Probabilistic methods

With this approach we generate information that enables us to handle projects more efficiently and transparently.

The less you know, the more you should use a method that can handle uncertainty.

The aim of forecasts is to depict the possible future (in risk management: in terms of dates and costs) as accurately as possible. However, forecasts are always subject to uncertainties.

The range of forecast uncertainty decreases as the project progresses and more detailed knowledge is obtained in the various project phases.

In everyday life, we are constantly confronted with uncertainties. For example, the weather forecast for the next 14 days. No one assumes that a meteorologist's forecast for Monday in two weeks is exactly right; in the far future, only a trend is foreseeable.

The same applies to cost and schedule forecasting in risk management.

Probabilistic methods are used for the analysis and control of construction projects (especially large projects), which provide more information about the individual cost and risk potential of the project. This approach generates information that enables projects to be executed more efficiently and transparently.

The result of a probabilistic risk analysis is a statement about the risk potential in arbitrary value units (e.g. euros or time). The advantage over deterministic standard methods is the significantly higher information content, since the result is a distribution function with underrun and overrun probabilities (value-at-risk information) that represents a range of risk potential (including best and worst case scenarios).

On this basis, the following questions can then be answered:

  • What percentage of the current cost potential is still covered by the remaining budget? Are there signs of a shortage or surplus?

  • What percentage of the current cost potential should be covered by the budget? How much remains deliberately uncovered?

  • How high is the risk potential compared to the basic costs?

  • Which elements are subject to the highest variation?