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Management by Decision Models

Management of a company can be done with the help of mathematical computations and spreadsheets. Decision models are computer-based systems with quantifiable results that are used in making management decisions. Decision-making is a tedious process. It can take time to accomplish, with management weighing the pros and cons of future decisions.

There are several types of management and that include management by decision models. Most companies apply this management approach because they find it is an excellent aid in decision-making. While people can be subjective, measurable results are objective. Even if a person will have to make the decision, the decision is better because he has a more solid basis for it. Other feasible alternatives are also presented thus the choices are not limited to ‘yes’ or ‘no’ alone. And you have a choice to use between a basic model and a complex decision model.

What is Management by Decision Models?

When management by decision models is used, it means that the company is actually aiming for accurate decision-making. A company will often choose a project with the maximum value. The values are expressed in monetary form since this is the foremost concern of companies. Insight is also provided for other viable alternatives and how different they are from each other. Although the results are quantified, it may also be translated into words so they may be understood more.

Different problems or proposals call for different decision models. A company will generally not employ one type of decision model all the time. After identifying the problem, the next step is to gather all the data necessary. After that, the actual computing can begin. Once the results are gathered, it will be time to make a decision and then it will be put into action.

Why Do Decision Models Work?

Decision models work because of the fact that human beings are limited. A human being can be inconsistent and biased when it comes to decision-making. But if you incorporate figures and computations through computer spreadsheets, the data can be accurate and objective. These models work because complex problems are made simple by breaking them into small components. Quantitative analysis of data means the results can be measured. The decision that needs to be made is analyzed using figures and graphs.

To illustrate, let’s say there is a proposal to buy new equipment as a replacement for an old one. A decision model called cost-benefit analysis can be used to help decide whether it is better to purchase or not. Decision models are useful because they convert data to information, information to facts and finally to knowledge. This knowledge is relevant because this is used in management decision-making.

Types of Decision Models

Decision models can be classified as deterministic, probabilistic, static and dynamic. Static models ignore time periods while dynamic models characterize the progression in which changes occur. An example of a deterministic decision model is cost-benefit analysis, difference equations and linear programming. Cost-benefit analysis is basically quantifying costs and benefits to determine the feasibility of a proposal.

Deterministic decision models assume all relevant data known with certainty. Probabilistic decision models include decision trees and the Markov model. This type of decision model integrates uncertainties through probabilities. To make a deterministic analysis probabilistic, you can use the Monte Carlo analysis. The Monte Carlo simulation can yield more answers than the simple deterministic analysis. The results include graphical results, sensitivity analysis and scenario analysis.

The complex decision models are used when a project is considered a priority. The company would wish to analyze all aspects of the project since it pertains to an uncertain future. 

Importance of Decision Data

When the company has to decide about creating a new product or purchasing a new piece of machinery, it is important to have not only basic information but also all pertinent data. Good research is important to help you determine if there is a problem with the proposal.

Next, you cannot make a good decision if you do not consider all options. For instance, if you are going to get a new machine, you must know more than just the purchase price. You have to consider the life of the machine, the income you can generate monthly, depreciation cost per year, and salvage value.

Decision data is important because it is what you need to reach a decision. If there is no decision data, the manager will rely solely on his judgment. Quantifiable and measurable data helps in avoiding making subjective and erroneous decisions that can cause harm to the company.

Benefits of Decision Models

  • Decision models can produce better choices. Inconsistency, bias and error in human judgment can be reduced through the use of decision models. Choices are enhanced since the decision model also includes insights for other alternatives for the project or proposal.

  • It also improves the decision process because the rules for proposal evaluation are equal. There is no human judgment hampering the decision model computation. People only input the data but they cannot manipulate or change the outcome to make it go either way. It also serves as a medium to take action immediately rather than for decision makers to struggle and debate endlessly.

  • Allows “what if” analysis or it increases the decision’s defensibility. For example, sensitivity analysis can be a supplement in linear programming.

Application of Management by Decision Models

  • Statement of the Problem—There has to be a clear and correct understanding of the problem or decision that needs to be made. Identification of the wrong problem leads to wrong decisions in the end.

  • Identification of alternatives—Usually the decision to be made is on whether to proceed or not, to buy or not to buy. But there are times when there are also other feasible alternatives to be considered such as to trade-in equipment or have it repaired.

  • Evaluation of alternatives—In this step, the decision model can be applied. You can use simple cost-benefit analysis, simulation or linear programming.

  • Decision-making—Once the results have been studied and analyzed, a decision to accept or reject a proposal must be made. Or you can choose the most feasible alternative there is. It is important to decide or else the entire process would be useless.

  • Decision implementation—The decision loses its value if not implemented immediately.