Quantitative decision analysis is the use of mathematical models to find answers to business problems. This analysis is quite common in business, with many companies hiring individuals to complete this specific activity. A few types of quantitative decision analysis are deterministic, stochastic, or probabilistic models. Their purpose is to use uncontrollable factors and controllable inputs to make decisions. Uncontrollable factors typically represent external items outside the company’s control, while controllable inputs are those items a company uses to produce goods and services.
Deterministic models work best when a business knows a relationship exists between two variables. For example, product price and total sales typically have a direct relationship. Therefore, a company can create a mathematical model to determine how one of these variables affects the other. Quantitative decision analysis offers many types of deterministic models for use in this process. One essential point for deterministic models is the inability for random variation to exist as variables must have direct relationships with each other.
Stochastic models are the opposite of deterministic models in quantitative decision analysis. Companies can use these models when a range of variables exists in a problem or situation. In most cases, the variables can each have their own individual value ranges. Going back to the price and sales example, a company may input a wide range of prices in order to determine their effects on overall sales. This model can take these multiple inputs and provide a variety of outputs when making decisions.
Probability models are a stochastic mathematical form. Companies typically use probability to determine the number of outcomes or possible events that will result from a single course of action. Decision trees are a form of a probability model in this quantitative decision analysis. A company outlines a certain event and defines the probability of success based on the variables that exist. Attaching percentages to the different outcomes provides more support for the decision outcome with these models.
Though a few basic models exist in quantitative decision analysis, there is no end to the number of variations to them. That is why so many businesses find this analysis activity so valuable. Altering a formula slightly allows a company to change the model to fit the situation. The use of these models allows for better decision making and often improves the end result. Qualitative analysis, however, may also be necessary to determine how nonmathematical factors will affect a decision outcome.