Problem Definition and Causal Loop Diagrams

James R. Burns

July 2008

Assignment

Complete exercise 12 and use VENSIM to create the CLD

VENSIM cannot translate CLD’s into working simulations

Develop the CLD for your term project problem

Problem Definition

The wrong model for the right problem is disconcerting, but fixable

The “right” model for the wrong problem is disastrous

The Right Problem

The first order of the day Requires discussion, dialogue, listening “I feel your pain”

The right paradigm

Is this a dynamic problem? Are there risk aspects to it? Is it a resource allocation problem? A scheduling/routing problem? A cost minimization problem? APPLY THE RIGHT PARADIGM

Dynamic problems

There is change over time The changing character of the situation IS

THE PROBLEM The problem should be studied in aggregates The problem does not have a significant

stochastic component or complexion to it

Dynamical Models: Explicit, Ordinary Differential Equations

. ,,, 00 xtxtptxfx

Start with descriptions of the following

PURPOSE Identify who the decision-maker(s) are and

involve them in the model-building process

PERSPECTIVE PROBLEM MODE

What are we doing here????

Attempting to characterize, cope with and understand complexity Especially DYNAMIC complexity, but also to a

lesser extent detail complexity

Inventing a physics for a system or process for which there exists no physics You get to become a Newton, a Liebnitz, a

Galileo, an Einstein, a ….

WHY???

How many of you have ever used a model to make a decision or take an action?

All decisions/executive actions are taken on the basis of models all the time

Because mental models frame and color our understanding of the problem—forcing us to take a particular course of action

Mental models must be driven by more formal, refined and analytical models—causal models/simulation models

Uses to which these models can be put

What IF experiments—hands on experimentation Decision making

Planning Problem solving Creativity Out of the box thinking

Hypothesis testing LEARNING

The Methodology once problem is identified

1. Find substance2. Delineate CLDs, BOT charts3. Submit these for outside scrutiny4. Delineate SFD5. Implement simulation in VENSIM6. Submit for outside VALIDATION7. Utilize model for policy experimentation

Find substance

Written material Books Articles Policy and procedure manuals

People’s heads Order of magnitude more here Must conduct interviews, build CLD’s, show

them to the interviewees to capture this

Delineate CLDs, BOTs

Collect info on the problem List variables on post-it notes Describe causality using a CLD Describe behavior using a BOT diagram

Submit these for outside scrutiny

We simply must get someone qualified to assess the substance of the model

Delineate SFD

Translate CLD into SFD

Implement simulation in VENSIM

Enter into VENSIMPerform sensitivity and validation studies

Submit for outside validation

Utilize model for policy experimentation

Perform policy and WHAT IF experimentsWrite recommendations

Key Benefits of the ST/SD

A deeper level of learning Far better than a mere verbal description

A clear structural representation of the problem or process

A way to extract the behavioral implications from the structure and data

A “hands on” tool on which to conduct WHAT IF

Places where failure can occur

You must have decision maker involvement If you are going to have an impact on their

mental models, they must be involved in the model development process from beginning to end

Solutions to the model must be reality checked to see if in-fact they can become solutions to the problem

Causal Loop Diagrams [CLD’s]

Motivation: CLD’s are excellent for…

Capturing hypotheses about the structural causes of the dynamics

Capturing the mental models of individuals or teams

Communicating the important feedbacks you believe are responsible for creating a problem

Notation

Variables and constants called quantities Arrows—denoting the casual influences

among the quantities Independent quantity—the cause Dependent quantity—the effect

dependentquantity

independentquantity

Quantities

Use nouns of noun phrases Assert nouns and noun phrases in their

positive sense

Example

Costs Profits

--

Costs Losses

+

The Connector

Also called “arrow,” “edge,” Is always directed from a quantity to a

quantity Denotes causation or influence

Could be proportional InverselyDirectly

Could be accumulative or depletive

Single-sector Exponential growth Model we considered

Consider a simple population with infinite resources--food, water, air, etc. Given, mortality information in terms of birth and death rates, what is this population likely to grow to by a certain time?

Over a period of 200 years, the population is impacted by both births and deaths. These are, in turn functions of birth rate norm and death rate norm as well as population.

A population of 1.6 billion with a birth rate norm of .04 and a death rate norm of .028

We Listed the Quantities

Population Births Deaths Birth rate norm Death rate norm

Births

population

Deaths

Birth rate normal

Death rate normal

R

B

++

+

+

+

--

Using VENSIM TO CONSTRUCT CLD’s

Use the variable – auxiliary/constant tool to establish the quantities and their locations

Use the “arrow” tool to establish the links between the quantities

Use the “Comment” tool to mark the polarities of the causal edges (links, arrows)

Use the “Comment” tool to mark the loops as reinforcing or balancing

Experiments with growth models

Models with only one rate and one state Average lifetime death rates Models in which the exiting rate is not a

function of its adjacent state

Example:

Build a model of work flow from work undone to work completed.

This flow is controlled by a “work rate.” Assume there are 1000 days of undone work Assume the work rate is 20 completed days a month Assume the units on time are months Assume no work is completed initially.

Solving the problem of negative stock drainage

pass information to the outgoing rate use the IF THEN ELSE function

Causation vs. Correlation

Ice Cream Sales Murder rate

Ice Cream Sales 0 Murder rate 0

AverageTemperature

Inadequate cause: Confusion

Market Share Unit Costs

--

Market Share Unit Costs

ProductionVolume

Cumulative ProductionExperience+

+

-

Validation of CLD’s

Clarity Quantity existence Connection edge existence Cause sufficiency Additional cause possibility Cause/effect reversal Predicted effect existence Tautology

Simplified Translationof CLD's into SFD's

Motivation

In the current “environment” there are too many connection “opportunities” that confuse and invalidate models built by naive users

The conventional translation of CLD’s into SFD’s is not easy. We may need to distinguish between Senge-style CLD’s

created for just the purpose of capturing the dynamics of the process from CLD’s intended to lead us to a SFD

More Motivation

variable

rate

Variable

Rate

RATEANO RATE

STOCK

Rate In

Rate Out

PARAMETER

STOCK1

STOCK2 STOCK3

RATE1

Robust Loops

In any loop involving a pair of quantities/edges,

one quantity must be a rate the other a state or stock, one edge must be a flow edge the other an information edge

CONSISTENCY

All of the edges directed toward a quantity are of the same type

All of the edges directed away from a quantity are of the same type

Rates and their edges

q1

q2

q3

RATES

q4

q5

q6

Informationedges

Flow edges

Parameters and their edges

PARAMETER

q1

q2

q3

Informationedges

Stocks and their edges

q1

q2

q3

STOCK

q4

q5

q6

Flow edges Information edges

Auxiliaries and their edges

AUXILIARY

q1

q2

q3

q4

q5

q6

Informationedges

Informationedges

Outputs and their edges

OUTPUT

q1

q2

q3

Informationedges

STEP 1: Identify parameters

Parameters have no edges directed toward them

STEP 2: Identify the edges directed from parameters

These are information edges always

STEP 3: By consistency identify as many other edge types as you

can

STEP 4: Look for loops involving a pair of quantities only

Use the rules for robust loops identified above

q1

q2

q3 q4

q5

q6

q7

q8

q3

q6

q2

q7

q1

q4

q5 q8

q17

q12

q11

q10

q5

q13q14

q4

q16

q2q1

q3q9

q7

q6

q8

q15

      5 CC/AA 1

6 AA/DD -1

7 AA/(BB.DD) 1

8 AA/ZZ 1

9 BB 1

10 CC 1 -1 1

11 CC\DD 1

12 DD -1

13 CC/DD -1

14 CC/(AA.DD) 1

15 ZZ -1

16 CC/AA -1

17 CC 1 -1 

Fig 2. Square ternary matrix (STM) corresponding to causal diagrammodel D shown in Fig. 1.

1 AA 1 -1 1 2 AA/DD 1 3 I/DD 1 4 dimless 1 1

 

 

 

 

 

 

 

 

 

 

 

Conclusions

CLD translation involves identifying every quantity and edge as to type

A rule structure might help to prevent naïve users from committing structural/causal implausibilities

It would be possible to automate the translation of CLD’s into SFD’s if the CLD’s are well-formed and “robust.”

A single-sector Exponential goal-seeking Model

Sonya Magnova is a resources planner for a school district. Sonya wishes to a maintain a desired level of resources for the district. Sonya’s new resource provision policy is quite simple--adjust actual resources AR toward desired resources DR so as to force these to conform as closely as possible. The time required to add additional resources is AT. Actual resources are adjusted with a resource adjustment rate

What are the quantities??