Sensitivity and Breakeven Analysis pptx

Chapter 8: Sensitivity and Breakeven Analysis Analyzing project risks by making mechanical trial and error changes to forecast... • Finding the values of particular variables which gi

Chapter 8: Sensitivity and

Breakeven Analysis

Analyzing project risks by

making mechanical trial and

error changes to forecast

• Analyzing the risks of investment projects, by

changing the values of forecasted variables.

• Finding the values of particular variables

which give the project a Breakeven NPV of

Process of Analysis

• Identification of those variables which will

have significant impacts on the NPV, if their

future values vary around the forecast values.

• The variables having significant impacts on the

NPV are known as ‘sensitive variables’.

• The variables are ranked in the order of their

monetary impact on the NPV.

• The most sensitive variables are further

investigated by management.

Management Use of Sensitivity and

Breakeven Analysis

Sensitive variables are investigated and

managed in two ways:

• (1) Ex ante; in the planning phase; more

effort is used to create better forecasts of future values If management decides the project is too risky, it is abandoned at this

Using Sensitivity:

Management Use of Sensitivity and

Breakeven Analysis

• (2) Ex post; in the project execution phase;

management monitors the forecasted values If the project is performing poorly, it is

abandoned or sold off prior to its planned

termination.

Using Sensitivity:

Sensitive variables are investigated and

managed in two ways:

Management Use of Sensitivity and Breakeven Analysis

Using Breakeven:

• Forecasted calculated Breakeven values of

variables are continuously compared against

actual outcomes during the execution phase.

Terminology Within the Analysis

• Sensitivity and Breakeven analyses are also known as:

‘scenario analysis’, and ‘what-if analysis’.

• Point values of forecasts are known as: ‘optimistic’,

‘most likely’, and ‘pessimistic’.

• Respective calculated NPVs are known as: ‘best case’,

‘base case’ and ‘worst case’.

• Variables giving a ‘breakeven’ value, return an NPV of

zero for the project.

Selection Criteria For Variables

in the Analysis

• Degree of management control.

• Management's confidence in the forecasts.

• Amount of management experience in assessing

projects.

• Extrinsic variables more problematic than

intrinsic variables.

• Time and cost of analysis.

Real Life Examples

of Forecast Errors

• Large blowouts in initial construction

costs for Sydney Opera House,

Montreal Olympic Stadium.

• Big budget films are shunned by critics

and public alike; e.g ‘Waterworld’:

whilst cheap films become classics;

eg.‘Easy Rider’.

• High failure rate of rockets used to

Developing Optimistic and

Pessimistic Forecasts

• (a) Use forecasting –error information from the

forecasting methods: eg - upper and lower

bounds; prediction interval; expert opinion;

physical constraints, are applied to the

variables.

This method is formalized, but arguable, slow and expensive.

Developing Optimistic and

Pessimistic Forecasts

• (b) Use ad hoc percentage changes: a fixed

percentage, such as 20%,or 30%, is added to and subtracted from the most likely forecast value.

This method is vague and informal, but

fast, popular, and cheap.

+20%

Outputs and Uses

• Each forecast value is entered into the

model,and one solution is given.

• Solutions can be summarized automatically, or

individually by hand.

• Variables are ranked in order of the monetary

range of calculated NPVs

• Management investigates the sensitive

variables.

• More forecasting is done, or the project is

Strengths and Weaknesses of

Analysis

• - - -

• Relatively unsophisticated.

• May not capture all information.

• Limited to one variable at a time.