Page 31 - DCAP208_Management Support Systems

Management Support Systems

Notes A decision making attempts to determine whether a problem exists, identify its symptom,
determine its magnitude and explicitly define it. What is described as a problem may be only a
symptom of a problem (real world problems are complicated by many interrelated factors and
is difficult to distinguish between the symptoms and the real problem). The measurement of
productivity and the construction of a model are based on real data. The collection of data and
the estimation of future data is a difficult step in the analysis.
Data may have some inconvenience like:

data are not available,
obtaining data may be expensive,
data estimation may be subjective,
data may be insecure,
important data that influence the results may be qualitative,
there may be too many data – information overload,
results may occur over an extended period,
the future data will be similar to historical data.
After the preliminary investigation is possible to determine whether a problem really exists,
where is located, how important it is, whether an information system is reporting a problem or
only the symptoms of a problem.

Problem Decomposition

The complex problems can be divided into sub-problems. Solving the simpler sub-problems
may help in solving the initial one. Poorly structured problems may have highly structured
sub-problems. Decomposition facilitates communication among decision makers. Decomposition
is one of the most important aspects of the Analytical Hierarchy Process – AHP – which helps
decision makers incorporate both qualitative and quantitative factors into the decision-making
models.

Problem Ownership

In the intelligence phase it is important to establish problem ownership. A problem exists in an
organization only if someone or some group takes on the responsibility of attacking it and if the
organization has the ability to solve it.

2.4.2 Design Phase

The design phase involves finding or developing and analyzing possible courses of action:
understanding the problem and testing solution for feasibility. A model of the decision-making
problem is constructed, tested and validated.
Modeling involves conceptualizing a problem and abstracting it to quantitative and qualitative
form – for a mathematical model the variables are identified, their mutual relationship are
established. Simplifications are made whenever necessary through assumptions.
A simpler model leads to lower development costs, easier manipulation and a faster solution
but is less representative of the real problem and can produce inaccurate results.
The process modeling is art (creativity are required when art determining what simplifying
assumptions can work and how to integrate models to obtain valid solutions) and science (there
are science many standard model classes available and an analyst can say which one is applicable).

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