System Dynamics Pitfalls and Pointers
Soft Variables and Intangibles
A hard variable is one which is used to describe
attributes or relationships in a problem to which physical laws
apply or where governing business rules are readily formulated using
algebraic operators linking other variables which, themselves, are readily quantifiable
and quantification can be validated. Those constructs for which quantitative
metrics and numerical data are available are sometimes termed hard
data or hard variables—the term hard being intended to show
that numerical data are more accurate and real than qualitative
data—qualitative data being seen by many modellers as insubstantial and
In contrast soft variables are a class of variables, which
includes a sub-class known as intangibles. These relate to attributes
of human behaviour or effects that variations in such behaviour
produce. As far as soft variables are concerned, numerical data
are often unavailable or non-existent. Despite this, such variables are
known to be critical to decision making and, therefore should
be incorporated into system dynamics models. But, the challenge is
to incorporate them into our models in ways that are
both scientifically sound and logically defendable.
The following explains how to
incorporate soft variables and intangibles in system dynamics models, in combination with hard variables .
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