Projects and programmes are, by definition, unique undertakings that include significant amounts of uncertainty. Techniques such as Monte Carlo address overall uncertainty using many inter-related variables and large amounts of data.

However, it can sometimes be useful to home in on the effect of individual variables to understand their potential impact.

For example: if a UK company were evaluating a project to build a factory in Eastern Europe there may be several areas of uncertainty, including currency fluctuations, raw material inflation and interest rates.

The simplest form of sensitivity analysis would look at each factor in turn and analyse the project based on upper and lower estimates. An analysis is based on cost would end up with variances in overall project cost in relation to each variable.

The results of this type of sensitivity analysis are often represented as a tornado chart.

The response to this may be to reduce uncertainty by concentrating on fixed price contracts for material supply and make arrangements to hedge the effects of currency fluctuations. Much of this depends upon the risk context of the project or programme and the host organisation.