"It isn't that people can't see the solution,
it is that they can't see the problem."
Is modeling "good" for me can
only be answered, once the problem is clearly posed and the key variables
or parameters necessary for answering the problems are identified.
If the planning process requires reconsidering
business goals, alternatives, constraints, expectations, preferences and
the decision rules, a model should be defined. Decision makers still intend
to be rational with all these inputs, but they are limited by their mental
capacities as well as by the accuracy and completeness of the available
Solution to above problem can be either rule based or choice based.
In another words one can say it can be either more by clarity and consistency
or by ambiguity and inconsistency.
In a situation it is always preferable to define
scenarios, rules, and constraints. With these inputs, the relevant data
is specified and at the same time framework for a model emerges. Now
use of state-of-the-art mathematical and computational techniques, which
helps find an optimum solution, can be a great decision making tool for
To experiment in real life situation with ambiguity
and inconsistency in your mind can be more complex and expensive. The
outcome of experiment is either a right or a wrong solution but a right
solution, which might be irrelevant, can also be a possibility. If the
cost of this irrelevant solution is non-negotiable to development of model,
you should go for modeling technique that will help you save your time,
money and energy.
If a development of a model can indicate the future consequences associated
with each alternative solution, one can justify the cost of savings by
calculating cost associated with each of the alternatives. So a decision
maker can get a chance in advance to make a choice from the alternatives.
Availability of right data and techniques
can also be a factor to decide the need for a model. No model without
right data can give you an optimum solution. Similarly the framework of
right mathematical technique with existing problem is equally important
to design a model.
Modeling is widely used in industry, commerce and government for various departments but model can be applied to simple situation like calculation of cattle feed mix to complex scenario of stock market prediction.