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MGS3100 Spreadsheet Modeling Chapter 2 Slides 2a: Introduction Models and Data • Useful (quantitative) models are developed based on relevant data (numbers); models without data are at best theoretical abstractions • Data are often collected according to the requirements of models – time series vs. cross-sectional – aggregated vs. disaggregated Numbers in Models • • • • Count Measure Rank Results • • • • Constant Variable Coefficient Precision Terminology and Relationships • Price • Volume – Sales volume – Production volume • Demand • Revenue • Profit • Cost – – – – – Overhead cost Sunk cost Fixed cost Variable cost Total cost • Breakeven point • Crossover point Basic Deterministic Models • Profit Model – Profit = Revenue - Total Cost – Profit = Price*Units - (FC + VC*units) • Break-even point – Profit = 0, or Revenue = Total Cost – Units = Fixed Cost/(Price - Var. Cost) • Crossover Point – Total Costa = Total Costb – Units = (FCa - FCb)/(VCb - VCa) Model Validation: Dimensional analysis • Multiplication : Apples x Apples = Apples2 • Division: Apples/Days = Apples/Days • Cancellation: (Apples/Day) x Days= Apples • Dissimilar addition: Apples + Oranges = Apples + Oranges • Similar addition: Apples + Apples = Apples • Congruity: Apples = Apples • Incongruity: Apples/Oranges2 Oranges Spreadsheet Modeling • Inputs should be logically grouped • Primary outputs should be easy to read • Input and output data should be labeled • Don’t embed parameters in a formula: use cell references • Use range names • Use fonts and color but don’t overuse them Sensitivity Analysis • The business world is a dynamic environment - stock market, interest rates, currency, oil prices, politicians! • How do changes in constants affect the model solution? • Look to both sides before you cross the business street! (upper and lower bounds) What-if Analysis • Decision variables are under the control of the manager • Testing different values will give the decision maker a sense of how they will affect the outcome • What happens if this value is changed? Graphical and Numerical Methods • Generate a range of possible changes • Input changes into the model and examine the outcome • If there are too many variables, use graphs What Next? • You have analyzed the process • You have determined the factors important to your situation • You have examined the relationships • You have represented the model in a usable form • You have checked for the sensitivity of the model Model Validation • Logical test – Are the assumptions realistic? – Do the model results reflect reality? – Obtain test data and “test drive” the model • Split the data (holdout sample) – Make model using one part – Test the validity using the other data set Intelligent Spreadsheet Use • Organization • Work smart, not hard • Design • Appearance Organization • Home screen should identify and describe the subject model • Inputs should be logically grouped • Primary outputs should be easy to read • Use tabs (new sheets) to group work • Model should be well documented Work Smart, Not Hard • Never embed a parameter in a formula always use a named cell (range) • Name a cells (ranges) that are referenced in other formulas • Use absolute references to avoid problems when moving cells • Use range names that anyone will understand Design • Clean and professional in appearance • Easy to use and understand • Keep a steady flow in your model • It must be accurate! Appearance • Use a spell checker! • Don’t overuse fonts and color • Don’t try to put too much on a page