# Quantitative Analysis for Business Decisions Research Paper Starter

## Quantitative Analysis for Business Decisions

Managers are frequently faced with complex decisions that need to be made. These decisions often have far-reaching impact on the profitability of the organization as well as the decision maker's career. Therefore, it is essential that the decision maker be given the best information available to aid in the process. A range of quantitative techniques are available for helping the decision maker in this task. Mathematical or computer models can help quantify the variables in the situation under consideration as well as the probabilities of the various outcomes. Model building tends to be an iterative process in the search to develop a model that realistically represents the real world situation. Quantitative analysis is only part of the equation, however. The decision maker must also use his/her expertise and experience in interpreting the results of the analysis. In addition, the worth of the decision aid depends on a number of factors both controllable and uncontrollable.

Every day, business managers are required to make decisions that can affect their organization, their industry, and their careers. Sometimes these decisions are sound and aid the parties affected. Sometimes, however, these decisions are not sound and embarrass or harm the parties involved. Brown cites several examples of business decisions gone awry. For example, a \$4 million probabilistic risk assessment of a nuclear reactor indicated that the facility was safe. However, inspection by a regulator indicated the opposite and the facility was put on a watch list. The results of a transportation study led a vehicle manufacturer to close three parts depots. It soon became evident, however, that the remaining depots could not handle the demand for parts and the three depots had to be reopened. On the other hand, an award-winning decision analysis indicated three nuclear waste sites should be studied further by the Department of Energy. The Secretary ignored the analysis and picked three other sites for study and was widely criticized for his efforts.

### Complex Nature of Real-World Business Decisions

These examples illustrate that the decisions that managers need to make often not only have far-reaching effects but can be quite complicated. As opposed to the problems in the back of a textbook, real-world problems are typically very complex and require the consideration of multiple variables, some of which may not seem important to the casual observer and some of which might even be unknown. Even when the variables are known, their values may not be known and multiple possible inputs need to be considered. In addition, the answers to real world problems are typically not black and white; there are many possible answers and frequently none of them is perfect. The decision maker must pick and choose among them in order to optimize the effectiveness of the alternative chosen. One of the objectives of quantitative analysis is to give decision makers tools to support them in this process. There are several disciplines that approach decision making using quantitative tools and techniques, including operations research, decision analysis, and mathematical modeling.

Part of the reason that business decisions can be so complex is that the organization does not act in isolation: it is affected by both internal and external factors. To make an effective decision, the decision maker needs to take all these factors into account. Business theorists refer to this approach as systems theory. This approach assumes that the organization comprises multiple subsystems and that the functioning of each affects both the functioning of the others as well as of the organization as a whole. In addition, the organization itself is part of a larger system whose component parts (e.g., the total economy, the political environment, the supply chain) affect it. As part of this greater system, the organization depends on inputs of raw materials, human resources, and capital in order to do its work as well as exports of goods or services, employee behavior, and capital to other parts of the system.

### Decision Theory

In general, decision theory is a body of knowledge and related analytical techniques designed to give the decision maker information about a situation or system and the consequences of alternative actions in order to help him/her choose among the set of alternatives. One of the primary tools of decision making is model building. The basis of much quantitative analysis work in support of decision making involves the development of models. Models are representations of a situation, system, or subsystem. Conceptual models are mental images that describe the situation or system. Conceptual models are the first step in creating mathematical or computer models that represent the situation or system using one or a series of mathematical equations. The development of a model that accurately represents the situation or system is often an iterative process. Models typically must be tested and refined until they represent the real world to the degree desired by the analyst or decision maker. Initial conceptual models tend to be broad or general representations without much detail but which span the range of variables to be considered. The initial model helps the analyst better understand the situation or system under consideration and to refine the representation of the real world. As the model is analyzed and more information about the situation or system is known and understood, the model can be refined to better reflect the underlying reality. When enough information is known, data can be gathered and quantitative techniques used to turn the conceptual model into a mathematical model.

The use of models is particularly helpful for making business decisions in complex situations that cannot be solved intuitively. Models create a representation that the decision maker can examine and manipulate to include relevant variables and relationships in the decision making process. However, a model needs to be validated at each step to determine how well it reflects the real world situation. It can be consequently adjusted as necessary and revalidated in order to optimize its use in decision making. After a satisfactory, validated model has been developed, a decision can be made and implemented. This process is illustrated in Figure 1.