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S ystems Analysis Laboratory Helsinki University of Technology 1 Systems Intelligence for Life Cycle Management - Shifting the Focus from Products to People.

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Presentation on theme: "S ystems Analysis Laboratory Helsinki University of Technology 1 Systems Intelligence for Life Cycle Management - Shifting the Focus from Products to People."— Presentation transcript:

1 S ystems Analysis Laboratory Helsinki University of Technology 1 Systems Intelligence for Life Cycle Management - Shifting the Focus from Products to People Raimo P. Hämäläinen

2 S ystems Analysis Laboratory Helsinki University of Technology 2 Disciplines for coping with complexity Operation Research / Management Science / Systems Analysis Develop generic tools and methods for structured problem solving and decision support. The “Science of Better” Goals: Improve problem solving by learning, understanding and communication Based on a systems thinking perspective

3 S ystems Analysis Laboratory Helsinki University of Technology 3 Multi-Criteria Decision Analysis (MCDA) Transparency in decision making – Integrated management of objective data and subjective values – Incorporation of risks and uncertainty Well developed theory Textbooks e.g.Belton, Stewart 2002; French et al Increasingly used in environmental management Introduced into Life Cycle Assessment literature in the late 1990’s ( Miettinen, Hämäläinen 1997)

4 S ystems Analysis Laboratory Helsinki University of Technology 4 Steps in MCDA Problem structuring Value focused thinking Identification of objectives and alternatives Interactive preference elicitation Composition of overall preferences and rankings Sensitivity analysis – what if Result: Transparent recommendation Tools and e-learning material available on the web:

5 S ystems Analysis Laboratory Helsinki University of Technology 5 Todays Topic Systems Thinking in LCM New lens: Systems Intelligence (SI) LCM is a systems approach Shifting the focus from products to people makes human thinking the driver for improvement SI + LCM = Ecological Intelligence Key perspective in Environmental Leadership

6 S ystems Analysis Laboratory Helsinki University of Technology 6 Systems Intelligence (Hämäläinen and Saarinen, 2004) Intelligent behaviour in the context of complex systems involving interaction,dynamics and feedback Combines human sensitivities with engineering thinking Pursuing the idea of making things work

7 S ystems Analysis Laboratory Helsinki University of Technology 7 Systems Intelligence A person with Systems Intelligence understands that she is always part of a system in her environment She perceives herself as part of the whole - her own influence upon the whole - the influence of the whole upon herself - she realizes that others in the system can have different views of the whole - she is able to act intelligently in the system

8 S ystems Analysis Laboratory Helsinki University of Technology 8 The SI perspective Helps to identify productive forms of action It is a competence that can be improved by learning Systems Intelligence is a basic form of human intelligence

9 S ystems Analysis Laboratory Helsinki University of Technology 9 Multiple Intelligences (Howard Gardner 1983) Linguistic Musical Logical-Mathematical Spatial Bodily-Kinesthetic The Personal Intelligences – intra / inter Plus higher-level cognitive capacities e.g. common sense and wisdom

10 S ystems Analysis Laboratory Helsinki University of Technology 10 SI and Multiple Intelligences Systems Intelligence is another higher level cognitive capacity SI links intelligence with the concept of system and systemic thinking SI embedds Social and Emotional intelligence (Goleman 1995, 2006) Systems Intelligence is a survival asset we have as a species

11 S ystems Analysis Laboratory Helsinki University of Technology 11 SI relates to Systems Thinking (Churchman 1968, Senge 1990,Checkland 1999,Jackson 2003) Organizational theories and Action research (Argylis, Schön, Schein,Bohm 1980, Isaacs 1999) Philosophy, Socratic tradition for thinking for good life Positive psychology (Bateson 2000, Goffman 1974, Seligman 2002) Theories of decision making and problem solving (Simon 1956, Keeney 1992, Kahneman, Tversky 2000)

12 S ystems Analysis Laboratory Helsinki University of Technology 12 Organizational learning The Fifth Discipline (Peter Senge 1990): Personal Mastery Mental Models Shared Vision Team Learning Systems Thinking Systems Intelligence is the link between Personal Mastery and Systems Thinking.

13 S ystems Analysis Laboratory Helsinki University of Technology 13 Systems Thinking Emphasizes the importance of wholes and perspectives Models systems of interaction from outside Can become a trap when one only sees the system from outside and does not recognize herself being an active player in the system

14 S ystems Analysis Laboratory Helsinki University of Technology 14 Characteristics of systems Whole is more than the sum of its parts “Whole” and “Part” are relative abstractions Always subject to redefinition by changing the perspective

15 S ystems Analysis Laboratory Helsinki University of Technology 15 How we see systems determines the model Beliefs about needs and goals Framing: costs or benefits Boundaries: fixed or flexible Alternatives: fixed or flexible Values: fixed or evolving and constructed in the context.

16 S ystems Analysis Laboratory Helsinki University of Technology 16 Systems can take over People can get caught in systems that serve nobody’s interests People can feel helpless regarding their possibilities of changing the system People react to the system without seeing their effect on the whole

17 S ystems Analysis Laboratory Helsinki University of Technology 17 Systems Intelligence Becomes a challenge for personal learning Trusts that people can influence complex systems The theoretical understanding of Systems Thinking need not increase Systems Intelligence

18 S ystems Analysis Laboratory Helsinki University of Technology 18 1.What does the system generate – and to what extent is this what we want? 2.How does the system mold us as human beings? 3.What kind of in-between does the system endorse? Ask first the System Questions

19 S ystems Analysis Laboratory Helsinki University of Technology 19 Change is not easy Mental change Perceptual change Individual behavioural change Change in the system

20 S ystems Analysis Laboratory Helsinki University of Technology 20 Thinking about thinking Key to learning Systems Intelligence One’s actions are a function of one’s thinking (mental models, beliefs, assumptions, interpretations, etc.) Challenge my mental models by meta-level thinking regarding my own thinking

21 S ystems Analysis Laboratory Helsinki University of Technology 21 Invisible system We often perceive systems only through a mechanistic perspective We see materials, products and costs When people are considered: – the true system often includes hidden subsystems – such as processes of trust or fear generation

22 S ystems Analysis Laboratory Helsinki University of Technology 22 Seeing oneself in the system With the eyes of the others The impact of my behaviour upon the behaviours of others The impact of the current system on all of us

23 S ystems Analysis Laboratory Helsinki University of Technology 23 Managing the invisible To understand the system, it can be more important to know what is not produced than what the standard output is SI tries to understand both the visible and the invisible part

24 S ystems Analysis Laboratory Helsinki University of Technology 24 Perceptual and behavioural change Seeing both the organizational/physical and the human parts SI looks for productive inputs to impact both parts

25 S ystems Analysis Laboratory Helsinki University of Technology 25 Change in the system People adjust to systems instinctively. If a system is changed, people also change their behaviours. This leads to further change A small change in my behaviour might trigger a chain of changes in the behaviours of others

26 S ystems Analysis Laboratory Helsinki University of Technology 26 In experimental games : People choose co-operative strategies with Systems Intelligence. They do not take everything for themselves. Evolution gave us SI

27 S ystems Analysis Laboratory Helsinki University of Technology 27 1.Seeing oneself in the System – Ability to see ones roles and behaviour in the system. Also through the eyes of other people and with different framings of the system. Systems thinking awareness. 2.Thinking about Systems Intelligence – Ability to envision and identify productive ways of behaviour for oneself in the system and understanding systemic possibilities. 3.Managing Systems Intelligence – Ability to personally work with systems intelligence. 4.Sustaining Systems Intelligence – Ability to continue and foster systems intelligence in the long run. 5.Leadership with Systems Intelligence – Ability to initiate and create systems intelligence culture in one’s organization. 5 step ladder of SI

28 S ystems Analysis Laboratory Helsinki University of Technology 28 So What? Is there a role for Systems Intelligence in LCM?

29 S ystems Analysis Laboratory Helsinki University of Technology 29 LCA is Systems Thinking Describes a product system and assesses the inventories and impacts. LCA is not enough The Systems Thinking trap lurks in LCA. Life Cycle Management takes LCA into action

30 S ystems Analysis Laboratory Helsinki University of Technology 30 Life Cycle Management (UNEP/SETAC LMC Definition Study 2003) Integration of life cycle perspective and economic, social, environmental considerations into overall strategy, planning and decision making of organization’s product portfolio System oriented platform Improvement and sustainability driver

31 S ystems Analysis Laboratory Helsinki University of Technology 31 The system questions What does a product system produce? - satisfaction of needs – what else? - environmental costs – is this what we want? How does the product system mold us? How does the product system influence our in - between? - does it endorse environmental responsibility and sustainability culture

32 S ystems Analysis Laboratory Helsinki University of Technology 32 Happiness as an indicator in LCA (Hofstetter, Madjau, Ozawa, 2006) Does the system produce happiness ? A weighted sum of happiness enhancers and rebound effects? set achievable important non-materialistic goals (weight = 2.5) become an outgoing personality (1.5) focus beyond self (1) ………. But - happiness is systemic

33 S ystems Analysis Laboratory Helsinki University of Technology 33 Systems can take over People can be caught in environmentally harmful systems that serve nobody’s interests People in the system can feel helpless regarding their possibilities of changing the system We live in consumption systems without seeing the cumulative overall effects

34 S ystems Analysis Laboratory Helsinki University of Technology 34 Social Life Cycle Management Impact categories are expanded Social evaluation of companies is not enough Expanding the product / service system boundary with a social perspective? –involve the stakeholders –re-evaluate needs

35 S ystems Analysis Laboratory Helsinki University of Technology 35 Stakeholder involvement with SI Invisible elements, emotions / trust are important in the process The way people are encountered can be more influential than the issue itself Dialogue not conflict resolution Beliefs about the expected beliefs and goals of others do matter

36 S ystems Analysis Laboratory Helsinki University of Technology 36 Redefinition question: What other possibilities are there to meet people’s needs? Goal and Scope in LCA

37 S ystems Analysis Laboratory Helsinki University of Technology 37 Consuming in Virtual Second Life

38 S ystems Analysis Laboratory Helsinki University of Technology 38 Can we see the drivers of our needs related to our consumption ? Maslow’s Hierarchy of Needs

39 S ystems Analysis Laboratory Helsinki University of Technology 39 Invisible systems What is not produced (happiness /sustainability) can be more important than the material output of the products system The process of achieving a social goal can matter more than the end product: -buying a bread or home baking the bread

40 S ystems Analysis Laboratory Helsinki University of Technology 40 My priorities in the satisfaction of needs over my own life Rethinking values can lead to revision of needs = a change in the system Where can I make value based trade-offs? Can I learn to manage consumption in a more sustainable way Change is not easy Personal Life Cycle Management

41 S ystems Analysis Laboratory Helsinki University of Technology 41 1.Seeing oneself in the Environmental System – Ability to see ones impacts on the environment. Environmental awareness. 2.Thinking about Environmental Systems Intelligence – Ability to envision changes in one’s consumption 3.Managing Environmental Systems Intelligence – Ability to personally change consumption patterns. 4.Sustaining Environmental Systems Intelligence – Ability to continue personal systems intelligent LCM in the long run. 5.Leadership with Environmental Systems Intelligence – Ability to initiate and create systems intelligent LCM culture in ones social network/ organinzation. 5 Levels of SI in personal LCM

42 S ystems Analysis Laboratory Helsinki University of Technology 42 Underlying philosophy in Life Cycle Thinking? Awareness of SI makes people want to have more of it It is systems intelligent for companies and people to use LCM Formula for Ecological Intelligence: EI = SI + LCM Systems Intelligence in LCM

43 S ystems Analysis Laboratory Helsinki University of Technology 43 Systems Intelligence Research Group Co-directors: Professors Raimo P. Hämäläinen and Esa Saarinen Downloadable articles and books on SI:

44 S ystems Analysis Laboratory Helsinki University of Technology 44 References Belton Valerie and Stewart Theodor J Multiple Criteria Analysis, An Integrated Approach. Massachusetts, Kluwer Churchman C. West The Systems Approach. New York, Delta French Simon, Maule John and Papamichail Nadia Decision Behaviour, Analysis and Support. Cambridge, University Press Gardner Howard Frames of Mind: The Theory of Multiple Intelligences, Tenth anniversary edition. New York, Basic Books Griesshammer Rainer et al Feasibility Study: Integration of Social Aspects into LCA, UNEP-SETAC Goleman Daniel Emotional Intelligence, New York, Bantam Books

45 S ystems Analysis Laboratory Helsinki University of Technology 45 References Goleman Daniel Social Intelligence, London, Hutchinson Goleman Daniel Ecological Intelligence, Bantam Hofstetter Patrick, Madjar Michael and Ozawa Toshisuke Happiness and Sustainable Consumption, Int J LCA 11, Special Issue 1, Ecomed Publishers Hämäläinen Raimo P. and Saarinen Esa (Eds.). 2004b. Systems Intelligence - Discovering a Hidden Competence in Human Action and Organizational Life, Helsinki University of Technology, Systems Analysis Laboratory Research Reports, A88, October 2004 Jackson Michael C Systems Approaches to Management, New York, Kluwer

46 S ystems Analysis Laboratory Helsinki University of Technology 46 References Keeney Ralph L Value-Focused Thinking: A Path to Creative Decisionmaking, Cambridge, Harvard University Press Miettinen Pauli and Hämäläinen Raimo P How to Benefit from Decision Analysis in Environmental Life Cycle Assessment (LCA), European Journal of Operational Research 102, Elsevier Miettinen Pauli and Hämäläinen Raimo P Indexes for Fixed and Feasible Environmental Target Setting: a Decision Analytical Perspective, International Journal of Environment and Pollution 12, Nos.2/3. Saur Kondrad et al LMC Definition Study, UNEP/SETAC Life Cycle Initiative Senge Peter The Fifth Discipline: The Art and Practice of the Learning Organization, New York, Doubleday Currency


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