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The following article was written by Coleman Patterson and appeared in the Business section of the Abilene Reporter-News.

‘Modeling’ for the organization can be good, September 22, 2D.

If you were to receive word that one of your coworkers has begun “modeling” for your organization, you might be shocked.  The fact is that organizations that support and practice modeling can operate more efficiently than those that do not and in the process, save precious organizational resources.  The modeling described here is not the type that involves hairspray, nice clothes, and looking good in front of a camera.  Rather, it is the type of modeling that management science practitioners use to solve complex organizational problems.

For example, suppose that your company produces three types of products.  Each product yields different amounts of profit on each item sold.  Additionally, each product incurs different production costs and requires different combinations of human and manufacturing inputs.  Also, assume that there are different limits on the quantities of each of the three products that can be produced due to different budget, raw materials, labor, and/or production-capacity constraints.  The question of “how many of each of the three types of products should the company produce to maximize profit?” ultimately arises.

Managers who regularly encounter these types of problems have a well-defined body of tools and techniques at their disposal to solve such problems.  The field of Management Science is the area of business that works with and develops solutions to these types of problems.  Also known as quantitative business analysis or decision systems, these tools and techniques can be used to solve a wide variety of complex organizational problems.  The term “modeling” refers to developing accurate representations of organizational problems and decisions using mathematical expressions and controls. 

Variations of the linear programming method used to solve the “product blend” problem described above can also be used to assign workers (with different abilities, credentials, and costs) to work shifts with differing personnel and staffing requirements, minimize shipping costs for products transported from factories and warehouses to distribution outlets, and determine the lowest-cost combinations of raw ingredients that meet minimum or maximum ingredient requirements.  Other quantitative modeling techniques can be used to develop forecasting and “what if” scenarios for a variety of complex and important business decisions.

These tools are used when problems are complex, when solutions are not readily apparent, when there is sufficient time to create and run the models, and when the solutions can provide significant payoffs to organizations.  The management science field is replete with examples of large-scale organizations saving millions of dollars in costs as a result of employing and implementing management science techniques and solutions.

Once for use only by people with advanced mathematical skills and those with access to supercomputers, many of these modeling techniques can now be run on personal computers using Microsoft Excel.  Business owners and managers should investigate how these techniques could help make their operations more efficient and profitable—the benefits they might reap could far outweigh the costs of learning, mastering, and using these techniques.

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