Maximize Human Understanding

Models and measurements of physical force systems (e.g. dams, planes, rockets, transistors) are commonly used for quantitative prediction. What is the chance a dam designed this way will burst? Will an airplane's landing gear built this way collapse? What is the specific thrust of this rocket design? What is the gain of this transistor?

Designers and modelers of physical force systems often use the process model, predict, make decisions. Because a more complex model will give better predictions, a model of a physical force system is a MorePainMoreGainSolution. Such models are usually made as complex as needed to achieve some desired level of prediction.

Since most information flow systems (e.g. business units, software programs, armies, economies) are too complicated to predict, models and measurements of such systems are commonly used for human understanding.

Designers and modelers of information flow systems often use the process model, understand, make decisions. Because humans can handle only a limited amount of complexity, a model of an information flow system is a GoldilocksSolution. Such models balance a human's need for simplicity against the need for completeness and accuracy, to try to maximize human understanding.

Therefore

Be careful!. Because our technical training is influenced by four hundred years of modeling physical force systems, the former approach is more "natural" to us than the latter. Thus it is tempting to make a model of an information flow system ever more complex, in an often vain attempt to achieve a "predictive" ability.

If you can achieve such an ability, by all means do so. But if you can't, don't leave you model hanging. Back way up, throwing away completeness and accuracy, until you return to a model that will MaximizeHumanUnderstanding.

Examples

See Also

SpecializationSweetSpot WabiSabi ShortBooks


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