The Necessary Complexity of the Information Space Generated by EUFORIE

The complexity of both the social ecological systems and the concept of sustainable development (of which energy efficiency – how ever defined – is a subcomponent) require adopting a suite of non-equivalent and non-reducible analytical approaches. To give an analogy illustrating the problem, in medicine when dealing with the study of a complex concept such as “human health” it is impossible to adopt a single analytical framework that provides all the required in-formation in a comprehensive and coherent quantitative representation. For this reason, the practice of medicine relies on a suite of different approaches used to generate non-equivalent and non-reducible quantitative representations – e.g. blood tests, X-rays, NMR, psychological test – which send complementary but different messages about the health state, to some extent linked to each other although occasionally seemingly contradictory. That is, the strategy adopted by medicine is to generate a heterogeneous information space made-up of different typologies of required information. Within this logic, nobody would expect the development of an analytical device integrating the various types of information coming from these different methods of observation in the one quantitative output. Instead, procedures have been established requiring an integrated check of the different pieces of information coming from the different types of analysis. This is what EUFORIE delivers, both in the form of individual methods applied to the investigated cases and in the form of combined approaches enriching the knowledge of the investigated system by looking at it from different perspectives. For this be-half, EUFORIE used a suite of different approaches in quantitative performance analyses; some of these approaches were already tested in the two previous projects DECOIN and SMILE. They were used to study the sustainability of social-ecological systems in a set of different case studies in which the concept of efficiency (its definition and its implementation in terms of quantitative analysis) has been explored from different angles.

This simultaneous application of non-equivalent approaches generates a diversified set of results complementing each other in terms of relevant information generated. As an analysis based on X-rays cannot see soft tissues, an analysis based on the biophysical conversions of energy flows cannot see the social perception of values associated with these conversions. Nor can it understand the extent different material flows are involved, in addition to energy flows, and thus the overall environmental cost supporting the investigated system.

Another important lesson that can be learned from medical science is that trade-offs are una-voidable when trying to change the state of a complex adaptive system. For instance, a given treatment aimed at fixing a given health problem (associated with a given physiological process) may generate problems concerning different physiological processes observed at different scales. Thus, EUFORIE uses different narratives associated with distinct pre-analytical choices (the framings of the analyses) as the basis for organising the quantitative analyses. Such differ-ences in the pre-analytical choices result in differences in the selected methods of analysis. As a consequence, EUFORIE generates different types of data and indicators. However, this fact should be considered as a strength, not a weakness of the project: the existence of contradictions at the level of basic narratives reflects the need of adopting a diversity of perspectives to generate a comprehensive understanding of the system under investigation. This is achieved by reflecting the existence of non-equivalent dimensions and scales of analysis ─ protecting eco-logical processes does have an opportunity cost for the economy, and vice versa. Rather than pretending these trade-offs do not exist, it is important that scientists learn how to combine different definitions of pros and cons, different choices of dimensions and different scales of analysis. It is important to be aware that, in so doing, the analysis does not aim at disregarding one of the results in favour of others, but instead aims at providing a richer picture as the basis of a more realistic policies addressing the complexity of social-environmental systems.