Options Analysis

The term “options analysis” includes analytical methods that serve to systematically compare options for action. Options analysis is used, for instance, in regulatory impact assessments or in the valuation of investments. In a systematic comparison, options for action are evaluated for their effectiveness, associated costs and, for instance, also unintended consequences. Options analysis therefore raises the transparency and quality of decision-making processes.

For the systematic execution of an options analysis, methods are available that are based on quantitative information, i.e. on volume or monetary units as well as qualitative information, i.e. purely subjective information. The following focus points, amongst others, of the options analysis are possible:

  • Cost-benefit analysis

If the concrete monetary value of the costs and benefits of certain reform alternatives is known, options can be compared on the basis of a cost-benefit analysis. The question can therefore be answered as to which processes will lead to greater benefits at the same or lower costs.

  • Cost-effectiveness analysis

For reform alternatives where it is difficult to assess all the aspects in monetary terms, a cost-effectiveness analysis can be carried out. In this type of analysis, monetary values are combined with volumes and used to answer the question as to which alternative has the lowest cost per benefit unit.

  • Multi-criteria analysis

If the underlying data consists of qualitative information or a mix of quantitative and qualitative information a multi-criteria analysis can be carried out, which makes it possible to systematically compare alternatives using different qualitative criteria such as, for instance, the degree of support for an intended reform in the population, the probability of implementation, etc.

  • Cost-utility analysis

In the cost-utility analysis, quantitative information is compared using an assessment scale (also called “scoring”). In the context of the cost-utility analysis, qualitative information is systematically compared using a scale. The scales can range from “very high effect” through to “no or unknown effect” or “very negative effect” or from 0 to 10 or similar. The individual values can also be weighted. Scoring can be combined with a multi-criteria analysis.