```Introduction System Dynamics
Un instrument
for System
Thinking
Learning Objectives

After this class the students should be able
to:



recognize their cognitive capacity limitation to
deal is dynamic systems;
understand the mean concepts of System
Dynamics, such as feedback loop, delays;
and archetype of systems; and
interpret System Dynamics diagrams
Time management

The expected time to deliver
this module is 50 minutes. 20
minutes are reserved for team
practices and exercises and 30
minutes for lecture
An experiment

Suppose a simple supply chain that has been in
steady-state for some time. The Retailer’s inventory
has been constant at some level for a long time,





A retailer maintains an inventory of product that is shipped
to customers on demand.
Upon shipping, the retailer always orders immediately from
his supplier the same amount of product just shipped.
The supplier also is very regular. He always deliveries the
product to retailer 7 days after the he places the order.
The supplier has never been out-of-stock (and never will
be!).
No product shipped by the supplier is ever, or will ever be,
defective, damaged or lost in transit.
Demand changes

Suppose, all of a sudden, the volume of
demand from customer coming into the
retailer steps up to a new higher level,
and then remains there.
Sketch the new behavior

On the axes provided in Figure I, sketch the
pattern you think will be traced by the level of the
retailer's inventory, over time, following the
one- step-increase to customer demand. ( Each
team has 5 minute to give a answer. )
Figure 1
The retailer's inventory behavior

following the step-increase in demand, the Retailer's
inventory will decline in a straight-line manner for 7 days; it
then will level off and remain at the new, lower level.
Cognitive Capacity limitation

“In the long history of evolution it has not been
necessary until very recent historical times for
people to understand complex feedback
systems. Evolutionary processes have not given
us the mental ability to interpret properly the
dynamic behavior of those complex systems in
which we are now imbedded.” Forrester, 1973
System Dynamics


In particular, to analyze how the
interaction between structures of the
systems and their policies determine
the system behavior
Methodology
behavior
to
study
systems
Filling a cup of water

Each team is invited to describe
through any kind of diagram (or
algorithm) the process to fill a cup of
water. Imagine this as an exercise of
operation management. (10 minutes)
Language: causal diagram
Faucet
Position
Desired
Water
Level
Perceived
Gap
Water
Flow
Current
Water
Level
Feedback loop and Delay



When we fill a glass of water we operate
"water-regulation" system involving five variables:

our desired water level, the glass's current water level;

the gap between the two;

the faucet position; and

and the water flow.
in
a
These variables are organized in a circle or loop of
cause-effect relationships which is called a "feedback
process.“
Delays are Interruptions
consequences
between
actions
and
their
Feedback loop with delay
Faucet
Position
Desired
Water
Level
Perceived
Gap
Water
Flow
Current
Water
Level
The means of arrows
Desired
Water
Level
Faucet
Position
Perceived
Gap
Water
Flow
Current
Water
Level
Negative feedback
+
Desired
Inventory
Level
+
Perceived
Gap
-
Order
Placed
Current
Inventory
Level

+
Supply
Line
+
Balancing Process for Adjusting Cash Balance
to Cash Surplus or Shortage
Positive feedback
Positive
Word
Mouth

+
Satisfied
Customers
Reinforcing Sales Process Caused by Customers
Archetypes of systems





Certain patterns of structure recur again and again. These generic
structures are named "systems archetypes".
Archetype systems are a set of reinforcing and balancing feedback
and delays interconnected.
A relatively small number of these archetypes are common to a very
large variety of management situations.
Approach developed to study system behaviors taking into account
complex structures of feedbacks and time delays.
The industrial environment, seen as a set of stocks and activities
linked by flow of information and flow of material submitted to time
delays, is a typical object for System Dynamics study.
Creating our own Market Limitation

People Express example

People Express example

Reference



Peter Senge,
The Fifth Discipline, 1990
Chapter 5
Complex Systems
Sterman (1994)
Real World
Unknown structure
Dynamic complexity
Time Delays
Impossible experiments
Virtual World
Implementation
Game playing Decisions
Inconsistency
Short term
Known structure
Variable Complexity
Controlled Experiments
Selected
Missing
Information Delayed
Feedback
Biased
Ambiguous
Strategy, Structure, Inability to infer
dynamics from
Decision Rules
mental models
Misperceptions
Mental Unscientific
Biases
Models
Defensiveness
Dynamic Complexity arises
because systems are…




Changing over
time
Tightly coupled
Governed by
feedback
Nonlinear:
changing
dominant
structure





Self-organizing
Counterintuitive
Policy resistant
Characterized by
System Dynamics
Contributions

Thinking dynamically


Move from events and
decisions to patterns of
continuous behavior over
time and policy structure
Thinking in circular
causal / feedback
patterns




Self-reinforcing and selfbalancing processes
Compensating feedback
structures and policy
resistance
Communicating complex
Thinking in stocks
and flows



Accumulations are the
resources and the
pressures on policy
Policies influence flows
Modeling and
simulation


Accumulating (and
remembering) complexity
Rigorous (daunting)
model evaluation
processes
The system dynamics
modeling process
Perceptions of
System Structure
Comparison and
Reconcilation
Representation of
Model Structure
System
Conceptualization
Model
Formulation
Empirical and
Inferred Time
Series
Comparison and
Reconciliation.
Deduction Of
Model Behavior
Processes focusing on system
structure
Mental Models,
Experience,
Literature
Perceptions of
System Structure
Comparison and
Reconcilation
Representation of
Model Structure
Diagramming and
Description Tools
Empirical
Evidence
System
Conceptualization
Model
Formulation
Processes focusing on system
behavior
Empirical
Evidence
System
Conceptualization
Model
Formulation
Literature,
Experience
Empirical and
Inferred Time
Series
Comparison and
Reconciliation.
Deduction Of
Model Behavior
Computing
Aids
Two kinds of validating
processes
Mental Models,
Experience,
Literature
Empirical
Evidence
Perceptions of
System Structure
System
Conceptualization
Comparison and
Structure
Reconcilation Validating
Processes
Representation of
Model Structure
Diagramming and
Description Tools
Model
Formulation
Literature,
Experience
Empirical and
Inferred Time
Series
Behavior
Validating
Processes
Comparison and
Reconciliation.
Deduction Of
Model Behavior
Computing
Aids
Contributing to the
Evolution of
Feedback Thought
•Biology: math models
•Econometrics
•Engineering
•Social Sciences
•Biology: homeostasis
•Logic
Feedback Thought
•System dynamics arises in
(the first four in this list)
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Forrester’s Hierarchy of
System Structure




Closed boundary around the system
Feedback loops as the basic structural
elements within the boundary
Level [stock] variables representing
accumulations within the feedback loops
Rate [flow] variables representing activity
within the feedback loops




Goal
Observed condition
Detection of discrepancy
Action based on discrepancy
The Endogenous Point of View



The closed causal boundary takes top
billing
Dynamics arise from interactions
within that boundary
Systems thinking is the mental
effort to uncover endogenous
sources of system behavior.
Dynamics
New York City Population,
1900-2000
Bronx
Brooklyn
Manhattan
Queens
Staten Island
9000000
8000000
7000000
6000000
5000000
4000000
3000000
2000000
1000000
0
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
Global Atmospheric Methane
(1860-1994)
Global Atmospheric Methane
400
350
300
250
200
150
100
50
1860
0
Global Average Temperature
(Reconstruction 1400-1980; Data 19021998)
Quic kTime™ and a
TIFF ( LZW) dec ompres s or
are needed to s ee this pic ture.
Stocks and Flows
Stocks and flows help to explain
self-reported drug use data
Have
ever
used
Potential
users
Frequent
users
Occasional
users
Past users
The Simplified Structure--p.
133
Reputation
Fleet size & flights
R
No. of pass. carried
B
Revenues
Service quality
Delay
Service quality stan
Service capacity
B
P erceived need to improve quality
Delay2
Structure
growing action
Reinforcing
state of stock
slowing action
Balancing
The Simplified Structure-variables
NAME
Actual Inventory
Desired Inventory
Order Rate

MNEMONIC
AI
DI
OR
AT
Desired invent o ry
Invent ory
Order rat e
Adjust m ent t im e
dEMAN D
The Simulation Structure-Reinforcing Loop
L ifet im e
Deprec
Flight s/yr
Flight s/\$-y r
Fleet capit al
Addns t o f leet capit al
R
No. of pass carried/y r
Rev. t o fleet fract
Revenues/yr
Avg. Revenue/pass
‘Challenging the clouds’ in a
study of leasing in the automobile
industry
?
New vehicle
inventory
Production
Purchase
or lease
“We’re not in the used car business!”
Stocks and flows in new car
purchase and leasing
Relative
attractiveness
of leased cars
Used
inventory
Purchase
used
Vehicles
being driven
New vehicle
inventory
Production
Sell or
Purchase
or lease
Scrapping
Intuitive view of effect of leasing
on auto sales:
Leased car pipeline
Stocks and Flows in Global
Warming
Thought
experiment:
Capital
stock
capital
investment
CO2 annual
production
Atmospheric
CO2
Breakdown of
atmopheric CO2
Economic
activity
incoming solar
heat energy
Global heat
energy
outgoing global
heat energy
Life of aerosols in atm
Life of GH gases in atm
Aer osols i n atm
Aer osol br eakdown
Aer osol pr oduction
But although the
stock-and-flow
insight holds, global
climate is of course
much more complex
than that.
GH g ases in atm
GH g as pr oducti on
GH g as br eakdown
Aer osol al bedo efct
Aer osol concentr ati on
Atm volume
Atm volume
~
GH g as concentr ation
~
Ice and cloud cover
Total albedo
~
Ear th Ocean and Atm heat
Cloud cover
GH g as reten efct
Ear th ar ea
Solar heat reachi ng ear th
Ear th heat radi ati on
Ear th ar ea
~
Ice cover
Cloud reten efct
Ice thi ckness
~
Solar heat incoming
Water vap reten efct
Sur face temp
Ice ar ea
Cloud thickness
Cloud ar ea
CO2 r eten efct
Atm temp
~
Ice density
Atm volume
Net thawing factor
Evap factor
Ice volume
Ear th ice
Ear th water
Net thawing
And still much more
complex than this
simple global climate
model, as well!
Cloud volume
Water vap conc
Water vapor in atm
Cloud density
Water in clouds
Evaporation
Condensation
Water density
Precipitati on
Ear th water vol ume
Atm volume
CO2 atm conc
CO2 water conc
Ear th photosynthesi s
Ocean photosynthesis
CO2 i n atm
CO2 i n oceans
Car bon in ocean biomass
Ocean CO2 br eakdown
CO2 ocean r el ease
Atm CO2 breakdown
Car bon in earth biomass
Ear th biomass decay
Ocean biomass decay
Ocean CO2 pr oduction
CO2 ocean uptake
Atm CO2 production
Feedback Thinking
“For one good deed leads to
another good deed, and one
transgression.” (Pirke Avot)
The Classic Cybernetic
Balancing Loop
Goal
Perceived
gap
Perceived
state
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Actual state of
the system
Changes in
the State of
the system
Intended
actions
The Cybernetic Loop with
Complications
Goal
Perceived
gap
Perceived
state
Autonomous
changes in the state
of the system
Actual state of
the system
Changes in
the State of
the system
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Intended
actions
The Cybernetic Loop with
Complications
Goal
Perceived
gap
Perceived
state
Autonomous
changes in the state
of the system
Actual state of
the system
Changes in
the State of
the system
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Intended
actions
Unintended
actions
The Cybernetic Loop with
Complications
Goal
Perceived
gap
Perceived
state
Autonomous
changes in the state
of the system
Actual state of
the system
Changes in
the State of
the system
Planned
action to
reduce gap
Implicit,
unstated goals
Implemente d
action
Intended
actions
Unintended
actions
Ramifying
effects
A Classic Reinforcing Loop
(Myrdal 1944, Merton 1948)
Prejudice against the
minority group
Majority’s perception
of the inferiority of
the minority
(R)
Economic and educational
discrimination against the
minority
Achievements of the
minority group
Structure and Dynamics of
Terrorist Cells
(R)
Peripheral
support for
terrorists
Terrorist
funding
(R)
Interfering with
terrorist funding
Terrorist
actions
Efforts to
suppress
terrorists
(B)
(R)
Terrorist
zeal
(B)
Recruiting
(R)
terrorists
(R)
Terrorist
group
Terrorist martyrs to
the cause
(B)
(B)
Losing
terrorists
(R)
Insights about building teamwork in a public school
Teamwork and Communication are self-reinforcing
Quality of
communication
+
Trust
+
(+)
Risk
taking
+
Quality of
communication
within teams
+
Teamwork
+ Resistance to
teamwork
Isolation of teams and punishing risk-taking inhibit the growth of trust
+
Quality of
communication
+
+
Positive
responses to
experiments
?
Trust
+
(+/-)
Individual
experiments
(+)
Risk
taking
Quality of
communication
between teams
+
(-)
Quality of
communication
within teams
+
Teamwork
+ -
+
Resistance to
teamwork
But longterm experience with teamwork can build communication
Quality of
+
communication +
between teams
+
Quality of
(-)
communication
Quality of
+
(+)
communication +
+
within teams
Trust
(+)
+
Cumulative
Positive
+
Risk
experience with
responses to
Teamwork
taking
teamwork
(+/-)
experiments
+ +
?
+
Individual
Resistance to
+
+
experiments
Team
teamwork
effectiveness
-
Risk taking can enhance effectiveness, which can build trust
Quality of
+
communication +
between teams
+
Quality of
(-)
communication
Quality of
+
(+)
communication +
+
within teams
Trust
(+)
+
Cumulative
Positive
+
Risk
experience with
responses to
Teamwork
taking
teamwork
(+/-)
experiments
+ +
?
+
Individual
Resistance to
+
+
experiments
Team
teamwork
effectiveness
+
+
Personal learning
Average personal
effectiveness
+
A team-player culture is self-reinforcing: an opportunity or a trap
Quality of
+
communication +
between teams
+
Quality of
(-)
communication
Attractiveness
Quality of
+
(+)
of the org to
communication +
+
within teams
+ team players
Trust
(+)
+
Cumulative
Positive
+
Risk
experience with
responses to
Teamwork
+
taking
teamwork
(+/-)
experiments
+ Fraction of
staff
who are
+
?
team players
+
Individual
Resistance to
+
+
experiments
Team
teamwork
+
effectiveness
+
+
Personal learning
Average personal
effectiveness
+
Likely leverage points
+
Extent of
Learning
Organization
characteristics
present
Quality of
communication
+
+
Trust
(+)
+
+
Positive
responses to
experiments
?
+
(+/-)
Teamwork
+ -
+
Resistance to
teamwork
+
Team
effectiveness
-
+
Personal learning
+
Dialogue
training
Attractiveness
of the org to
+ team players
Cumulative
experience with
teamwork
+
Individual
experiments
teaching
role
Risk
taking
+
Quality of
communication +
+ between teams
+
(-)
Quality of
(+)
communication +
within teams
+
Average personal
effectiveness
+
+
+
Fraction of
staff who are
team players
+
+
Understanding
stages of
community
building
The Problem: 1996 U.S.
welfare reform


Since 1930, a guarantee of lifetime Federal
support
1996 legislation ended that:






Temporary Assistance for Needy Families - TANF
At most five years of Federal support in one’s
The clock started for everyone on TANF in
1997
People began timing out in 2002
Financial burden will begin shifting to the
states and counties
A series of facilitated group modeling efforts
in three New York State counties tried to help

Three
Policy
Mixes
Base run (for comparison)



Investments in the “Middle”




Flat unemployment rate
Historical client behaviors
Increased TANF assessment & monitoring
Safety net assessment & job services
Investments on the “Edges”



Prevention
Child support enforcement
Self-sufficiency promotion
Investing in the “Middle”
Investing on the “Edges”
Base, “Edges,” and “Middle”
Compared:
Populations on the Welfare Rolls
“Edges” looks better.
Total Job-Finding Flows from
TANF
“Middle” looks better.
Program Expenditures
“Edges” looks worse, then better.
Populations in the Welfare
System
“Middle” looks worse than “Base”! “Edges” looks much better.
Total Recidivism Flows
(back to TANF)
The hint for understanding the puzzling dynamics: recidivism.
A Stock-and-Flow Archetype
at Work Here
+
(R)
Probability of
recidivism
Recidivism
Families on
TANF
Enter TANF
Job finding
rate
Post TANF
employed
To mainstream
employment
(R)
support capacity
(R)
Time to find
first job
support capacity
+
Behavior of the Archetype in response
to increased TANF support capacity
6,000
Total families at risk
4,500
Families on TANF
3,000
1,500
Post-TANF employed
0
0
6
12
18
Fam ilies on T ANF : archet ype base
P ost T ANF employed : archet ype base
T otal families at risk : archet ype base
24
30
36
T im e (M ont h)
42
48
54
60
families
families
families
The Behavior of the Archetype



Families on TANF initially declines, as
more support hastens job finding.
Post-TANF families employed initially
increases, just as policy makers would
predict.
Eventually (it takes a year and a half to
begin to see it), …



Families on TANF rises higher to a new high,
Post-TANF Employed declines to a new low,
And Total Families at Risk rises!
Why?
• Increasing TANF support
• Speeds job finding,
• Swamping downstream
Post-TANF jobs and support
Time in post
TANF employ
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism




Desirable rise in Post-TANF employed
continues for almost a year and half after the
intervention
Families on TANF falls below initial for over a
year after increasing TANF support capacity
Very hard (impossible?) to see that the rise in
Total Families at Risk is attributable solely to
the improvement in TANF support capacity
Dynamics almost certainly to be blamed on a
weakening economy, a rise in client
pathologies, or other exogenous factors
A Loop View of the Archetype in Detail
Time in post
TANF employ
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Suppose TANF support capacity increases…
Probability of
recidivism
4,000
White bar (left) is the
time slice of interest
3,000
controls recidivism
2,000
Red arrows (below) are
the dominant influences
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
White bar (left) is the
time slice of interest
3,000
controls recidivism
2,000
Red arrows (below) are
the dominant influences
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
4,000
Dynamic
complexity even in
a structure this
aggregate and tiny!
3,000
controls recidivism
2,000
1,000
0
0
30
60
Time (Month)
90
Time in post
TANF employ
120
Outflow from post
TANF employ
Recidivism
Enter TANF
+
Families on
TANF
support capacity
TANF support
capacity
+
-
Job finding
rate
Time to find
first job
+
Post TANF
employed
- To mainstream
employment
support capacity
Post TANF employment
support capacity
Probability of
recidivism
System Dynamics and
Dynamic Complexity



Thinking dynamically moves us beyond
separate events and decisions, toward
understanding.
causal thinking.
It improves (makes more realistic) how
we think about the world and how we
Burden” Story




Is there a problem that is getting
gradually worse over the long term?
Is the overall health of the system
Is there a growing feeling of
helplessness?
Have short-term fixes been applied?

The Casa Olay problem of using cupouns to
generate business and then can’t get away




Identify the problem
Next, identify a fundamental solution
Then, identify one or several
symptomatic solutions
Finally, identify the possible negative
“side effects” of the symptomatic
solution
Review

We have now seen two of the basic
systems archetypes.




The Limits to Growth Archetype
The Shifting the Burden Archetype
As the archetypes are mastered, they
become combined into more elaborate
systemic descriptions.
The basic “sentences” become parts of
paragraphs
Seeing Structures, not just
Trees


Helps us focus on what is important and
what is not
Helps us determine what variables to
focus on and which to play less
attention to
WonderTech: The Chapter 7
Scenario


A lesson in Growth and
Underinvestment
What Senge gets out of this is the
Growth and Underinvestment Archetype

A combination of variants of the Limits to
Growth Archetype and the Shifting the
Burden Archetype
The WonderTech Scenario

WonderTech continues to invest in the growth
side of the process. Sales grow but then
plateau. Management puts more sales people
into the field. Offers more incentives to sales
force. But because of long lead times,
customers wane. “Yes you have a great
time promise of eight weeks. We know; we’ve
heard from your other customers.” In fact,
the company relaxed its lead-time standard
out to twelve to sixteen weeks because of
The Reinforcing Loop
Size of Sales Fo rce
REINFOR
CING
Revenues
Number of Orders
The Balancing Loop:
Following the LTG Archetype
Sales Diff iculty
Size of Sales Force
Number of Orders
Revenues
Size of Backlog
Delay
Delivery T ime
The Growth Curve: Page 117
What’s happened?

WT’s management did not pay much
attention to their delivery service. They
mainly tracked sales, profits, market
share and return on investment. WT’s
managers waited until demand fell off
times. But this is too late. The slow
delivery time has already begun to
correct itself. The management was
not very concerned about the relaxed
The WonderTech Scenario


The firm decides to build a new
manufacturing facility. But the facility
comes on line at a time when sales are
declining and lead times are coming
back to the eight-week standard.
Of every 10 startup companies, 5 will
disappear with five years, only 4 survive
into their tenth year and only 3 into
their fifteenth year.
The Shifting the Burden
Component
Sales Dif ficulty
Number of Orders
Delay
Size of Backlog
Delivery T ime
Delivery time standard
P roduction Capacity
P erceived need to im prove delivery tim e
Delay2
Put the whole thing together
Methodology



Sees problems as conforming to a finite
number of “archetypes”
Formulates models based on
combinations of the archetypes

What about situations and systems that
are technology-driven, dynamics-driven,
exogenously-driven, anything but problemdriven
Methodology


But does this become sufficiently
general to accommodate all dynamical
“scenarios and situations”?
It is difficult to translate his archetypes
and causal models into running system
dynamics simulations

A lot of variables (RATE VARIABLES,
specifically) get left out in terms of
connections
Methodology


The focus is on characterizing the
dynamics, not on how to capture that in
terms of stocks, flows and information
paths
He doesn’t label his edges with “+” or
“-” signs
Another methodology: The
Sector Approach to SD model
formulation

Begin by identifying the sectors



Determine the within-sector structure


A “sector” is all the structure associated
with a single flow
There could be several states in a single
sector
Reuse existing “molecules” where possible
Determine the between-sector
information infrastructure
A Single-sector Exponential
goal-seeking Model

Sonya Magnova is a television
retailer who wishes to maintain a
desired inventory of DI television
sets so that she doesn’t have to sell
her demonstrator and show models.
Sonya’s ordering policy is quite
toward desired inventory DI so as to
force these to conform as closely as
possible. The initial inventory is Io.
The time required for ordered
inventory to be received is AT.
A Two-sector
Housing/population Model

A resort community in Colorado has
determined that population growth in
the area depends on the availability of
hoousing as well as the persistent
natural attractiveness of the area.
Abundant housing attracts people at a
greater rate than under normal
conditions. The opposite is true when
housing is tight. Area Residents also
leave the community at a certain rate
due primarily to the availability of
Two-sector Population/housing
Model, Continued

The housing construction iindustry, on
the other hand, fluctuates depending on
the land availability and housing
desires. Abundant housing cuts back
the construction of houses while the
opposite is true when the housing
situation is tight. Also, as land for
residential development fills up (in this
mountain valley), the construction rate
decreases to the level of the demolition
rate of houses.
What are the main sectors and
how do these interact?


Population
Housing
What is the structure within
each sector?


Determine state/rate interactions first
Determine necessary supportng
infrastructure


PARAMETERS
AUXILIARIES
What does the structure
within the population sector
look like?



RATES: in-migration, out-migration, net
death rate
STATES: population
PARAMETERS: in-migration normal, outmigration normal, net death-rate
normal
What does the structure
within the housing sector look
like?





RATES: construction rate, demolition
rate
STATES: housing
AUXILIARIES: Land availability
multiplier, land fraction occupied
PARAMETERS: normal housing
housing
PARAMETERS: land occupied by each
unit, total residential land
What is the structure between
sectors?

There are only AUXILIARIES,
PARAMETERS, INPUTS and OUTPUTS
What are the between-sector
auxiliaries?





Housing desired
Housing ratio
Housing construction multiplier
Attractiveness for in-migration multiplier
PARAMETER: Housing units required
per person
System Dynamics
Douglas M. Stewart, Ph.D.
Anderson Schools of
Management
University of New Mexico
Adapted from Senge, P. The Fifth
Discipline, Doubleday/Currency, 1990.
Why System Dynamics





TQM requires a systems view of the
world
See the interrelationships rather than
the linear cause-effect chains
See the process of change rather than a
snapshot
In systems thinking every influence is
both a cause and effect
Introduction to Systems
Diagrams

From any element in a situation you can
trace arrows that represent the
influence on another element.
Example: Filling a glass of
water
Am I filling the glass of water?
Desired
Water Level
Faucet Position
Perceived Gap
Water Flow
Current
Water Level
Or is the level of water controlling my hand?
Building Blocks of Systems
Thinking



Reinforcing Loops (Positive Feedback)
Balancing Loops (Negative Feedback)
Delays
Reinforcing Loops
If the product is good we have a virtuous cycle.
Sales
Positive Word
of Mouth
Satisfied
Customers
If the product is bad we have a vicious cycle.
Reinforcing Loops



The snowball effect
Accelerating growth or accelerating
decline
These systems can take you by
surprise!
Balancing Loops
Body Temperature
Desired Body
Temperature
Temperature Gap
Balancing Loops



System reverts to status quo
Often in business the goals are implicit
When there is resistance to change,
look for a hidden balancing process
Delays: The Sluggish Shower
Current Water
Temperature
Shower Tap
Setting
Desired Water
Temperature
Temperature
Gap
Delays



When you tell the story add the word
“eventually”
Cause the system to overshoot the
target
Aggressive action produces the opposite
of what is intended
An Example: Reducing
Burnout
Actual Hours
Worked
Threat of being
perceived as
uncommitted
Implicit goal of 70
hour workweek
Heroism Gap
Archetype 1: Limits to Growth

A reinforcing process is begun to
produce a desired result. It works, but
also creates unintended side-effect (a
balancing process) that eventually slows
down success.
Limits to Growth
Size of
Market Niche
Motivation and
Productivity
Morale
Growth
Promotion
Opportunities
Where is the leverage?
Saturation of
Market Niche
Limits to Growth


The tendency is to push hard
The leverage not in the reinforcing loop,
but removing the limits on the
balancing loop
Don’t push growth. Remove the factors
that limit growth
Archetype 2: Shifting the
Burden



An underlying problem generates
symptoms that demand attention.
But…underlying problem is obscure or
costly to confront.
So… people shift the burden to other
Shifting the Burden
Bring in HR Expert
Personnel
Performance
Problems
Develop Managers’
Abilities
Expectations that HR
Experts will solve
problem
Shifting the Burden



Beware the symptomatic solution
Benefits are short term at best
Pressure on symptomatic response only
gets larger
Archetype 3: Eroding Goals


A shifting the burden type structure
where the short term solution is letting
the long term goal decline.
Customers are dissatisfied with late
schedules. Production scheduling never
really under control. Company says we
ship to schedule 90% of time.
But…every time the schedule begins to
slip, they add to quoted delivery times.
Eroding the Goals
Pressures to
Goal
Early warning symptom:
“It’s OK if our
performance standards
slide just a little until the
crisis is over”
Gap
Condition
Actions to
Improve Conditions
Principle: Hold the vision
Archetype 4: Success to the
Successful


Two activities compete for limited
resources. The more successful one
becomes, the more support it gains,
thereby starving the other.
Manager has two protégés. One gets
sick for a week, the other gets
preferential treatment. The first feeling
approval flourishes and therefore gets
more opportunity. The second, feeling
insecure, languishes and eventually
Success to the Successful
Success
of A
Resources
to A
Warning symptom: One of two
interrelated activities is
beginning to do very well and
the other is struggling
Allocation to
Success
of B
Resources
to B
Principle: Look for
overarching goal to balance
both, or decouple the shared
resource.
Tragedy of the Commons


Individuals use a joint resource on the basis
of individual need. At first they are rewarded
for using it. Eventually they get diminished
returns, which causes them to intensify their
efforts. The resource becomes depleted.
Several divisions use a common retail sales
force. Each is concerned that sales force will
not give enough attention to their products.
One manager sets higher than needed
targets. Other managers followed. Sales
force becomes tremendously overburdened,
performance declines and turnover increases.
Tragedy of the Commons
Individual A’s
Activity
Net Gains
For A
Resource
Limit
Gain per
Individual
Activity
Total
Activity
Individual B’s
Activity
Warning Symptom: There used to be plenty
for everyone. Now things are tough. I will
have to work harder to succeed.
Net Gains
For B
Principle: Manage the commons
through education and selfregulation or an official regulation
Archetype 5: Growth and
Underinvestment


Growth approaches a limit which can be
pushed out with investment in additional
capacity. But if investment is not aggressive
enough to forestall growth, it may never get
People express was unable to build service
capacity to keep up with demand. Firm tried
to outgrow problems. Deteriorating service
quality, increased competition and lower
morale followed. Firm relied on
underinvestment strategy until customers no
longer wanted to fly airline.
Principle: Build in advance of demand as
strategy for developing it. Hold the vision
on quality standards.
Growth and Underinvestment
Reputation
Increased
Flights
Number of
Passengers
Revenues
Warning: We used to be
best and will be again, but
right now we need to
conserve resources and
not overinvest
Quality
Standard
Service
Quality
Service
Capacity
Perceived need
To improve quality
Service Capacity
Spend on R&D to Drive
Growth
Size of
Engineering Staff
R&D Budget
Management
Complexity
Revenues
New
Products
Management
Burden to Senior
Engineers
Product
Development
Time
Senior Engineers
Ability to Manage
The growth of survey based
Researcher A’s
Surveys
Net Research
For A
Total #
Surveys
Researcher B’s
Surveys
Net Research
For B
Tolerance
Survey
Burnout and
Resistance
What is a system?

A definition as offered by Gregory
Watson in his book, Business Systems
Engineering: “System means a
grouping of parts that operate
together for a common purpose.”
(Watson, 1994).
What is a System? (Cont’d)

Definition as adapted from Random House
Dictionary: A system is an assemblage or
combination of elements or parts forming a complex
or unitary whole, such as a river system or a
transportation system; any assemblage or set of
correlated members, such as a system of currency;
an ordered and comprehensive assemblage of facts,
principles, or doctrines in a particular field of
knowledge or thought, such as a system of
philosophy; a coordinated body of methods or a
complex scheme or plan of procedure, such as a
system of organization and management; any regular
or special method of plan or procedure, such as a
system of marking, numbering, or measuring
What is Thinking?

What, precisely, is thinking? When at the reception of
sense impressions, memory pictures emerge, this is
not yet thinking. And when such pictures form a
series, each member of which calls forth another, this
too is not yet thinking. When, however, a certain
picture turns up in many such series, then—precisely
through such return—it becomes an ordering element
for such series…Such an element becomes an
instrument, a concept. I think the transition from free
association of dreaming to thinking is characterized
by the more or less dominating role which the
concept plays in it (Einstein, in Schilpp, 1949).
Connectedness

“If you wish to understand a system,
and so be in a position to predict its
behavior, it is necessary to study the
system as a whole. Cutting it up into
bits for study is likely to destroy the
system’s connectedness, and hence the
system itself.” (Sherwood, 2002)
Connectedness

“If you wish to influence or control the
behavior of a system, you must act on
the system as a whole. Tweaking it in
one place in the hope that nothing will
happen in another is doomed to
failure—that’s what connectedness is all
Systems Theory
General Systems Theory
 Chaos Theory
 Quantum Theory
 Ecological Theory

Systems Principles
Openness
 Purposefulness
 Multidimensionality
 Emergent property
 Counterintuitivess

Systems Thinking
Problem Solving Tool
 Pioneered By Biologists
 Looks At The Whole View
 Reduces Complexity
 Controls System Behavior

Systems Thinking Methodologies
Soft Systems Methodologies
 Hard Systems Thinking
 The Fifth Discipline

Systems Thinking Tools
Archetypes
 Causal Loop Diagrams
 Stocks and Flows
 Simple Structure Dynamics

Systems Thinking Models
Archetypes
 Causal Loop Diagrams
 Stocks and Flows

Archetype: Fixes That Backfire
Problem
Symptom
Fix
Original threshold of tolerance
Unintended
consequences
delay
The problem symptom alternately improves. It goes down, then comes
Back up again and usually comes back worse than before (Senge, 1994).
Archetype: Limits to Growth
Problem
Symptom
Actual
performance
Corrective
action
Growth occurs and sometimes dramatic but levels off and/or
falls into decline (Senge, 1994).
Archetype: Shifting the Burden
Quick fixes
Side
effects
Problem
Symptom
Corrective
Actions
delay
Root cause
Three patterns exist side by side. The reliance on short-term fixes grows stronger, while
efforts to fundamentally correct the real problems grow weaker, and the problem symptom
alternately improves and deteriorates (Senge, 1994).
Archetype: Tragedy of Commons
limits or constraints
A’s growth
process
A’s growing
action
actual performance
that A measures
A’s limiting
process
gain per
individual
activity
total growing
action
B’s limiting
process
B’s growth
process
B’s growing
action
PROCESS
actual
performance
that B measures
delay
Total activity grows, but the gains from individual activities are dropping off. Parts of the organization
are suffering for the whole (Senge, 1994).
A’s activity with B
(actions in B’s favor)
A’s unintended
obstruction of B’s success
A’s success
A’s fixes to
Improve A’s
own results
B’s success
B’s unintended
obstruction of A’s success
B’s activity with A
(actions in A’s favor)
B’s fixes to
improve B’s
own results
Each sides performance either declines or stays level and low, while competitiveness
Increases over time (Senge, 1994).
Causal Loop
Diagrams
O
Pressure from
Contractor for
More Dollars
Quality of the
Government-Industry
relationship
Pressure on the
Government to stay
Within cost
S
Risk of cost overruns
O
S
Pressure on the
Government to deliver
A workable system
Pressure on the
Government to control
The contractor
S
Pressure on the
Government to control
Costs and quality
S
S
Requirement for high
Technical and service
Quality standards
Risk to the
Government of
Cost escalation
S
Government Cost
From Sherwood’s
Causal Loop
Diagrams
S
S
Dependency of the
Government on the
contractor
S
S
Policy of
outsourcing
Pressure on the
Government
To satisfy
the taxpayers
S
Causal Loop Diagram
Total Work
Capacity
My Goals
My Consumption of
Dollars
Dollars
+
+
+ -
-
+
My Need for Work
+
My fear that you will
Not leave enough work
me
+
Work
Available
+
-
-
-
Not leave enough work
you
Number of activities competing
For work
+
Conflict
+
Option 1: Two reinforcing loops (Sherwood, 2002)
Causal Loop Diagram
Total Work
Capacity
My Goals
My Consumption of
Dollars
Dollars
+
+
+
+ -
-
-
-
Work
Available
My Need for Work
+
+
+
+
My fear that you will
Not leave enough work
me
-
-
Not leave enough work
you
Police the
Work allocation
+
+
Appeal to
A higher
authority
+
Option 2: Limit consumption—before turf war (Sherwood, 2002)
Causal Loop Diagram
Total Work
Capacity
My Goals
My Consumption of
Dollars
-
Dollars
+
+
-
+
+ +
Work
Available
My Need for Work
-
+
+
My fear that you will
Not leave enough work
me
My willingness to
Participate in a cooperative
Goal-setting process
+
-
+
-
Recognition of
The need for
cooperation
+
Not leave enough work
you
My willingness to
Participate in a cooperative
Goal-setting process
+
Option 3: Players See the Sense in Cooperation (Sherwood, 2002)
Causal Loop Diagram
Total Work
Capacity
My Goals
My Consumption of
Dollars
-
Dollars
+
+
-
+
+ -
+
Work
Available
My Need for Work
-
+
+
My fear that you will
Not leave enough work
me
My willingness to
Participate in a cooperative
Goal-setting process
+
-
+
-
Recognition of
The need for
cooperation
+
+
Not leave enough work
you
My willingness to
Participate in a cooperative
Goal-setting process
+
Mutual Trust
Best Solution: Goals Match—Combined Benefit!
+
System Dynamics: Growth and Goal Seeking Structure and Behavior
Goal
state of
the system
state of
the system
Time
Time
+
Goal (desired
state of
the system)
state of
the system
+
Net Increase
Rate
R
State of
The System
discrepancy
B
+
Corrective
action
+
+
Stocks and Flows
Valves represent the flow of inventory into and out of the warehouse
Stock
Inventory
source
sink
Production (inflow)
Shipments (outflows)
Sources and sinks are outside the model boundary.
Stocks and Flows are used in Causal Loop Diagrams to cover some
of their limitations of not being able to capture stocks and flows
within systems (Sterman, 2000).
Some Models from Soft
Systems
Methodology--Checkland
The inquiring/learning cycle of SSM (Checkland, 1999)
perceived
real-world
problem or
situation
selection of
‘comparison’
(question problem
situation using models)
action to
improve
models of relevant
purposeful activity
systems each based on
a declared world-view
find
accommodations
which enable
a structured debate
and feasible change
Principles
• real world: a complexity of relationships.
• relationships exploded via models of purposeful activity
based on explicit world visions.
• inquiry structured by questioning perceived situation using the models as a
source of questions.
• ‘action to improve’ based on finding accommodations (versions of the
situation which conflicting interests can live with)
• inquiry in principle never-ending; best conducted with wide range of
interested parties; give the process away to people in the situation.
Method for Unstructured Problems
1.
the problem situation:
unstructured
7.
action to improve
the problem
situation
2.
the problem
situation:
expressed.
6.
feasible, desirable
changes
5.
comparison
of 4 with 2
Real world
Systems thinking
4.
conceptual
models
3.
root definitions of
systems
Checkland, 1999
4.a.
formal systems
concept
4.b.
other systems
thinking
An area of reality containing:
Concerns
Issues
Problems
Aspirations
Other sources
Gives rise to
IDEAS
from which may
be formulated
provide
which support
criticism of
THEORIES:
Substantive
Methodologies
which present
CASE RECORDS
PROBLEMS
documented in
which may be
analyzed using
to be used in action
(intervention, influence,
observation) in
which yield
MODELS
METHODOLOGY
A developing subject
which may be
manipulated using
TECHNIQUES
which may be
used in
ANY DEVELOPING SUBJECT (Checkland, 1999)

Laws of Systems Thinking
Today’s problems come from yesterday’s solutions.


The harder you push, the harder the system pushes back.










Moving the problem around.
Compensating feedback.
Behavior grows better before it grows worse.
The easy way out usually leads back in.
The cure can be worse than the disease.
Faster is many times slower.
Cause and effect are not closely related in time and space.
Small changes can produce big results—but the areas of highest
leverage are often the least obvious.
You can have your cake and eat it too, but not at the same time.
Dividing the elephant in half does not produce two small elephants.
There is no blame.
Senge, 1990
```