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While the very process of constructing such a detailed model can often aid immeasurably in better understanding the syst


While the very process of constructing such a detailed model can often aid immeasurably in better understanding the syst
While the very process of constructing such a detailed model can often aid immeasurably in better understanding the system, the model may well be useless from an analytical perspective since its construction may be extremely time-consuming and its complexity precludes any meaningful analysis.
At the other extreme, one could build a less comprehensive model with a lot of simplifying assumptions so that it can be analyzed easily.
However, the danger here is that the model may be so lacking in accuracy that extrapolating results from the analysis back to the original system could cause serious errors.
Clearly, one must draw a line somewhere in the middle where the model is a sufficiently accurate representation of the original system, yet remains tractable.
Knowing where to draw such a line is precisely what determines a good modeler, and this is something that can only come with experience.
In the formal definition of a model that was given above, the key word is selective.Fassilia
United States. Alabama



day: 19.09.2018
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While the very process of constructing such a detailed model can often aid immeasurably in better understanding the syst

As an example, a marketing manager might cite historical production data or data from similar environments and tend to e
As an example, a marketing manager might cite historical production data or data from similar environments and tend to estimate resource availability in very optimistic terms.
On the other hand, a production planner might cite scrap rates or machine downtimes and come up with a much more conservative estimate of the same.
The final estimate would probably represent a compromise between the two that is acceptable to most team members.
There is no single correct way to build a model and as often noted, model-building is more an art than a science.
The key point to be kept in mind is that most often there is a natural trade-off between the accuracy of a model and its tractability.
At the one extreme, it may be possible to build a very comprehensive, detailed and exact model of the system at hand; this has the obviously desirable feature of being a highly realistic representation of the original system.Fassilia
United States. Alabama



day: 19.09.2018
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While the very process of constructing such a detailed model can often aid immeasurably in better understanding the syst

Data collection can have an important effect on the previous step of problem definition as well as on the following step
Data collection can have an important effect on the previous step of problem definition as well as on the following step of model formulation.
To relate data collection to our hypothetical production example, based upon variable costs of production and the selling price of each of the products, it might be determined that the profit from selling one gizmo is 10 and one widget is 9.
It might be determined based on time and work measurements that each gizmo and each widget respectively requires 7 10 unit and 1 unit of resource 1, 1 unit and 2 3 unit of resource 2 and 1 10 unit and 1 4 unit of resource 3.
Finally, based upon prior commitments and historical data on resource availability, it might be determined that in the next month there will be 630 units of resource 1, 708 units of resource 2 and 135 units of resource 3 available for use in producing the two products.
It should be emphasized that this is only a highly simplified illustrative example and the numbers here as well as the suggested data collection methods are also vastly simplified.
In practice, these types of numbers can often be very difficult to obtain exactly, and the final values are typically based on extensive analyses of the system and represent compromises that are agreeable to everyone on the project team.Fassilia
United States. Alabama



day: 19.09.2018
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has been the rapid growth in computer technology and the concurrent growth in information systems and automated data sto
has been the rapid growth in computer technology and the concurrent growth in information systems and automated data storage and retrieval.
This has been a great boon, in that O.
analysts now have ready access to data that was previously very hard to obtain.
Simultaneously, this has also made things difficult because many companies find themselves in the situation of being data-rich but information-poor.
In other words, even though the data is all present somewhere and in some form, extracting useful information from these sources is often very difficult.
This is one of the reasons why information systems specialists are invaluable to teams involved in any nontrivial O.Fassilia
United States. Alabama



day: 19.09.2018
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Continuing with our hypothetical illustration, the objective might be to maximize profits from the sales of the two prod
Continuing with our hypothetical illustration, the objective might be to maximize profits from the sales of the two products.
The alternative courses of action would be the quantities of each product to produce next month, and the alternatives might be constrained by the fact that the amounts of each of the three resources required to meet the planned production must not exceed the expected availability of these resources.
An assumption that might be made here is that all of the units produced can be sold.
Note that at this point the entire problem is stated in words ; later on the O.
approach will translate this into an analytical model.
One of the major driving forces behind the growth of O.Fassilia
United States. Alabama



day: 19.09.2018
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