In ecology, as with other sciences, it is useful to attempt to build mathematical models of the real world. One can start with very simplistic models, compare them with real life stats and see how closely they comply with results in the real world then refine the model to more closely reflect results observed in the real world. The mathematical model after several rounds of refinement still does not have to be perfect and does not have to provide us with the ability to create a perfect simulation of the real world yet is still useful in making us understand the dynamics of the real world and grasp a great part of its complexity. It can also help in prediction and to some extent in control.
Similarly, in the business world, even if it was not possible to create perfect models of the economy and the markets in which businesses are working, it is still useful to attempt to create mathematical models for them that reflect the real world dynamics of businesses as closely as possible and as much as the data available would allow. Such mathematical models can be used for decision making and help one understand the economy and dynamics of the business world much better thus aiding in effective decision making once again.
Similarly, in the business world, even if it was not possible to create perfect models of the economy and the markets in which businesses are working, it is still useful to attempt to create mathematical models for them that reflect the real world dynamics of businesses as closely as possible and as much as the data available would allow. Such mathematical models can be used for decision making and help one understand the economy and dynamics of the business world much better thus aiding in effective decision making once again.
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