In order to achieve the strategic goals, the company should utilise an efficient data gathering and analysis system for mapping the technical and economic situation, following up the development and detecting technical and economic deviations at an early stage to plan and perform necessary maintenance actions on time. In many cases, measuring and following up the development of relevant and well selected technical and economic performance measures can be more applicable for mapping the situation and making cost-effective decisions compared with monitoring big mount of data. But, in many cases it demands a reliable technique for interpretation of the behaviour of these performance measures especially if they are not linearly interrelated and if some of them reflect a combination of technical and financial impact. The problem addressed in this paper is; how is it possible to enhance the ability of detecting significant deviations in the maintenance performance measures at an early stage and tracing their root causes by using data- and knowledge base and inference engine? The major result achieved in this paper is a model developed for interpreting the changes in the maintenance performance measures and tracing their basic causes, which is verified in an example with typical data. The model consists of five modules; what performance measures to chose, how and why an eventual deviation on the performance measures occur, what to do to eliminate and prevent their reoccurrence and mapping of the current situation technically and financially. The main conclusion is that applying the model would enhance the ability of detecting changes in the maintenance performance through identifying the causes for elimination. In Al-Najjar et al (2004), a model for how to identify the measurable variables, which are needed to develop measures for monitoring maintenance performance behaviour systematically, is introduced and discussed. Also, five maintenance performance measures are propos