Decision Modeling Analysis And Analysis - 1386 Words

Decision Modeling Analysis â€Å"Business these days is all in the numbers, as franchises tap into the power of big data to customize marketing, select locations and manage staffing. These are the companies leading the charge† (Daley, 2016, p. 133). This is how today’s world works. However, just simply collecting data is not enough. What do you do with it, and how do you turn it into something meaningful? Competition is fierce, and being wrong is never a good option. Using terms like I think, hopefully, and that is the way we have always done it, is a good first step to going out of business and the unemployment line. Using proper business analysis techniques with reliable data will increase the likelihood that a prediction, or a†¦show more content†¦Once a decision has been made (hopefully utilizing probability), the different outcomes can be displayed with their probability of occurring. For example, A business is wanting to develop a new product with the highest profit margin p ossible. The initial options are a cheap, midrange, or a high-quality product. Each has their own fixed material and labor cost. The first step in the decision tree is to determine the feasibility of making a profit at all. If after marketing samples are done and a low chance of success is determined, then the product should be abandoned during this first step. Otherwise, an option can be chosen. We will say that the mid-range product was chosen as the best option due to demand and cost. Next, it should be determined how well this product will sell, and how much product, or market share will be needed to be profitable, and by how much. Imputing this data into Excel or Precision tree can result in an expected monetary value which is the weighted average of all these choices (Albright, Winston, 2017). Distribution and Uncertainty. Distribution, as in probability distribution, take probability one step further. In the previous example of rain, there is only two possible outcomes. Either it will rain, or it won’t. Unfortunately, most decisions are not that simple. Sometimes there are several choices to make, and the cheapest one is not always the best option. Probability distribution doesn’t necessarily present aShow MoreRelatedSpeadsheet Modeling Decision Analysis 5e: Chapter 3 Solutions4520 Words   |  19 PagesChapter 3 Modeling Solving LP Problems In A Spreadsheet 1. In general, it does not matter what is placed in a variable (changing) cell. Ultimately, Solver will determine the optimal values for these cells. If the model builder places formulas in changing cells, Solver will replace the formulas with numeric constants representing the optimal values of the decision variables. An exception to this general principle is found in Chapter 8 where, when solving nonlinear programming problems, theRead MoreData Analysis Golf Course Design1491 Words   |  6 Pages2013 Decision Modeling Assignment: Golf Course Design CO 5124 Data Analysis Decision Modeling Tutorial : B By Madhumita Srinivasan (12772343) Submitted to Dr.Eddie Chng 1 |CO5124 DATA ANALYSIS DECISION MODELING INTRODUCTION Paradise Palm Golf Club, a well established golf club in Cairns, has planned to expand its operations by building a brand new golf course in Townsville. As the success of the golf course largely depends on the extent to which the users find it enjoyable, FutureRead MoreBusn312 Hw1A963 Words   |  4 PagesHomework 1a Multiple Choice Identify the choice that best completes the statement or answers the question. B 1. 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In sustainability science, a model has the ability to provide information that will lead to the best decis ions regarding the longevity of environmental systems and how to go about ensuring the sustainabilityRead MoreSystem Analysis and Design1287 Words   |  6 PagesSystem Analysis and Design Syllabus SYSTEM ANALYSIS AND DESIGN Module 1: Data and Information (3) Types of information: operational, tactical, strategic and statutory – why do we need information systems – management structure – requirements of information at different levels of management – functional allocation of management – requirements of information for various functions – qualities of information – small case study. Module 2: Systems Analysis and Design Life Cycle (3) Requirements determinationRead MorePredicting Preferences1636 Words   |  7 Pagesmathematical topic involving probabilistic modeling. Indeed, the mathematician Karl Pearson said in 1907 that the fundamental problem in statistics is prediction. Prediction, however, is usually not an end goal itself, but rather means to put probabilistic bounds on the relative frequency or likelihood of occurrence of future uncertain events so that strategies or actions can be taken incorporating these prediction s. Risk management needs predictive analysis, as does economic regulation, engineering