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Business Software Tools 200. Topic 2 Modelling. Why Model?. Why Model?. Focus on key aspects Perform “What if?” (sensitivity analysis) Make predictions Improve (shared) understanding Reduce uncertainty Solve problems…. Good models. Are parsimonious

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Business software tools 200

Business Software Tools 200

Topic 2 Modelling



Why model1
Why Model?

  • Focus on key aspects

  • Perform “What if?” (sensitivity analysis)

  • Make predictions

  • Improve (shared) understanding

  • Reduce uncertainty

  • Solve problems…


Good models
Good models

  • Are parsimonious

    • Have just enough variables to explain the variation

    • Too many variables create complexity and confusion and may mislead (model is overfitted)

    • Too few variables don’t explain (model is underfitted)


Good models ctd
Good models ctd.

  • Provide explanation

  • Give accurate predictions

  • Correlate with the “real world”

    • Have face validity

  • Are scalable, extensible

  • Understandable by others

    • documentation


Modelling
Modelling

  • financial

  • forecasting

  • simulation/risk analysis

  • MCDM (multi criteria decision making)

  • goal seeking/optimisation/linear programming


Excel add ins
Excel Add-Ins

  • Analysis ToolPak

  • Solver



Financial models
Financial models

  • “adjusting for the time value of money based on interest, depreciation, inflation rates”

  • NPV (net present value)

  • IRR (internal rate of return)

  • DCF (discounted cash flow)

  • Amortisation (loan repayments)


Financial models1
Financial models

  • Software

    • Excel financial functions


Forecasting
Forecasting

  • “predicting future values based on past patterns of a time series”

  • trend

  • regression

  • exponential smoothing

  • decomposition

  • Box Jenkins


Forecasting1
Forecasting

  • Software

    • Excel statistical functions


Simulation risk analysis
Simulation/Risk Analysis

  • “either the modelling of a process or a form of sensitivity analysis where many “what ifs” are performed”

  • Systems Dynamics

    • dynamic

    • based on store/flow/control

    • difference equations


Simulation risk analysis1
Simulation/Risk Analysis

  • Monte Carlo

    • variation of given variables according to an assumed statistical pattern

    • static

  • Example software

    • @Risk by Palisade

    • Works with Excel

    • http://www.palisade.com.au/risk/


Simulation risk analysis2
Simulation/Risk Analysis

  • discrete

    • snapshot of model is triggered by an event

  • continuous

    • snapshot of model is triggered at regular time intervals

  • visual

    • interface

    • iconic

      • abstract .... real


Regression
Regression

  • statistical model

  • dependent, independent variables

  • may be time based

  • software

    • See excel statistical functions and

    • Data analysis toolpack add-in



Mcdm multi criteria decision making
MCDM (multi criteria decision making)

  • “exploration of the pain and gain associated with different alternatives”

  • alternatives

  • criteria

  • rating of alternatives

  • weighting of criteria

  • exploration


Mcdm ctd
MCDM ctd

  • Software

    • Hiview3 by Catalyze

  • http://www.catalyze.co.uk/resources/docs/pdf/Catalyze_Case_Study_Shampoo.pdf

  • See next slide copied from the above pdf



Goal seeking optimisation linear programming
Goal Seeking/Optimisation/Linear Programming

  • “either the search for the pattern of variables that will lead to a goal or the pattern of variables that will optimise a goal under given constraints”

  • Software

    • Goal seek (in Excel “What if Analysis”)

    • Excel Add In – Solver (optimisation under constraints)


Goal seek e g find a break even point
Goal seek – E.g. Find a Break even point

New Perspectives on Microsoft Office Excel 2007


Working with what if analysis and goal seek
Working with What-If Analysis and Goal Seek

New Perspectives on Microsoft Office Excel 2007



Sensitivity analysis what if
Sensitivity Analysis (“What if”)

  • “The performing of “what if” analysis in a given model through varying underlying variables”

  • fixed values

  • interval/increments

  • according to a statistical pattern




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