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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