Page 287 - Mechanical Engineers' Handbook (Volume 2)

278 Analysis, Design, and Information Processing

• Mathematical programming, which is used extensively for operations research and
analysis practice, resource allocation under constraints, resolution of planning or
scheduling problems, and similar applications. It is particularly useful when the best
equilibrium or one-time setting has to be determined for a given policy or system.
• Optimum systems control, which addresses the problem of determining the best con-
trols or actions when the system, the controls or actions, the constraints, and the
performance index may change over time. A mathematical description of system
change is necessary to use this approach. Optimum systems control is particularly
suitable for refining controls or parameters in systems in which changes over time
play an important part.
Application of the various refinement or optimization methods, like those described here,
typically requires significant training and experience on the part of the systems analyst. Some
of the many characteristics of analysis that are of importance for systemic efforts include
the following:
1. Analysis methods are invaluable for understanding the impacts of proposed policy.
2. Analysis methods lead to consistent results if cognitive bias issues associated with
expert forecasting and assessment methods are resolved.
3. Analysis methods may not necessarily lead to correct results since ‘‘formulation’’
may be flawed, perhaps by cognitive bias and value incoherence.

Unfortunately, however, large models and large optimization efforts are often expensive
and difficult to understand and interpret. There are a number of possibilities for ‘‘paralysis
through analysis’’ in the unwise use of systems analysis. On the other hand, models and
associated analysis can help provide a framework for debate. It is important to note that
small ‘‘back-of-the-envelope’’ models can be very useful. They have advantages that large
models often lack, such as cost, simplicity, and ease of understanding and, therefore, ex-
plicability.
It is important to distinguish between analysis and interpretation in systems engineering
efforts. Analysis cannot substitute, or will generally be a foolish substitute for, judgment,
evaluation, and interpretation as exercised by a well-informed decision-maker. In some cases,
refinement of individual alternative policies is not needed in the analysis step. But evaluation
of alternatives is always needed, since, if there is but a single policy alternative, there really
is no alternative at all. The option to do nothing at all must always be considered as a policy
alternative. It is especially important to avoid a large number of cognitive biases, poor judg-
ment heuristics, and value incoherence in the activities of evaluation and decision making.
The efforts involved in evaluation and choice making interact strongly with the efforts in the
other steps of the systems process, and these are also influenced by cognitive bias, judgment
heuristics, and value incoherence. One of the fundamental tenets of the systems process is
that making the complete issue resolution process as explicit as possible makes it easier to
detect and connect these deficiencies than it is in holistic intuitive processes.

4.3 Information Processing by Humans and Organizations
After completion of the analysis step, we begin the evaluation and decision-making effort
of interpretation. Decisions must typically be made and policies formulated, evaluated, and
applied in an atmosphere of uncertainty. The outcome of any proposed policy is seldom
known with certainty. One of the purposes of analysis is to reduce, to the extent possible,