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Corporate real estate (CRE) is a costly and risky asset in need of more rigorous evaluation methods to support strategic decision making for portfolio and asset management. Especially the indirect added value on organizational revenues is hard to quantify, while it is gaining importance. The purpose of this paper is to describe a quantitative technique that predicts office use as input for CRE management (CREM) decisions.

After a literature study to identify relevant aspects influencing office use in modern work environments, a Bayesian belief network (BN) is constructed from a large database of 80,907 observations of office use in three organizations in Belgium and the Netherlands. Next specific evidence from future scenarios of organizational change is entered to discuss the application of BN for CRE decision-making processes.

This study showed that the use of activity-based offices might be influenced by a complex network of office design variables and user characteristics. The use of the predicting possibilities of a BN model can help CRE managers identify employee behaviour inside their offices. That information is valuable input for future workplace decisions and strategic CREM activities.

This study provides CRE managers with a model to gain knowledge on office use to get a better grip on how to add value with activity-based office concepts. The results obtained through using such a model can help support decision making on their office layouts.

Bayesian BNs have not been used in this area of research before. This paper provides both academics and practitioners with valuable insights in the possibilities of this methodology for the field.