Chapter 1: Using Sensitivity Analysis

9 Topics | 1 Assessment Test
Chapter 2: Forecasting Structures

8 Topics
Chapter 3: Modelling Excercise And Assessment Test: Forecasting Calculations (I)

1 Topic | 1 Assessment Test
This Chapter has introduced sensitivity analysis, with a focus on:

- Its use as a thought-process in model design, as well as in model testing and decision support.
- The running of sensitivities using manual methods, which is especially when testing a model as it is being built.
- The use of DataTables to automate sensitivity analysis.
- Using GoalSeek or reverse-sensitivities.

In fact, there are some related topics which are used in more advanced or specialised contexts. These include:

- Scenario modelling.
- Uncertainty and risk modelling.
- Optimisation modelling.
- Running sensitivities in non-dynamic models.

The topic of scenario modelling is a direct extension of sensitivity analysis, and so is covered in Level II courses. The other topics within the above list are treated in other later courses.

In fact, it is worth noting that – from the perspective of creating models which reflect the real-life situation – the topics of uncertainty, risk and optimisation could be considered as “basic”, or at least “fundamental”. For example, in real-life situations:

- Some aspects may be uncertain or subject to risk (e.g. input costs, prices achieved, volumes sold, exchange rates, and so on).
- Some aspects may be decisions i.e. are controllable (e.g. list prices for products to sell, how many staff to hire, etc.)
- Some (controllable) decisions may depend on the outcome of a risky or uncertain process, and therefore involve both of the above (e.g. if the flight is cancelled, we will take the train, or if the volume sold is too low, we will reduce the list price).

Therefore, to “model reality”, it could be argued that one should include risks, uncertainties and possible (optimal) responses into any models that are built. On the other hand, to do so would often require the use of concepts and techniques that are advanced or specialised (such as statistics, VBA macros, simulation techniques, optimisation algorithms, add-ins or additional software, and so on). For this reason, these topics are covered in detail in later courses (especially within the context of the discussion of VBA macros).

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