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Modelling decisions help companies to judge correctly regarding issues that involve both quick decisions and long term decisions. Bechtel is an electrical company that has several business units including civil infrastructure, communication and transmission, mining, metal, oil, gas, chemical, power, and US Government services.
Each of these units has their own responsibilities and production that generates income to the company. Some of the problems the company is presumed to have included issues to do with optimization of their sales of goods and services and reducing their cost of production.
Computer models can easily be used to help make decision towards achieving a low cost of production and maximizing on income. The option of pricing can also be solved by coming up with a comprehensive model. With these models in place, Bechtel will definitely increase their overall revenue. Besides the pricing and timing optimization models, the worker scheduling model will increases the companys overall output in terms of labour force which reflects in the overall revenue achieved by the company.
Building this models only require a computer that has spreadsheets. The spreadsheets have mathematical functions that can help to work out and solve the problem mathematically. By doing so, the company is able to identify alternatives for basing decisions. Modelling makes it less costly for the company to analyse some of the decisions made and deliver any necessary information needed quicker as it is easier to trace the source of information from the models.
Making these decisions in the company is essential because it saves on the limited resources especially the metals that the company mines to make equipments for sale. Mathematical programming that helps in optimization is critical for ensuring production of maximum product mix, optimization of the manufacturing of the product
Every function in the mathematical programming model is linear and therefore uses linear programming concepts. The model identifies the maximum or best value for the production of the units that the company sells. There are steps that formulate a good model for optimization of the output.
It begins with understanding the problem. For instance there could be a problem in the civil infrastructure unit of the company. Drafting a linear programming model can help identify where the problem arises from. It can help notice a short fall in either the time or cost used to produce a unit of these tools. The second thing to do is to identify the variable that needs to be decided on. It could be the telecommunication infrastructure.
Thirdly there is need for coming up with the objective function and express it as a linear combination of the decision variables. The objective function could to find the maximum value produced by single units of the companys products. The next step is to write down each constraint that is possible and expressing them as linear combination of the variables.
These constraints might include the time spent on labour for each unit of the decision variable and the total number of units per day that is produced. The final step is to identify upper bounds and lower bounds of each unit. The constraint helps in defining the feasible region in which the variables are viable. Once the graphs are drawn, of all these constraints, the highest point in the feasible region will give the best position.
By making the best decisions, a business no matter how small will grow. This also helps to increase the revenue of the business unlike bad decision that adds up to the problem. Solving problems in business is possible by using models for problem solving.
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