describing a relevant system; systems models; diagrammatic tools for capturing system structure and behavior. |
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(iii) |
Analyzing systems. Viewing systems in a hierarchy of systems within systems; overview of OR/MS methodology: problem formulation or scoping – modeling – implementation. |
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(iv) |
“Hard” and “soft” systems thinking. Contrasting quantitative and problem structuring approaches; behavioral and philosophical assumptions; brief overview of some specific methods. Building the bridge from “hard” to “soft” approaches to Systems Design; role of hard approaches within soft approaches, particularly multicriteria approaches and System Dynamics; ethical considerations for system analysts. |
Course Goal The main objective of this topic is to introduce the students to the use of quantitative modeling and simulation in the design and analysis of complex systems.
Course Summary Particular emphasis will be given to System Dynamics, a widely used approach to the modeling and simulation of complex systems. Using examples from the management and engineering fields, the course will first explain the use of ordinary differential equations for the purpose of describing systems. Basic concepts of modeling and simulation such as the importance of causal-loops, positive and negative feedbacks, S-shaped growth structures, etc. will be introduced, followed by an overview of some of the most important modeling approaches and of the use of spreadsheets (Excel) as a modeling tool.
Based on these fundamentals, the second part of the course will introduce System Dynamics as a methodology for the design and analysis of complex system. Particular attention will be given to the presentation of systems modeling as a scientific method, discussing themes such as objectivity, bias, testability, validation, etc. During the course, students have to develop some simple models using the concepts of Systems Dynamics. Depending on the interest of the participants, they can choose to implement some of these models in the computer laboratory, practicing simulations by means of the “Vensim” simulation software.
Previous knowledge: Although quantitative in its orientation, the course does not require any advanced mathematical knowledge. As far as necessary, a basic understanding of the use of differential and integral calculus will be developed in the course itself. Students who wish to do some practical work in the computer lab should of course bring along some practice using the computer.
Course Outline
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Systems design and modeling with particular emphasis on simulation models. Structural modeling: methods and tools for the identification of elements and the analysis of a qualitative structure (feedback analysis, pulse analysis, etc.) |
| (ii) |
Simulation models. The different types of simulation models: continuous, discrete with respect to time and/or space (discrete event models, discrete models, cellular models, differential equations models, etc.). The use of models: if–then analysis through simulation, experimentation, validation and related concepts. System Dynamics as a modeling methodology: the basic concepts and some simple models. The importance of feedback loops. The principles of System Dynamics; discussion of "System Dynamics, system thinking and soft OR," a paper of Jay Forrester. |
| (iii) |
Computer applications. Building system dynamics models with and without a System Dynamics oriented software: the graphic representation and the associated mathematical structure, examples of building and using models with software such as Stella or I-Think, Powersim, Vensim, etc. Analysis of simple feedback loops (of first and second order, positive and negative). |
| (iv) |
Advanced topics in System Dynamics (delays, quantifiable and non-quantifiable variables, multipliers, use of historical data, etc.). Examples of the use of System Dynamics in area such as engineering, social sciences, economics, environmental sciences and global models. |
Course Goal To provide an appreciation of the history and nature of Soft Systems Methodology (SSM) so that students are in a position to begin to use it to tackle real-world problem situations.
Course Summary The course will cover the emergence of soft systems thinking and SSM in the light of the failure of systems engineering to cope with problem situations outside those defined in terms of technical objectives. SSM as a whole will be covered in its interpretive context; it will be treated as a systemic learning system with both “constitutive” and “strategic” rules. The methods which form the parts of the approach will be described and illustrated in practical examples. The use of SSM as a whole will be illustrated in real-world applications in “management” situations and in the field of information systems.
Finally the course will cover reflections on the 30-year program of action research in which SSM was developed.
Course Outline
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(i) |
Systems engineering and its failure in “management” situations. |
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(ii) |
The emergence of SSM: the whole in its interpretive context. |
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(iii) |
SSM: the parts, constitutive and strategic. |
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(iv) |
SSM in action in real-world situations. |
Course Goal Students who successfully complete this course will (a) understand the meaning and relevance of critical systems thinking for Systems Design; (b) be able to apply Critical Systems Heuristics as a framework for putting such understanding into practice; (c) know how to apply and combine different systems approaches and other methodologies in a truly critical way; and (d) redefine their concept of professional competence in terms of reflective practice and critically systemic discourse.
Course Summary The course introduces the participants to the notion of critical systems thinking and how it translates into reflective professional practice.
Course Outline
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(i) |
Critical systems thinking. Why critical systems thinking in addition to hard and soft systems thinking? How can/ should we combine these different approaches to Systems Design? Alternative models of rational practice; the critical turn. |
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(ii) |
Critical Systems Heuristics. Three crucial lessons in critical systems thinking. The core concept of systemic boundary critique; boundary categories and questions. |
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(iii) |
Towards Reflective Practice. Three ways to practice systemic boundary critique. The process of unfolding. The emancipatory employment of boundary judgments; implications for Reflective Practice; some guidelines and an example. |
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(iv) |
The quest for professional competence. Back to the beginning: How can/ should we combine different approaches? Critique of current concepts of combining methods; from informed methodology choice to critically systemic discourse. |
Course Goal To relate the specific field of information systems (IS) and information technology (IT) as represented by IT-artifacts to the philosophy and practice of systems, that is, to the historical and present attempts to look at problems in their wider economic and ethical context.
Course Summary Central to this course is C. West Churchman’s concept of “inquiring system”. Information systems will be understood as designs for inquiry. Accordingly, the course will analyze (a) how the concept of inquiry developed in relation to the design of inquiring systems, and (b) how it may orient the future development of IS and IT-artifacts. This is done by reviewing some basic models of knowledge organization in terms of historical designs (or archetypes, styles) of information systems. They imply different conceptions of data, information, and knowledge; these conceptions in turn shape contemporary studies of knowledge management, executive or strategic information systems, as well as trends of the so-called information society. The purpose is to give a philosophical basis for IT that prepares the students for their own development of new design methods, and for evaluating what is really new and valuable in present research and commercial trends.
Course Outline
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(i) |
Overview. 40 years of development of information systems, based on literature, personal experiences, and participation. Waves of popularity as represented by bywords, slogans and catch-phrases such as data management, management science, cybernetics, operations research, management information systems, very large databases, artificial intelligence, decision support systems, multimedia, virtual reality, e-commerce, e-education, e-government, e-mobile. |
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(ii) |
The role of intellectuals in research and development as represented by universities, business schools and institutes of technology. The rise of academic disciplines that deal with computers and computerization. Their historical settings and mother-disciplines. Approaches to IS-design: life cycle, structured programming, programming environments, business process re-engineering BPR, enterprise resource planning ERP/SAP. |
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(iii) |
Inquiring systems and conceptions of information as related to knowledge and systems, as emerging from concrete industrial problems of "quality of information". Inquiry as related to design, programming, systems, artificial intelligence, object orientation, data representation, conflict management and executive-strategic IS/EIS, multidisciplinary and pluralistic interaction systems. Multicultural aspects as information and action in ancient Chinese and Hindu thought. |
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(iv) |
Perspectives. Present and foreseeable opportunities and problems in practice and research, in view of "everything" and the aesthetization implied in multimedia and in the integration of computers and communications. The place of aesthetics in relation to science and ethics, and its expression in the ongoing commercialization and media rhetoric, and in postmodern trends of design in academia. |