Systems Thinking Analysis method

System Dynamics Simulation

Translates a dynamic hypothesis into stock-flow equations and tests scenarios.

A system dynamics simulation defines stocks, flows, auxiliaries, units, and initial values. Calibration, dimensional checks, and sensitivity analysis limit false precision.

Core question

What feedback and accumulation structure generates the behaviour, and how do scenarios respond?

Plan System Dynamics Simulation Method guide

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Participants: 1-5 Modellierende, Stakeholder asynchron
Time: Mehrere Tage bis Wochen

System Dynamics Simulation uses stock-flow model with dimensionally consistent equations, calibration, and sensitivity. Assessments remain justified and context-bound.

Paper illustration of System Dynamics Simulation with its method-specific working model.

Reference mode
Reference mode
Define problem behaviour and horizon as data curves.
Build stock-flow
Build stock-flow
Model stocks, flows, feedback, and delays with equations.
Validate model
Validate model
Test structure, extreme conditions, and historical fit.
Run scenarios
Run scenarios
Compare interventions and parameter sensitivity over time.

Maintain model version, parameter sources, and deviations between simulation and observation.

A good fit when

For accumulative problems with feedback and delay where decisions depend on behaviour over time.

Ideal for

Public policy
Climate and energy models
Business model stress testing

Not good for

Fast operational decisions

Outputs

validated stock-flow model
validated stock-flow model with traceable sources, assumptions, and domain decisions.
Decision and review trail
Owners, dates, and next review for validated stock-flow model.

validated stock-flow model

Fictional worked example

stock-flow model with dimensionally consistent equations, calibration, and sensitivity as a precise working structure with a fictional example.

Reference mode

Variable · unit · time series

Open tickets, daily, 26 weeks.

Stock and flows

Stock · inflow · outflow

Backlog; new/resolved tickets per day.

Equations

Formula · unit · source

Δt=1 day; Out=min(Stock/Δt, Agents×Productivity) [tickets/day]; State next=State+(In−Out)×Δt.

Validation and scenario

Tests · range · intervention

±20% sensitivity; reduce recurrence from W6.

The example demonstrates the domain logic of System Dynamics Simulation; worksheets remain blank.

MIT System Dynamics in Education Project: Road Maps

First step

Start with the core question: What feedback and accumulation structure generates the behaviour, and how do scenarios respond?

Open the method guide

Good to do first

Systems Thinking

Causal Loop Diagram

Supplies the causal hypothesis that is translated here into stock-flow equations.

Systems Thinking

Stock and Flow Diagram

Supplies the stocks and flows that are simulated in the model.

Where to go next?

Business Strategy

Scenario Planning

Uses the simulated scenarios as a quantitative basis for the strategy discussion.

Systems Thinking

Behavior Over Time Graph

Tracks how the open parameter uncertainties play out on behavior over time.

Deep dive

Purpose

System Dynamics Simulation makes assumptions about time, delay, and feedback testable through experiments. It draws relationships, patterns, and feedback loops. The result is captured as a simulation model and scenario reports.

How it works

First, stocks, flows, rules, and delays are formulated as a simulation model. The team then tests various scenarios and varies the assumptions until visible patterns emerge. The results help make robust decisions against seemingly simple but deceptive linearizations.

In detail

System Dynamics Simulation goes back to Jay Forrester and combines qualitative models such as Causal Loop Diagrams with quantitative stocks, flows, and auxiliary variables. Tools such as Vensim, Stella, or Simantics calculate scenarios over time and enable policy tests. It is often used in sustainability, public policy, and strategy consulting.

Facilitation

Start with the stock-and-flow diagram. Use sensitivity analysis instead of emphasizing single-point forecasts. Keep assumptions explicit.

The method guide walks execution through 4 phases, timing, 4 pitfalls, and clear stop criteria.

Open method guide

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Sources and topics

Topics

Systems thinking Dynamics Simulation Analysis

Sources

MIT System Dynamics in Education Project: Road Mapssystemdynamics.orgSystem Dynamics Society; Road Maps curriculum on stocks, flows, feedback loops, and model validation.

Artifact templates

System Dynamics Simulation: WorksheetPlan System Dynamics Simulation around its domain steps and the concrete decision question.

markdown

system-dynamics-simulation-working-template.md

Plan System Dynamics Simulation around its domain steps and the concrete decision question.

System Dynamics Simulation: Worksheet

Question

To be confirmed

Desired outcome

To be confirmed

Scope

Full initiative Time: Multiple sessions over 2–6 weeks

Complete this worksheet on paper or in your own document during the work.

Preparation for this scope

Method setup

Materials: Reference mode and time series, causal hypothesis, parameter sources and units, shared workspace, source links, and decision log.
Roles: Modeler · domain experts · data analyst · decision owner
Advance information: Collect Reference mode and time series, causal hypothesis, parameter sources and units in advance and mark open assumptions.
Overall time needed: Multiple sessions over 2–6 weeks
Setup: Prepare stock-flow model with dimensionally consistent equations, calibration, and sensitivity visibly and calibrate assessment terms before starting.

Prepare for the work steps

Reference mode: Reference mode

Reference mode and time series
causal hypothesis
parameter sources and units

Build stock-flow: Build stock-flow

reference mode
causal hypothesis
parameter sources and units

Validate model: Validate model

simulation model
causal hypothesis
parameter sources and units

Run scenarios: Run scenarios

validation record
causal hypothesis
parameter sources and units