Systems Thinking

  • Much of the art of system dynamics modeling is discovering and representing the feedback processes which along with stocks and flows structures, time delays and nonlinearities, determine the dynamics of the system.
  • The fundamental principle of system dynamics states that the structure of the system gives rise to its behaviour,the lack of this leads to the fundamental attribution error.
  • Dynamics: This is the subject that deals with change, with systems that evolve in time, whether the system settles in equilibrium, keeps repeating in cycles or does something more complicated.
  • Data-driven discovery on systems that typically nonlinear, dynamic, multi-scale in space and time and high-dimensional with dominant underlying patterns that should be characterized and modeled for the eventual gola of sensing, prediction, estimation and control.
  • Many complex systems exhibit dominant low-dimensional patterns in the data, despite rapidly increasing resolution of measurements and computations, this underlying structure enables efficient sensing and compact representations for modeling and control.
  • Information about existence of a problem may be necessary but not sufficient to trigger action, information about resources, incentives and consequences is necessary too.
  • Pattern extraction can be defined as finding coordinate transforms that simplify the system.

Need for system dynamics simulation model

  • Increase our understanding of the problem.
  • Improve existing systems.
  • Improve behaviours
  • Reduce complexity.
  • Avoid black-box decision making.
  • Get qualified answers - Reduce cost - Save time.

Preparation for system dynamics simulation

  • Problem definition: Formulating a problem from a dynamic perspective.
  • Key variables: Recognising central factors and key variables.
  • Behaviour over time: Recognising and estimating the behaviour of key variables over time.
  • Feedback diagrams: Identifying cause and effect, drawing feedback diagrams.

Process of system dynamics simulation

  • Stock and flow diagrams: Identification of stocks ad flows in the system.

  • Model equations: Integrations for stocks and Policies for flows.

  • Simulation: Generate model behaviour over time.(5-6 tests)

  • Analysis and Implementation: Compare real and simulated behaviour, test structure, identify and test policy alternatives, implement changes in the real system.

  • Look into Powersim Studio 10.

Information-based relationships

  • A system's function or purpose is not necessarily spoken, written or expressed explicitly except through operation of the system. Purposes are deduced from behaviour not rhetoric or stated goals and every system ultimately ensures its own perpetuation.
  • For systems within systems keeping sub-purposes and overall system purposes in harmony is an essential function of successful systems as change in purpose changes the system profoundly.
  • There is a limit to the rate at which any leader can turn the direction of a nation due to physical constraints of elements.
  • A stock, elements of the system that you can see, feel, count and measure at any given time, is the foundation of any system. A stock is the memory of the history of changing flows within the system, stocks change over time via actions of a flow.
  • Understand the dynamics of stocks and flows, their behaviour over time you understand a good deal about behaviour of complex systems.
  • Human mind seems to focus more easily on stocks than on flows, inflows more than outflows, inflows vs outflow strategies may have different costs.
  • Rehabilitation of existing structures vs building new ones.
  • A stock takes time to change because flows take time to flow, changes in stocks set the pacce of dynamics of systems. If you have a sense of the rates of change of stocks, you don't expect things to happen faster that they can happen.
  • Presence of stocks allows inflows and outflows to be decouled, stock maintaining mechanisms allow inflows and outflows independent and stalls.
  • System thinkers see the world as a collection of stocks along with the mechanism for regulating levels in stocks by manipulating flows. If you see behaviour persisting over time, there is likely a mechanism creating that consistent behaviour which operates via a feedback loop.
  • Feedback loop is formed when changes in a stock affect the flows into or out of that same stock.
  • Balancing feedback loop; equilibrating or goal-seeking structures.
  • Runaway loops; reinforcing feedback, system element has the ability to reproduce itself at a constant fraction of itself.
  • Competing balancing loops.
  • Information delivered by a feedback loop can only affect future behaviour, your mental model of any system needs to include all the information flows or you will be surprised by the systems' behaviour.
  • Dominance of feedback loops.
  • System analysis can test a number of scenarios to see what happens if the driving factors do different things. Dynamic systems studies designed to explore 'what would happen' not predict if some factors unfold in a rage of different ways.
  • How is good is the model, capture inherent system dynamics, what drives the driving factors.
  • Delays are pervasive in systems and are string determinants of behaviour
  • Resilience
  • Self-organisation
  • Hierarchy
  • Loss of resilience, enhance a systems own restorative power.
  • Complex systems can evolve from simple systems only if there are stable intermediate forms.
  • Hierarchies reduce information that any part of systems has to keep track of.
  • Take your eyes off short-term events and look for long-term behaviour and structure.
  • Events are the most visible aspect of larger complex but not always the most important.
  • Put events into historical context, look for data, time, graphs, history of the system.
  • Behaviour based models ve event-based ones.
  • Law of the minimum, what is the limiting factor?
  • Bounded rationality.