Opinion
Evgeni Kochman, Fabian Sempf y Michael Kruse adoptan un enfoque simplifi cado para la toma de decisiones basadas en el riesgo.
Evgeni Kochman, Fabian Sempf und Michael Kruse stellen eine vereinfachte Herangehensweise an die risikobasierte Entscheidungsfi ndung vor.
Beating the unknown
Evgeni Kochman, Fabian Sempf and Michael Kruse take a simplifi ed approach for risk-based decision-making.
T
hanks to the turbulent business environment, making decisions is
becoming both quicker and more complex. Nevertheless,
most decisions are made based on single- numeric metrics (e.g. net present value or internal rate of return). One reason for the widespread use of such metrics is that they off er simple calculations, but more importantly, decision-makers are familiar with them. T ey are able to understand the evaluation even with limited knowledge about the underlying assumptions. T e factor of uncertainty is usually included by adding lump-sum contingencies or calculating multiple scenarios using diff erent assumptions (e.g. sensitivity analyses). But even with risk-adjusted metrics, the possibility of neglecting huge upside and downside potential is still there. T is might crucially aff ect the fi nal decision, especially in changing and complex environments such as the energy sector. In this article a strong but pragmatic
approach to the assessment of risks associated with business decisions is presented. T e approach is illustrated using a real case example in which a business case for a large-scale power plant was developed.
PERT distribution functions provide adequate uncertainty models set up from three input variables.
Knowing the rules Of the vast number of underlying assumptions, which are the main risks
aff ecting the potential outcome? T ree broad categories of risks can be identifi ed that need to be dealt with in decision- making:
● Low-impact uncertainties are the large number of small, independent risks with relatively low impact on the business case (e.g. late deliveries and cost overruns).
● Non-negligible uncertainties involve manageable amounts of uncertainty with signifi cant impact and a realistic probability of occurrence. Often, these uncertainties are correlated additionally. An example would be a political election that infl uences the boundary conditions of the business case (e.g. regulations).
● Black swans/catastrophic events are surprising, rarely occurring events with major impact on the outcome of a scenario (e.g. a vapour cloud explosion or a plane crashing into the power plant).
T e focus of the assessment should be on non-negligible uncertainties. Experience shows that low-impact uncertainty can be covered by reasonably adding a contingency based on project management knowledge or historical data. Black swans ‘distort’ the business case and have to be treated separately from the assessment model (e.g. through expected maximum-loss calculations and transferring these to insurances).
Uncertainty drivers Non-negligible uncertainties represent the main uncertainty drivers and can therefore be crucial to the outcome of a business case. Emphasis on these factors can add certainty to the results and enhance the basis of the decision-making process – especially if complemented by ‘stress tests’ of the model through the assessment of major risks. One common example of a non- negligible uncertainty in the power plant business is the market price of
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