Sensitivity and Breakeven Analysis pptx

1 Chapter 8: Sensitivity and Breakeven Analysis Analyzing project risks by making mechanical trial and error changes to forecast values of selected variables. 2 Introduction • 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 zero. 3 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. 4 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 stage. Using Sensitivity: 5 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: 6 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. 7 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. 8 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. 9 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 launch commercial satellites. 10 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. [...]... 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% ? -20% 11 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... order of the monetary range of calculated NPVs • Management investigates the sensitive variables • More forecasting is done, or the project is accepted or rejected as is 12 Strengths and Weaknesses of Analysis • Easy to understand • • • • • • • • Forces planning discipline Helps to highlight risky variables Relatively cheap - - Relatively unsophisticated May not capture all information Limited . phase. 7 Terminology Within the Analysis • Sensitivity and Breakeven analyses are also known as: ‘scenario analysis , and ‘what-if analysis . • Point values. project is too risky, it is abandoned at this stage. Using Sensitivity: 5 Management Use of Sensitivity and Breakeven Analysis • (2) Ex post; in the