Ranking Local Sustainability Performances by Data Normalization : An examination of Finnish local authorities

Sustainable development is a large entity, that as a concept, is still ambiguous and unclear. Since the Brundtland report in 1987, sustainable development has slowly stared to increase its significance in day-to-day activities, where the ongoing UN’s international Agenda 2030 aims yet to increase the progress towards sustainable development across the globe. Sustainable development includes multidimensional economic, environmental and social aspects, where challenges facing sustainability within its dimensions are different in different regions. The ambiguity related to sustainable development lies in its complexity, where measuring progress demands clear and legible applications to ensure the accurate interpretation and communication of the measures. There are many ways to measure sustainable development, and as it is such an immense subject, the transparent procedure behind any sustainable assessment is underlined. This study is a local-level sustainable development performance analysis, that is conducted of all the Finnish local authorities. Sustainability performances are derived as sustainable development scores and ranking positions for each considered local authority via a dataset of 59 indicators. The indicators are aligned with the Agenda 2030 17 SDGs – the sustainability performance assessment is based on indicator data normalization, where normalized indicator data is aggregated to the appointed SDG, and furthermore as the overall sustainable development scores for each local authority. The sustainable development ranks are then derived from the score values as a data arrangement application. Being a data-based examination, data-related characteristics are invoked in this study by computing the sustainable development performance numbers of all the Finnish local authorities four times: once with the original dataset, and three times by applying weights to the data; considering indicator-specific data coverage by the share of population included, indicator-specific coverage by local authority data availability and lastly SDG-specific coverage by the number of indicators aligned. The results after all the four sustainability performance applications show that Kuopio scores the best of all the Finnish local authorities every time. On the contrary, Koski Tl gets the worst performance, also for all the four performance applications. Otherwise, there are movements in ranking positions and sustainable development scores comparing the weighting applications with the non-weighted outcomes. When reviewing the top 10 and bottom 5 local authorities, municipalities of Åland; Jomala, Lemland and Lumparland, for instance improve their performances significantly when applying the weights to indicator coverage by local authority data availability. What can be deduced from this analysis, is that this sustainability performance assessment application is one way of measuring local sustainable development. The outcome of this data-based analysis is dependent on the indicators in use, and the applied minimum-maximum normalization method used in the aggregation process. This study provides an example of a local-level sustainability performance application, that may be utilized and further continued, acknowledging all the variable components, causal relations and data-related challenges that inevitably are present in such assessments. Such aggregated sustainability indicators’ analyses are prone to challenges related to data, where the intent for the given application vary case-by-case and should therefore also be assessed regarding the intended use