break-even point. Decision Analyst An individual who is responsible for problem
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break-even point. Decision Analyst An individual who is responsible for problem scenario or environe Probabilistic Model A model which assumes that some in developing a decision model. Decision Modeling A scientific approach that uses quantitative )techniques as a tool in managerial decision data are not known with certainty Problem Parameter A measurable quantity that is in making. Also known as quantitative analysis, in a problem. It typically has a fixed and known value a management science, and operations research relevant input data and parameters are known with certainty lem scenario is translated and expressed in terms of a a constant) Deterministic Model A model which assumes that all the Sensitivity Analysis A process that involves determ Formulation The process by which each aspect of a prob- of a problem. how seonsitive a solution is to changes in the formulation Variable A measurable quantity that may vary or that is sub- mathematical model. ject to change. Discussion Questions and Problems Discussion Questions 2-3 What are the differences between quantitative and qualita- tive factors that may be present in a decision model? 2-4 Why might it be difficult to quantify some qualitative 2-1 Define decision modeling. What are some of the organi- rations that support the use of the scientific approach? 2-2 What is the difference between deterministic and probabilistic models? Give several examples type of model. factors in developing decision models? of each 2-5 What steps are involved in the decision modeling process? Give several examples of this process.Explanation / Answer
2.1.
The Decision Model is an intellectual template for perceiving, organizing, and managing the business logic behind a business decision. An informal definition of business logic is it is a set of business rules represented as atomic elements of conditions leading to conclusions. A more formal definition of business logic is “a means by which a business derives a conclusion from facts.” So, business logic is a prescription for the way business experts want to evaluate facts in order to arrive at a conclusion where the conclusion has both meaning and value to the business. Therefore, a business decision is defined as a conclusion that a business arrives at through business logic and which the business is interested in managing.
Decision modeling is the scientific approach to managerial decision-making. This type of analysis is a logical and rational approach to making decisions. Emotions, guesswork, and whim are not part of the decision modeling approach. A number of academic and professional organizations support the use of the scientific approach: the Institute for Operation Research and Management Science (INFORMS), the Decision Sciences Institute (DSI), the Production and Operations Management Society (POMS), and the Academy of Management.
2.2.
Probabilism is an epistemic model, where as determinism is an ontic model. They address different things. One addresses what we can or cannot know about something, and the other addresses what exists.
Determinism just means every event has a cause (whether that be a local cause or a non-local cause as some deterministic models of quantum mechanics postulate). Probabilism means that we either don't have or can't have all of the information to assess the specifics of an event, so we have to assess a probability. For example, if we roll a die, we don't have all of the specifics of the way the die was flung, the weight of the die, the surface of the die and the surface of what the die lands on, the specific gravitational force, the air pressure, and so on, to figure out what it will causally land on. Our (lack of) knowledge means we can only assess a "probability" of a 1 in 6 chance for each number (probabilism) - even if causally it will land on a 4 (determinism).
In other words, probabilism doesn't necessarily imply that each of the options (1 through 6) are actually possible, only that our lack of knowledge of the only possibility (if deterministic) means we need to assign a probability (a range of likely outcomes).
It's important to point out that probabilism and determinism are not mutually exclusive. A system can be entirely deterministic, yet we might be able to only assess a probability for an event within the deterministic system.
2-3.
When you make business decisions as a manager, you take into account qualitative factors like reputations, brand strength and employee morale, as well as quantifiable data such as sales figures, profitability and return on investment. Both qualitative analysis and quantitative methods can be used to make decisions. The decisions that most often result in the desired outcomes use one method to check whether the predictions of the other method are reasonable.
While qualitative and quantitative analysis may use information about the same characteristic, qualitative methods rely on information that is not easily measurable while quantitative methods deal with data. For example, if you want to analyze how positively customers view one of your products, you might interview a cross-section of your customers and ask for feedback. This qualitative information is hard to express as numbers. Instead, you might analyze objective data such as how many customers buy the product again, how many make complaints, how many have warranty claims and how many return the product. You can express this quantitative information mathematically.
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