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A model is a copy of a system, thing, or thought used as a stand-in to the real thing that enables the researcher to manipulate it in order to make decisions. The model needs to represent the salient parts of a question and demonstrate them in the simplest way to make it easier for the researcher to make interpretations. Models can vary in complexity, from rudimentary images to tables of data, or mathematical equations researchers use decision models to understand, analyze, or facilitate making a decision (Evans, 2013, 272). The complexity of the decision model is based on the necessary variables that the researcher needs to incorporate into the model in order to make the best decision. For instance, if you have only two variables, the decision model will be quite simple making it easier for the manager to make a decision. Whereas if you have multiple variables, the model will be large, which makes it very important to have valuable data in order to make sure that your model is not producing garbage. As we have discussed throughout this course, a manager must use data to make informed business decisions. If this does not take place then a manager makes a decision in the dark. An informed decision is one that is based on reliable data, especially when it is plugged into a well-developed decision model that incorporates the correct variables. According to Evans, there are three types of inputs that make up a decision model (Evans, 2013, 272). The first is data the main point that is made about data is that the manager assumes the data to be constant and not fluctuate while being used in the model. An example of data would be price, manufacturing times, warehouse storage capacity, etc. The second input is the uncontrollable variable. An uncontrollable variable is one that the manager cannot influence or control such as market fluctuations, natural disasters, customer frequency, or returns on investment. The third input type is decision variables these are variables that the manager can control and manipulate, such as manufacturing levels, the number of employees, how much goods to store, and what investments the company will make. All of these elements must be accounted for in a decision model. The manager can incorporate as many or as few as desired, but the inputs should always be relevant to the particular problem that the manager is trying to solve, or the decision to be made.