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1ZM65 System Dynamics Book Summary Systems Thinking and Modeling for a Complex World
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BUSINESS DYNAMICSSystems Thinking and Modeling for a Complex World
Book Summary
Ch1, 3, 4, 5.1-5.4, 6, 7.1, 8 , 9, 11, 13, 15, 17
,Contents
Part I Perspective and Processes ............................................................................................................ 7
1 Learning in and about Complex Systems ........................................................................................ 7
1.1 INTRODUCTION ....................................................................................................................... 7
1.1.1 Policy Resistance, the Law of Unintended Consequences, and the Counterintuitive
Behaviour of Social Systems ........................................................................................................... 7
1.1.2 Causes of Policy Resistance............................................................................................. 7
1.1.3 Feedback ......................................................................................................................... 8
1.1.4 Process Point: The Meaning of Feedback ....................................................................... 8
1.2 LEARNING Is A FEEDBACK PROCESS ........................................................................................ 8
1.3 BARRIERS TO LEARNING.......................................................................................................... 9
1.3.1 Dynamic Complexity ....................................................................................................... 9
1.3.2 Limited Information ........................................................................................................ 9
1.3.3 Confounding Variables and Ambiguity ........................................................................... 9
1.3.4 Bounded Rationality and the Misperceptions of Feedback ............................................ 9
1.3.5 Flawed Cognitive Maps ................................................................................................. 10
1.3.6 Erroneous Inferences about Dynamics ......................................................................... 10
1.3.7 Unscientific Reasoning: Judgmental Errors and Biases................................................. 10
1.3.8 Defensive Routines and Interpersonal Impediments to Learning ................................ 10
1.3.9 Implementation Failure ................................................................................................ 10
1.4 REQUIREMENTS FOR SUCCESSFUL LEARNING IN COMPLEX SYSTEMS ................................. 10
1.4.1 Improving the Learning Process: Virtues of Virtual Worlds .......................................... 10
1.4.2 Pitfalls of Virtual Worlds ............................................................................................... 11
1.4.3 Why Simulation Is Essential ......................................................................................... 11
3 The Modeling Process ................................................................................................................... 11
3.1 THE PURPOSE OF MODELING: MANAGERS AS ORGANIZATION DESIGNERS ........................ 11
3.2 THE CLIENT AND THE MODELER ........................................................................................... 12
3.3 STEPS OF THE MODELING PROCESS...................................................................................... 12
3.4 MODELING IS ITERATIVE ....................................................................................................... 12
3.5 OVERVIEW OF THE MODELING PROCESS ............................................................................. 13
3.5.1 Problem Articulation: The Importance of Purpose ....................................................... 13
3.5.2 Formulating a Dynamic Hypothesis .............................................................................. 13
3.5.3 Formulating a Simulation Model .................................................................................. 14
3.5.4 Testing ........................................................................................................................... 14
3.5.5 Policy Design and Evaluation ........................................................................................ 14
2
,4 Structure and Behavior of Dynamic Systems ................................................................................ 15
4.1 FUNDAMENTAL MODES OF DYNAMIC BEHAVIOR ................................................................ 15
4.1.1 Exponential growth ....................................................................................................... 15
4.1.2 Goal seeking .................................................................................................................. 15
4.1.3 Oscillation...................................................................................................................... 16
4.1.4 Process point ................................................................................................................. 16
4.2 INTERACTIONS OF THE FUNDAMENTAL MODES .................................................................. 16
4.2.1 S-shaped growth ........................................................................................................... 16
4.2.2 S-Shaped Growth with Overshoot ................................................................................ 17
4.2.3 Overshoot and Collapse ................................................................................................ 17
4.3 OTHER MODES OF BEHAVIOR ............................................................................................... 18
4.3.1 Stasis, or Equilibrium..................................................................................................... 18
4.3.2 Randomness .................................................................................................................. 18
4.3.3 Chaos ............................................................................................................................. 18
Part II Tools for systems Thinking ......................................................................................................... 19
5 Causal Loop Diagrams ................................................................................................................... 19
5.1 CAUSAL DIAGRAM NOTATION .............................................................................................. 19
5.2 GUIDELINES FOR CAUSAL LOOP DIAGRAMS ......................................................................... 20
5.2.1 Causation versus Correlation ........................................................................................ 20
5.2.2 Labeling Link Polarity .................................................................................................... 20
5.2.3 Determining Loop Polarity ............................................................................................ 20
5.2.4 Name Your Loops .......................................................................................................... 20
5.2.5 Indicate Important Delays in Causal Links .................................................................... 20
5.2.6 Variable Names ............................................................................................................. 20
5.2.7 Tips for Causal Loop Diagram Layout ............................................................................ 21
5.2.8 Choose the Right Level of Aggregation ......................................................................... 21
5.2.9 Don’t Put All the Loops into One Large Diagram .......................................................... 21
5.2.10 Make the Goals of Negative Loops Explicit ................................................................... 21
5.2.11 Distinguish between Actual and Perceived Conditions ................................................ 21
5.3 PROCESS POINT: DEVELOPING CAUSAL DIAGRAMS FROM INTERVIEW DATA ..................... 21
5.4 CONCEPTUALIZATION CASE STUDY: Managing YOUR WORKLOAD ...................................... 21
6 Stocks and Flows ........................................................................................................................... 22
6.1 STOCKS, FLOWS, AND ACCUMULATION ............................................................................... 22
6.1.1 Diagramming Notation for Stocks and Flows................................................................ 22
6.1.2 Mathematical Representation of Stocks and Flows...................................................... 22
6.1.3 The Contribution of Stocks to Dynamics ....................................................................... 23
3
, 6.2 IDENTIFYING STOCKS AND FLOWS ........................................................................................ 23
6.2.1 Units of Measure in Stock and Flow Networks ............................................................. 23
6.2.2 The Snapshot Test ......................................................................................................... 23
6.2.3 Conservation of Material in Stock and Flow Networks................................................. 23
6.2.4 State-Determined Systems ........................................................................................... 23
6.2.5 Auxiliary Variables ......................................................................................................... 23
6.2.6 Stocks Change Only Through Their Rates ..................................................................... 24
6.2.7 Continuous Time and Instantaneous Flows .................................................................. 24
6.2.8 Continuously Divisible versus Quantized Flows ............................................................ 24
6.2.9 Which Modeling Approach Should You Use? ............................................................... 24
6.2.10 Process Point: Portraying Stocks and Flows in Practice ................................................ 24
6.3 MAPPING STOCKS AND FLOWS............................................................................................. 24
6.3.1 When Should Causal Loop Diagrams Show Stock and Flow Structure? ....................... 24
6.3.2 Aggregation in Stock and Flow Mapping ...................................................................... 24
6.3.3 Guidelines for Aggregation ........................................................................................... 25
6.3.4 System Dynamics in Action: Modeling Large-Scale Construction Projects ................... 25
6.3.5 Setting the Model Boundary: “Challenging the Clouds” ............................................... 25
7 Dynamics of Stocks and Flows ...................................................................................................... 25
7.1 RELATIONSHIP BETWEEN STOCKS AND FLOWS .................................................................... 25
7.1.1 Static and Dynamic Equilibrium .................................................................................... 25
7.1.2 Calculus without Mathematics ..................................................................................... 26
7.1.3 Graphical Integration .................................................................................................... 26
7.1.4 Graphical Differentiation .............................................................................................. 26
8 Closing the Loop: Dynamics of Simple Structures ........................................................................ 26
8.1 FIRS-ORDER SYSTEMS ........................................................................................................... 26
8.2 POSITIVE FEEDBACK AND EXPONENTIAL GROWTH .............................................................. 27
8.2.1 8.2.1 Analytic Solution for the Linear First-Order System ............................................ 27
8.2.2 Graphical Solution of the Linear First-Order Positive Feedback System ...................... 27
8.2.3 The Power of Positive Feedback: Doubling Times ........................................................ 28
8.2.4 Misperceptions of Exponential Growth ........................................................................ 28
8.2.5 Process Point: Overcoming Overconfidence................................................................. 28
8.3 NEGATIVE FEEDBACK AND EXPONENTIAL DECAY ................................................................. 28
8.3.1 Time Constants and Half-Lives ...................................................................................... 29
8.4 MULTIPLE-LOOP SYSTEMS .................................................................................................... 30
8.5 NONLINEAR FIRST-ORDER SYSTEMS: S-SHAPED GROWTH ................................................... 30
8.5.1 Formal Definition of Loop Dominance .......................................................................... 30
4
, 8.5.2 First-Order Systems Cannot Oscillate ........................................................................... 31
Part III The Dynamics of Growth ........................................................................................................... 31
9 S- Shaped Growth: Epidemics, Innovation Diffusion, and the Growth of New Products ............. 31
9.1 MODELING S-SHAPED GROWTH ........................................................................................... 31
9.1.1 Logistic Growth ............................................................................................................. 31
9.1.2 Analytic Solution of the Logistic Equation .................................................................... 32
9.1.3 Other Common Growth Models ................................................................................... 32
9.1.4 Testing the Logistic Model ............................................................................................ 32
9.2 DYNAMICS OF DISEASE: MODELING EPIDEMICS .................................................................. 32
9.2.1 A Simple Model of Infectious Disease........................................................................... 32
9.2.2 Modeling Acute Infection: The SIR Model .................................................................... 33
9.2.3 Model Behavior: The Tipping Point............................................................................... 34
9.2.4 Immunization and the Eradication of Smallpox ............................................................ 35
9.2.5 Herd Immunity .............................................................................................................. 35
9.2.6 Moving Past the Tipping Point: Mad Cow Disease ....................................................... 35
9.3 INNOVATION DIFFUSION AS INFECTION: MODELING NEW IDEAS AND NEW PRODUCTS ... 36
9.3.2 Process Point: Historical Fit and Model Validity ........................................................... 36
9.3.3 The Bass Diffusion Model.............................................................................................. 37
9.3.4 Behavior of the Bass Model .......................................................................................... 37
9.3.5 Fad and Fashion: Modeling the Abandonment of an Innovation ................................. 37
9.3.6 Replacement Purchases ................................................................................................ 38
11 Delays ........................................................................................................................................ 39
11.1 DELAYS: AN INTRODUCTION ................................................................................................. 39
11.1.1 Defining Delays ............................................................................................................. 39
11.2 MATERIAL DELAYS: STRUCTURE AND BEHAVIOR ................................................................. 39
11.2.1 What Is the Average Length of the Delay? ................................................................... 39
11.2.2 What Is the Distribution of the Output around the Average Delay Time? ................... 39
11.2.3 Pipeline Delay................................................................................................................ 40
11.2.4 First-Order Material Delay ............................................................................................ 40
11.2.5 Higher-Order Material Delays ....................................................................................... 40
11.2.6 How Much Is in the Delay? Little’s Law ........................................................................ 41
11.3 INFORMATION DELAYS: STRUCTURE AND BEHAVIOR .......................................................... 42
11.3.1 and Exponential Smoothing and Exponential Smoothing............................................. 42
11.3.2 Higher-Order Information Delays ................................................................................. 42
13 Modeling Decision Making........................................................................................................ 43
13.1 PRINCIPLES FOR MODELING DECISION MAKING .................................................................. 43
5
, 13.1.1 Decisions and Decision Rules ........................................................................................ 43
13.1.2 Five Formulation Fundamentals ................................................................................... 43
13.2 FORMULATING RATE EQUATIONS ........................................................................................ 44
13.2.1 Fractional Increase Rate................................................................................................ 44
13.2.2 Fractional Decrease Rate .............................................................................................. 44
13.2.3 Adjustment to a Goal .................................................................................................... 44
13.2.4 The Stock Management Structure: Rate = Normal Rate + Adjustments ...................... 44
13.2.5 Flow = Resource * Productivity ..................................................................................... 44
13.2.6 Y = Y* * Effect of X, on Y * Effect of X2 on Y * * Effect of X, on Y ................................. 44
13.2.7 Y = Y* + Effect of XI on Y + Effect of X2 on Y + …+ Effect of Xn on Y ............................... 45
13.2.8 Fuzzy MIN Function ....................................................................................................... 45
13.2.9 Fuzzy MAX Function ...................................................................................................... 45
13.2.10 Floating Goals............................................................................................................ 46
13.2.11 Nonlinear Weighted Average .................................................................................... 46
13.2.12 Modeling Search: Hill-Climbing Optimization ........................................................... 47
15 Modeling Human Behavior: Bounded Rationality or Rational Expectations? .......................... 47
15.1 HUMAN DECISION MAKING: BOUNDED RATIONALITY OR RATIONAL EXPECTATIONS? ...... 47
15.2 COGNITIVE LIMITATIONS ...................................................................................................... 47
15.3 INDIVIDUAL AND ORGANIZATIONAL RESPONSES TO BOUNDED RATIONALITY ................... 48
15.3.1 Habit, Routines, and Rules of Thumb............................................................................ 48
15.3.2 Managing Attention ...................................................................................................... 48
15.3.3 Goal Formation and Satisficing ..................................................................................... 48
15.3.4 Problem Decomposition and Decentralized Decision Making ...................................... 48
15.4 INTENDED RATIONALITY ....................................................................................................... 48
15.4.1 Testing for Intended Rationality: Partial Model Tests .................................................. 48
17 Supply Chains and the Origin of Oscillations ............................................................................ 48
17.1 SUPPLY CHAINS IN BUSINESS AND BEYOND ......................................................................... 49
17.1.1 Oscillation, Amplification, and Phase Lag ..................................................................... 49
17.2 THE STOCK MANAGEMENT PROBLEM .................................................................................. 49
17.2.1 Managing a Stock: Structure ......................................................................................... 49
17.2.2 Steady State Error ......................................................................................................... 51
17.2.3 Managing a Stock: Behavior .......................................................................................... 51
17.3 THE STOCK MANAGEMENT STRUCTURE............................................................................... 51
17.4 THE ORIGIN OF OSCILLATIONS .............................................................................................. 52
6
,Part I Perspective and Processes
1 Learning in and about Complex Systems
1.1 INTRODUCTION
Changes arise as consequences intended and unintended of humanity itself.
Systems thinking The ability to see the world as a complex system, in which we understand that
you can’t just do one thing” and that “everything is connected to everything
else”.
System dynamics A method to enhance learning in complex systems. Fundamentally
interdisciplinary and grounded in the theory of nonlinear dynamics and
feedback control.
1.1.1 Policy Resistance, the Law of Unintended Consequences, and the
Counterintuitive Behaviour of Social Systems
Counterintuitive behaviour of social system:
- Our policies may create unanticipated side effects.
- Our attempts to stabilize the system may destabilize it.
- Our decisions may provoke reactions by others seeking to restore the balance we upset.
Policy resistance The tendency for interventions to be delayed, diluted, or defeated by the
response of the system to the intervention itself.
1.1.2 Causes of Policy Resistance
Causes of policy resistance:
- We Interpret experience as a series of events. Event-oriented worldview leads to an event-
oriented approach to problem-solving -> linear view
- We often do not understand the full range of feedbacks operating in the system -> feedback
view
7
,1.1.3 Feedback
Dynamics of a system are determined by:
- Feedback processes
- Stock and flow structures
- Time delays
- Nonlinearities
Most complex behaviors arise from the interactions (feedback) among the components of the system,
not from the complexity of the components. Two types of feedback loops:
- Positive/self-reinforcing loops: Reinforce or amplify whatever is happening in the system.
Processes that generate their own growth.
- Negative/self-correcting loops: counteract and oppose change. Processes that tend to be self-
limiting, seek balance and equilibrium.
1.1.4 Process Point: The Meaning of Feedback
The dynamics of all systems arise from the interactions of networks of feedbacks.
1.2 LEARNING Is A FEEDBACK PROCESS
Single loop learning Process whereby we learn to reach our current goals in the context of our
existing mental models nor our goals and values.
Mental models Our understanding of the causal structure of the system, the boundary we
draw around the system, the time horizon we consider relevant.
Double-loop learning Information feedback about the real world alters decisions within the context
of existing frames and decisions rules and feeds back to alter our mental
models: As our mental models change we change the structure of our
systems, creating different decision rules and new strategies.
Replacing a reductionist, narrow short-run static view of the world with a
holistic, broad, long-term dynamic view.
8
,1.3 BARRIERS TO LEARNING
Learning feedbacks fail in several ways:
- Dynamic complexity
- Imperfect information about the state of the real world
- Confounding and ambiguous variables
- Poor scientific reasoning skills
- Defensive routines
- Other barriers to effective group processes
- Implementation failure
- Misperceptions of feedback that hinder the ability to understand the structure and dynamics
of complex systems
1.3.1 Dynamic Complexity
Combinatorial complexity Number of components in a system or number of combinations one
must consider in making a decision.
Dynamic complexity arises because systems are:
- Dynamic
- Tightly coupled
- Governed by feedback
- Nonlinear
- History-dependent
- Self-organizing
- Adaptive
- Counterintuitive
- Policy resistant
- Characterized by trade-offs
1.3.2 Limited Information
We experience the real world trough filters. Changes in mental models are constrained by what we
previously chose to define, measure and attend to. Seeing is believing and believing is seeing.
1.3.3 Confounding Variables and Ambiguity
The information we receive is ambiguous because changes in the state of the system resulting from
our own decisions are confounded with simultaneous changes in a host of other variables. The number
of variables that might affect the system vastly overwhelms the data available to rule out alternative
theories and competing interpretations.
1.3.4 Bounded Rationality and the Misperceptions of Feedback
Bounded rationality We often systematically fall short, limiting our ability to learn from
experience.
Observe dysfunction in dynamically complex settings arises from misperceptions of feedback. Due to
two direct consequences of bounded rationality:
9
, 1. Our cognitive maps of the causal structure of systems are vastly simplified compare to the
complexity of the systems themselves.
2. We are unable to infer correctly the dynamics of all but the simplest causal maps.
1.3.5 Flawed Cognitive Maps
Cues to causality which lead to difficulty in complex systems where cause and effect are often distend
in time and space, where actions have multiple effects, and where the delayed and distant
consequence are different from and less salient than proximate effects.:
- Temporal and spatial proximity of cause and effect
- Temporal precedence of causes
- Covariation
- The similarity of cause and effect
A fundamental principle of system dynamics: The structure of a system gives rise to its behaviour.
Fundamental attribution error The tendency to blame the person rather than the system.
1.3.6 Erroneous Inferences about Dynamics
Dysfunction in complex systems can arise from:
- The misperception of the feedback structure of the environment.
- Faulty mental simulation: the misperception of feedback dynamics.
1.3.7 Unscientific Reasoning: Judgmental Errors and Biases
Insight skills The skills that help people to learn when feedback is ambiguous.
Central principle of system dynamics: examine issues from multiple perspectives to expand the
boundaries of our mental models to consider the long-term consequences and “side effects” of our
actions, including their environmental, cultural, and moral implications.
1.3.8 Defensive Routines and Interpersonal Impediments to Learning
Defensive routines and cultural assumptions people rely on, interact with and interpret their
experience of others. Defensive routines often yield group think and ensure that mental models of
team members remain ill formed, ambiguous and hidden.
1.3.9 Implementation Failure
The need to maintain performance often overrides the need to learn by suppressing new strategies
for fear they would cause present harm even though they might yield insight and prevent future harm.
1.4 REQUIREMENTS FOR SUCCESSFUL LEARNING IN COMPLEX SYSTEMS
Every link in the feedback loops by which we might learn can be weakened or cut by a variety of
structures.
1.4.1 Improving the Learning Process: Virtues of Virtual Worlds
Virtual worlds Formal models, simulations, or “microworlds” in which decision makers can refresh
decision-making skills, conduct experiments and play. Several virtues:
10
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