Real-time digitalisation refers to the continuous collection, integration, and analysis of operational building data, enabled by the integration of digital technologies into building management platforms. It is an advanced extension of building post-occupancy evaluation (POE) that transforms it from a static, retrospective evaluation process into a dynamic, data-driven methodology. In this entry, real-time digitalisation is discussed in relation to its role within the POE framework. The discussion includes a review of its evolution from early automation systems to contemporary cyber-physical infrastructures, supported by advanced analytics and machine learning. In addition, its dual benefits are highlighted as both a measurement tool and a decision-support system. Prevalent implementation complexities that limit its practicality in the building industry are also discussed. Real-time digitalisation is unlikely to replace conventional POE; instead, it broadens its capabilities, reconfiguring the process into a continuous, evidence-based building performance management process. The future relevance of real-time digitalisation to POE depends on its ability to become less technology-focused and more human-centric. Its infrastructure needs to align with occupant-subjective metrics, become more affordable, and increase its capacity to translate data into practical building management actions. As buildings become increasingly socio-technical systems, real-time digitalisation is emerging as a core methodological component of mainstream POE, with its importance spanning the entire lifecycle of buildings.
Post-occupancy evaluation (POE) relies on historical data from periodic building audits, occupant satisfaction surveys, and other retrospective performance assessments to determine whether buildings are performing as intended in relation to set targets such as energy use, environmental quality, and system function. While helpful, decision-making based on these time-bound data has made POE reactive rather than proactive, highlighting a performance gap in which projected performance gains from remedial actions do not match actual performance. The advent of real-time digitalisation promises to bridge this gap by enabling the continuous monitoring and acquisition of performance-related data through interconnected sensors, building management systems, and analytical platforms.
For example, research demonstrates its ability to support adaptive building management across the operational lifecycle by capturing granular, time-dependent data on various aspects of a building’s operations in real time
[1]. These data may include building energy consumption, indoor environmental quality (IEQ), system operation, and occupant behaviour
[2]. This enables the evaluation and even modification of the building’s performance while it is in use.
Real-time digitalisation can be described as a POE method that operates across two interconnected but distinct aspects, functioning as both a measurement tool and a decision-support system. As a measurement tool, it enables conventional POE to be extended towards greater diagnostic, predictive, preventive, and corrective capabilities
[3][4]. Descriptive questions like “what is wrong”, “why is it happening”, and “where is the problem originating from” can be asked and addressed in real time as the problem arises. As a decision-support system, continuous real-time data enable decision-making by supporting the analytical modelling of potential solutions to identified issues, as well as the benchmarking, comparison, verification, and modification of these solutions into strategic interventions
[5]. These two aspects position real-time digitalisation as a meaningful extension of POE.
This entry extends these discussions and examines whether this technological advancement represents the future of POE as a methodological evolution or a technological replacement.