The project FokoKEM explored how public procurement in small municipalities can be assessed and optimized to reduce greenhouse gas emissions. At the heart of the project was the idea that procurement decisions, though often seen as purely administrative, play a key role in shaping a municipality’s ecological footprint.
The research was based on real-world procurement data provided by two municipalities in the Klima- und Energie-Modellregion (KEM) Carnica Rosental. The project brought together an interdisciplinary team: Michael Hilpert from the KEM region, Renate Hübner from the Department of Educational Science at the University of Klagenfurt, Michael Has from the Institut d’Ingénierie et de Management in Grenoble, and a researcher team led by Wilfried Elmenreich from the Institute of Networked and Embedded Systems (NES) at the University of Klagenfurt, consisting of Anja Adamitsch and Stefan Hohnwald.
By combining technical tools and sustainability perspectives, the project aimed to uncover both the climate impact of municipal procurement and opportunities for improvement, grounded in data and tailored to the regional context.
Before the actual analysis could begin, the procurement data had to be made usable. The two municipalities provided Excel tables containing information on purchases over several years. As is often the case with real-world administrative data, these tables were not standardized: item descriptions varied, quantities were missing, and multiple products were sometimes listed in a single row.
To address this, the research team developed a Python-based tool that automatically grouped similar products, corrected inconsistencies, and filtered out entries that were too vague or incomplete to analyze. In a key step, all items were also categorized as either durable goods (e.g. tools, lighting, water meters) or non-durable goods (e.g. cleaning supplies, consumables). This distinction was essential for later analysis, as the environmental impact of these two groups differs not only in volume, but also in usage patterns and replacement frequency.
The resulting cleaned and structured dataset provided a reliable foundation for assessing the financial and ecological effects of procurement decisions, separately for both product types.
With the structured data in place, the team used two well-established analysis techniques, ABC and XYZ, to uncover patterns in procurement behavior and environmental impact.
ABC analysis was performed twice: once to rank products by total CO₂ emissions, and once by expenditure. This allowed the team to compare financial and environmental relevance side by side. Particularly important were products with high CO₂ emissions but low cost, which are often overlooked in budget discussions. Items like trash bags, disinfectants, and heating oil turned out to be major contributors to the carbon footprint, despite accounting for only a small portion of spending.
Among the durable goods, items such as LED lighting, vehicle tires, and water meters stood out due to their material intensity and associated emissions. These goods are purchased less frequently but have a lasting environmental impact.
The XYZ analysis revealed how regularly each item was procured. Frequently purchased products, like gravel, cleaning supplies, or de-icing salt, were flagged as especially relevant, as even small changes in their procurement could quickly add up to a noticeable reduction in emissions.
To visualize the results, the team created a series of heatmaps combining both ABC and XYZ categories. These visual tools helped identify products that were not only climate-relevant but also part of regular procurement routines, providing municipalities with practical and effective starting points for more sustainable purchasing strategies.