Systems Dynamics and Equilibrium Dr. Fred Mugambi Mwirigi JKUAT

What is a System? A group of interacting, interrelated, and interdependent elements forming a complex whole A configuration of parts connected and joined together by a web of relationships The whole is different from, and greater than, the sum of its parts

Parts of an Elephant One way to see this system – reduce it to its parts, when in reality the sum is more than and different from the sum of its parts – refers to a Hindustani tale in which people are blindfolded and asked to describe what they touch. All are right, but they misidentify the whole – an elephant

Systems Thinking A way of understanding reality that emphasizes the relationships among a system’s parts, rather than the parts themselves. Concerned about interrelationships among parts and their relationship to a functioning whole Sees underlying patterns and structures

Foundations of Systems Theory Cybernetics: system feedback, information; differences (that make a difference); human – machine analogy; inclusion of the observer and the observed in the system General systems theory: open systems; system integrity; nested system hierarchy, boundaries, webs, emergence (sum greater than parts) Recent theories developed starting in the 1920’s to describe the interrelatedness of organisms in ecosystems Cybernetics –early (Gregory Bateson, Norbert Weier, Warren McMulloch, Margaret Mead, Ross Ashby, Talcott Parsons General systems theory – Ludwig von Bertalanffy, Kenneth Boulding, Geoffry Vickers, Howard Odum and Fritjof Capra Late cybernetics – Heiz von Foerster, Stafford Beer, Humbarto Maturana, Niklas Luhmann, Paul Watzilawick

Systems Theories Soft and critical systems: human systems - multiple perspectives, power issues, intractable problems without simple solutions Systems dynamics: systems have reinforcing and balancing feedback loops, circularity, system archetypes, mental models, unintended consequences Soft and critical systems – C. West Churchman, Russell Ackoff, Peter Checkland, Werner Ulrich, Michael C. Jackson System Dynamics – Jay Forrester, Donnella Meadows, Peter Senge

More Systems Theories Complexity theory: complex adaptive systems; semi-independent, interacting agents; self-organization; emergence; nonlinearity; co-evolution; past is irreversible; future is unpredictable Learning systems: the way that people learn and the systems in which they learn Complexity theory – Ilya Prigogine, Stuart Kauffman, James Loveback, Ralph Stacey Learning Systems – Kurt Lewin, Eric Twist, Chris Argyris, Donald Schon, Mary Catherine Bateson

System Boundaries Shows what is inside and outside of the system Geographical (location) Organization (department, unit or function) Physical (money, material, information) Conceptual (goals, mission, purpose, rules) Intangibles (perceptions, awareness, models) Natural or man-made The change of a boundary can affect an entire system. We just experienced the 20th anniversary of a boundary shift that changed history – the fall of the Berlin Wall – it was part of a cascading set of changes from Perestroika to the break-up of the Soviet Union – that was one of the major paradigm shifts in the last century – the elimination of an “iron curtain”.

System Relationships (Interconnections) Connections and exchanges among system parts, parts and the whole, and the whole and its environment Flows of information Flows of funding Client referrals Collaborative partnerships Family, community, and social networks The creation of new relationships is an important tool of diplomacy for system change/paradigm shifts. Nixon’s visit to China to meet with Mao Zedong, Zhoe Enlai and others led to normalization of relations between the U.S. – Chinese.

System Perspectives Stakeholders’ worldviews and purposes System agents who have different perspectives may pursue different purposes within a given situation Patterns of (mis)alignment of purposes and processes within and across system levels

System Change System differences generate creative tension or energy within a system Positive or negative, energy provides potential for system change System change: shifts in patterns (similarities and differences) of system relationships, boundaries, focus, timing, events and behaviors over time and space

System Dynamics Random (unorganized) Organized (simple or complicated) Adaptive (organic, self-organizing) All three system dynamics can be present in a complex situation

Random System Attributes Random activity – no pattern Unconnected collection of parts No cause-effect relationships Turbulence – no stability or equilibrium Answers are unknowable No purpose or direction – people react blindly in a war zone or natural disaster

Random System: Hurricane Katrina

Organized (Simple) System Attributes Stable, static pattern Parts tightly connected machines Predictable cause-effect relationships System can be reduced to parts and processes and replicated Directive leadership, designed change Answers are knowable, with recipes or prescriptions for action

Single Organized System: Ring-Around the Rosie Simple system – parts are tightly connected, process is simple and straightforward – sing a verse and fall down

Simple Organized System: Riding a Bicycle Another simple system that includes a human with machinery.

Organized (Complicated) System Attributes Dynamic patterns of feedback loops with many interrelated parts within and across subsystem levels Recursive, non-linear cause-effect relationships; reinforcing and balancing feedback loops maintain equilibrium Expert analysis can identify causal loops, deep structural causes to actions

Adaptive (Complex) System Attributes Dynamical patterns – parts adapting, co-evolving with each other and environment Parts are massively entangled and interdependent; nested webs, networks Parts self-organize, learn, and change Equilibrium in flux, sensitive to initial conditions; system change emerges through interactions among parts

Ecological View of an Elephant When you can the boundaries of inquiry, you can see an elephant’s adaptation and co-evolution in its context – hot, dry, grassy, with dangerous predators and need for migration across large spaces for food and water

Complex Interdependencies

Alignment of Context, Program, and Evaluation Dynamics Context can be random, organized, adaptive, or combination of dynamics Program design uses random, organized (entity-based), or adaptive (paradigm-based) or a combination of dynamics Evaluation design (content and process) can be entity-focused (organized), paradigm-focused (adaptive) or a combination of both

Three Dynamics of a Social System and its Context

Initiative Renewal Design Match of Evaluation Designs to Dynamics of Social Systems and Their Context Exploratory Design Initiative Renewal Design Organic Design Predictive Design

Complex Adaptive Systems and Adaptive (Self-organizing) Dynamics Self-organizing/adaptive/organic Sensitivity to initial conditions Emergence Macro pattern

Complex Adaptive Systems and Adaptive (Self-organizing) Dynamics (cont Feedback Co-evolution Pattern formation and points of influence

Implications for Evaluation and Action Small differences can create large effects. The past influences but does not predict the future. Many points of influence exist. Boundaries, differences, and relationships are levers of influence toward a purpose.

Implications for Evaluation and Action Simple rules underlie patterns. Pattern-based feedback and actions are iterative. Tensions are not resolved. Patterns are outcomes.

Four Stages of Evaluation Design Evaluation Shape Practice Collect Data Make Meaning from Data

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