Innovative Enterprise Architecture (EA) approaches developed by researchers and focused on the evaluation and the analysis of organizations require an extensive set of "measurable" input parameters. In practice, organizations often cannot provide the required data, which makes the implementation of these approaches difficult. In this work, the authors specify the build-up process that represents a systematic identification, gathering, and consolidation of data required by the target EA approach. This paper illustrates the build-up process by presenting a case study where the research approach to business-IT fitness measurement, in the context of a real industrial project in a mass retail company, is implemented. Initially, the poor quality of the input data presented a serious threat for business-IT alignment assessment using the fitness measurements. After the input parameters have been built up, the applicability of the fitness measurements were significantly improved and alignment assessment was accomplished successfully. By using the build-up process, it is possible to increase the applicability of any research approach in EA and, in spite of the initial absence of input measurable parameters, to deliver meaningful results to practitioners.