Systems Thinking and Complexity Management Training Course

Participants can expose assumptions, competing perspectives and boundary choices affecting a systems diagnosis.

• Argyris ladder of inference exposes assumptions behind managerial conclusions
• Double-loop learning tests governing variables, not only corrective actions
• Polarities mapped using both poles, benefits, fears and early warnings
• Stakeholder salience assessed through power, legitimacy and urgency criteria
• Boundary critique identifies included voices, excluded interests and value judgements
• Competing mental models compared before choosing intervention hypotheses

Participants can create and validate causal loop diagrams that explain feedback-driven behaviour.

• Variables written as measurable nouns that can increase or decrease
• Positive and negative causal links labelled with polarity notation
• Reinforcing and balancing feedback loops identified from operational evidence
• Link delays marked to expose deferred consequences and oscillation risks
• Loop narratives test whether diagrams reflect observed system behaviour
• Causal loop diagrams revised after stakeholder challenge and data review

Participants can distinguish accumulations from rates and explain changing system performance over time.

• Stocks, flows and clouds distinguish accumulations from rates of change
• Conservation principles test whether stock-and-flow structures are physically plausible
• Bathtub dynamics explain backlog, liquidity, inventory and workforce patterns
• Decision rules represented as equations, thresholds and information delays
• Behaviour-over-time graphs compare reference modes against simulated trajectories
• Dimensional consistency checks expose invalid units and implausible relationships

Participants can diagnose recurring problem structures and identify deeper corrective actions.

• Fixes That Fail traces symptomatic relief and delayed unintended consequences
• Shifting the Burden separates dependency mechanisms from fundamental solutions
• Limits to Growth identifies reinforcing expansion and constraining feedback
• Success to the Successful reveals allocation rules creating structural advantage
• Tragedy of the Commons tests shared-resource depletion and replenishment rules
• Archetype diagnosis distinguishes recurring structure from isolated operational incidents

Participants can select suitable management responses for ordered, complex and chaotic conditions.

• Cynefin distinguishes clear, complicated, complex, chaotic and confused contexts
• Probe-sense-respond practices guide action where cause and effect emerge retrospectively
• Safe-to-fail experiments specify hypotheses, boundaries, signals and stop conditions
• Complex adaptive systems examined through agents, rules, networks and adaptation
• Attractors, path dependence and tipping points inform intervention timing
• Ordered-domain methods reserved for repeatable work with knowable relationships

Participants can assess whether organisational structures have the functions required to manage complexity.

• Viable System Model diagnoses operational, coordination, control, intelligence and policy functions
• System 1 through System 5 roles tested against accountability gaps
• Algedonic signals escalate critical exceptions without overloading senior decision-makers
• Variety engineering matches response capacity to environmental complexity
• Autonomy boundaries clarify local discretion, escalation triggers and shared constraints
• Recursive structures connect frontline units, business divisions and enterprise governance

Participants can select interventions that address system structure, decision rules and learning needs.

• Meadows' twelve points distinguish parameters, feedbacks, rules, goals and paradigms
• Assumption mapping separates certainties, critical uncertainties and testable beliefs
• Impact-effort matrix prioritises interventions within authority and resource constraints
• Pre-mortem analysis identifies failure pathways before committing implementation resources
• Implementation hypotheses link actions to mechanisms, measures and expected effects
• Ethical review tests distributional consequences, consent and unintended harm

Participants can prepare strategies for plausible future conditions and define decision triggers.

• Critical uncertainties frame plausible futures rather than single-point forecasts
• Two-by-two scenario matrices combine independent, high-impact uncertainty axes
• Wind-tunnelling tests strategies against each scenario's operating conditions
• Leading indicators distinguish weak signals from routine performance variation
• Signposts trigger contingency actions, reassessment dates and governance decisions
• Adaptive portfolios balance committed action, options and reversible decisions

Participants can assemble a practical systemic intervention plan for a current organisational challenge.

• Systemic problem statement defines outcomes, boundaries, evidence and affected parties
• Causal loop diagram and behaviour-over-time graph support a shared diagnosis
• Intervention portfolio specifies owners, mechanisms, dependencies, measures and review cadence
• Learning agenda records assumptions, experiments, indicators and decision thresholds
• After-action reviews capture results, surprises, adaptations and next-cycle commitments
• Thirty-day application plan schedules stakeholder conversations and first tests