Decision support methodologies in public policy formulation : ERSA 54th Congress : Regional development & globalisation: best practices : Saint Petersburg, Russia, 26-29 August 2014

A decision problem is relatively complex and broadly involves two distinct moments, i) information gathering and ii) use of available information and decision-making. In the first case one can discuss the potential of rigorous methods (statistical analysis and modelling) commonly used to enable and improve the collection, analysis and interpretation of the most relevant data. On the second case it is important to note that the existing information may not be enough, it is not always possible to combine and organize (objective and subjective) information and that decisions are highly subject to contexts of high uncertainty. This paper develops this issue focusing on the regional and local development decision-making process, acknowledging the need to complement objective information based on statistical data and modelling with unstructured and non-rigorous rule of thumb information and opinions generated by experts. In the specific context of regional and local public policies it is reasonable to assume that there is a considerable body of information disseminated by different actors and experts, although distributed in a fragmented and asymmetric manner. This information is insufficient to support the decision-making process when used individually, but can provide better results if experts obtain synergies through an interactive process. Simultaneously their decisions are conditioned by the evolution of exogenous variables that they cannot predict. If, on the one hand, the application of formal models (supported on quantitative data) may be unsatisfactory because they are conditioned by the available information, and are not able to include subjective (but technically) informed knowledge, nor the volatility and uncertainty of the future, on the other hand, the application of more informal methods (based, for example, in scenario analysis or expert panels) may lead to biased results, as a consequence of opinions being strongly influenced by individual preferences and perceptions. This paper is based on the assumption that public decision-making needs to be more i) transparent, as it demands prioritization, budgeting and resource allocation; ii) accountable, as it involves alternative choices; iii) participated, as it requires the combination of formal and informal relationships between different agents and iv) future oriented, as it supports strategic approaches. Therefore it presents and discusses a methodological framework that combines technically informed subjectivity with more rigorous models. In other words, it explores the combination of several decision-making methods, such as foresight techniques, multi-criteria and cost-benefit approaches.