lecture 5 : systems models and
diagrams
this lecture is about modelling
• modelling
• influence diagrams
• flow charts, precedence charts, spray diagrams
etc.
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a model is
• a representation of reality intended for some purpose
• a representation of reality intended to be of use to someone
charged with managing or understanding that reality
• a representation of reality intended to be of use to someone
in understanding, changing, managing and controlling
that reality
• a representation of part of reality as seen by the people
who wish to use it to understand, to change, to manage and
to control that part of reality
• an external and explicit representation of part of reality
as seen by the people who wish to use it to understand, to
change, to manage and to control that part of reality
• a model is a tool for thinking
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a system model specifies:
• the transformation processes or activities of the
system
• the boundary, ie. the narrow and the wider
systems of interest
• subsystems of the narrow system involved in
transformation; the dynamic relationships ie.
processes; stable relationships ie. structure
• uncontrollable inputs; control inputs; decisions and
decision rules
• outputs that are desired, undesired, planned,
unplanned
• outputs serving as performance measures
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question
does aspect
affect
system?
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is aspect affected by system variables or
inputs?
answer
YES
NO
YES
component
or
relationship
input
NO
output
irrelevant
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models should be:
• simple but complete, not trivial or irrelevant
– simple models are easier to understand, to evaluate,
to work with and to communicate
– they can be explained to problem users and owners;
this helps to convince them to use models as tools
for thinking (for example spreadsheets are fine)
– even if users cannot comprehend its inner working
properly, a model should be easy to manipulate
and it should be tested by owners and users
– simplicity in doing something is parsimony (Occam’s
razor: the fewest possible assumptions should be
made in explaining a thing ) model should observe
parsimony
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• start small, then add and refine
– start with a small model even if it is not
sufficiently realistic
– make sure you immediately test it numerically; if
data is not yet ready, use approximate data and
guesstimates; this will show if the model makes
sense; see if it helps you to understand the
problem situation
– as you discover the shortcomings of your model,
refine it:
• either by enriching, ie. adding new features,
• or by reformulating, ie. replacing with a different,
new model
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• a good model should be:
– adaptive and robust so that it can be modified
when data or the problem situation changes
– appropriate to the problem situation, eg.
practicable to run within the timeframe needed
– relevant and approprite for decision making
eg. without extensive need to process model
outputs
– aided by diagrams such as influence diagrams
– used to go back to rich pictures and mind maps
for revision of both these and the model etc.
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influence diagrams
parameters,
constraints, etc
output
control i/p,
decision rules, etc
A
influence
B
system
variables:
rates, levels
etc
rate = flow (a process element)
level = stock (a structural element)
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stocks and flows or
levels and rates
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flow charts, spray diagrams etc.
• flow charts are used to show logical or
temporal flows such as:
– material flows
– information flows
– decision flows etc.
• spray diagrams are useful to map
detailed cause-and-effect relationships
• precedence charts are useful in project
management
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