To maximize the returns on a real estate investment, it is essential that property owners intelligently manage all the variables that could negatively impact the long-term value of the asset. Occupancy costs have historically represented a large percent of what is spent over the lifetime of a real estate investment. Therefore, to maximize the returns on their investment, it is important that property owners, first, make a cost benefit analysis of various options, and second, reduce the occupancy costs associated with the chosen option by either eliminating or better managing the underlying drivers. This study is addressed to facilitate the decisions made around the second point by gaining a better understanding of the causal relationships between identified drivers and occupancy cost indictors. In refer to Pfarr (1976) and Stoy (2005) the amount of occupancy costs always depends on the following factors: usage, building characteristics, strategies, location and market dynamics. By examining the costs of 150 municipal buildings (schools, sport facilities) and all the factors that go into those costs, the research looks to both build on the investment versus occupancy cost analyses done by GSD (2003) and Stoy (2005, 2008) and help property owners identifying how they can better reduce occupancy expenditures and manage their investments more intelligently. The current collection of data forms the main part over the course of the study and comprises the investigation of occupancy costs (dependent variables) and the definition of relevant cost drivers (independent variables). Subsequently the collected data will be analysed by conducting a series of univariate analysis. First results will be presented in spring 2010. Cost-optimized and financially sustainable real estate can only be planned, built and used if the causal relationships existing between occupancy costs and their identified drivers can be confirmed and translated into practice. This empirical study seeks to make such a confirmation by quantifying the relevant drivers of occupancy costs. Based on these findings it will be possible to create occupancy cost benchmarks for early project phases and to specify design rules and basic conditions for planning, building and using financially sustainable real estate.