Purpose – This paper argues that usual key indicators used in real estate management only show differences to a planned level. For this reason we consider the construction of behavioural key indicators supporting the human decision-making and learning process to improve decision-making in real estate management.Design / methodology / approach – We draw on findings in the area of dynamic decision-making. This viewpoint implicates the existence of a dynamic system on the property level thus employing an analytical case for showing the dynamics in the rental cash flow pattern. Findings – The dynamics in real estate cash flow pattern are driven by interdependencies and feedback processes between a set of variables. Thus, traditional instruments of managing the rental process are prone to erroneous perception about the ‘real-world’. Furthermore classical key indicators neither support the human decision-making process as well as the learning process for understanding such dynamic systems. A computational system is proposed to address support for both the dynamic decision-making and learning process.Research limitations / implications – (1) More research is needed on the validation of dynamic behaviour in cash flow pattern. (2) Validation on the performance of decision-making in the specific context of the rental process is needed. For this paper it is intended to raise questions for future research rather than delivering answers to this difficult and complex topic. Originality / value – The paper provides a new viewpoint on decision-making in real estate management by means of transforming task methodology in real estate management.Paper type – Viewpoint, Case studyArticle Classification: R10, G02, G17, C58