System Dynamics Analysis

Within the content framework, understanding system behavior is fundamental in steering towards intended realization benefit that fits adaptation objective. This requires a number of Steps achieve intended benefit with respect to resolving problems, to elevate capability and potentiality, system potential and variety engineering. Intended intervention identity initiative applicable within context environment (governance) and define fundamental requirements relevant for Information Architecture realization/realignment.

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SYSTEM DYNAMICS STEPS:

  1. Problem Articulation (tell the story)

Theme selection: What is the intended purpose? What is the problem? Why is the purpose of this analysis? What is the issue the clients are most concerned with? What problem are they trying to address? What is the real problem, not just the symptom of difficulty?

  • Reconfirm system purpose: reconfirm what is the objective
  • What results are expected from the system
  • Compared to the goal: what are the actual results
  • This then clarifies differences between vision/expectation and current reality
  • Intended purpose theme selection of the system dynamics initiative: address specific problem, manage potential, elevate capability and potentially, variety engineering articulation
  • Define intended realization benefit: improve … or reduce …..
  • Illuminate diverse viewpoints of the multiple stakeholders
  • Create focusing statement; statement to channel energy during modelling process to achieve analysis expectations.
  1. Describe the systemic structure

Describe systemic structures that are creating dynamic behavior and its patterns. This is fundamental in understanding systemic feedback and dominant influence.

  • Define elements and define sub system in question
  • Define relevant variables and system element association
  • Model system structure and behavior (associated archetype) :
    1. Causal Loop diagrams
    2. Stock and flow diagrams and simulation
  • Identify behavior of key variables
  • Associate system archetypes.
  1. Behavior over time graphs

Map behaviour of critical system variables which are part of sub-system understudy in order to connect present to the past associating events to patterns of behaviour and emerging properties.

Time horizon: How far in the future should we consider? How far back in the past lie the roots of the problem?

Ensure that graphs have adequate historical data superimposed with critical events.

Clearly plot key variables that exhibit the following:

  • Oscillations

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  • S shaped growth

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  • Runaway growth
  • Flat line, no growth
  • Gradual decline
  1. Going deeper into the analysis

Based on above step system structure and behavior (archetypes) a theory is now possible to define systemic behavior and what is happening (positive and negative aspects). This then requires going deeper in the analysis:

  • Revisit purpose of the system (related to larger context) and verify if related subs system are coherent
  • Ask questions :
  • Behavior around the problem under-study:
  • Is the problem chronic
  • Does it have kwon pattern of behavior over time.
  • How does pattern relate to what is expected to actually occur
  • Historical occurrences of related problems and previous attempts to solve the problem and attempt (what was attempted, by whom, and what outcome) to associate Senge laws of system
  • What is likely to happen if problem in question is not solved ? What are the cost of not changing
  • How would stakeholders see the issue, how the think about the issues and what is important for them
  • How is the issue seen by higher management? What components and factors would they see?
  • What other causes are affecting this system? What other effects (unintended) does the system produce
  • Mental models
  • Explore the mental models by using the analysis causal loop models by adding ‘thought bubbles’ that document tendency and direction of information connection , resulting causality, emerging properties  and feedback loops (reinforcing and balancing) . This is fundamental in improving the quality of dynamic decisions.
  • Association to larger system
  • Add links and loops to connect to larger system in order to enrich the understating effort
  • Clarifying roles
  • Clarify roles, expectation and viewpoint of the different players from the environment and what role they played influencing the system performance
  1. Design solution

Design the solution that will structurally work and achieve intended realization objectives.  This implies modelling a ‘to-be’ SD scenario:

  • Causal loop diagram clearly showing feedback strength (balancing and feedback)
  • Identify if additional elements needed to the loops
  • Weaken the crisis loops
  • System dynamics model and simulations
  • The model must ensure consistency to what is intended, robustness by verifying behavior when stressed to its limits. Verify how the model behaves given uncertainty in parameters, initial conditions, model boundary, and aggregation?
  1. Systemic intervention

The intervention must clearly identify the following:

  • Policy design:
  • Scenario specification: What environmental conditions might arise?
  • Policy design: What new decision rules, strategies, and structures might be tried in the real world? How can they be represented in the model?
  • What are the effects of the policies?
  • How robust are the policy recommendations under different scenarios and given uncertainties?
  • Do the policies interact? Are there synergies or compensatory responses?
  • Leverage points and related key changes.
  • The intended intervention must be associated to systemic transformation initiative that need to be planned and realized (WHAT, WHO, HOW, WHEN, WHERE).
  • Clearly define intervention systemic benefit, associated risk and change management impact.
  • Identify monitoring criteria with respect to the intervention so as to measure and understand intended efficacy once realized (critical for systemic tower and continuous learning)